No Cost – Low Cost Compressed Air System Optimization in Industry

NASA Astrophysics Data System (ADS)

Dharma, A.; Budiarsa, N.; Watiniasih, N.; Antara, N. G.

2018-04-01

Energy conservation is a systematic, integrated of effort, in order to preserve energy sources and improve energy utilization efficiency. Utilization of energy in efficient manner without reducing the energy usage it must. Energy conservation efforts are applied at all stages of utilization, from utilization of energy resources to final, using efficient technology, and cultivating an energy-efficient lifestyle. The most common way is to promote energy efficiency in the industry on end use and overcome barriers to achieve such efficiency by using system energy optimization programs. The facts show that energy saving efforts in the process usually only focus on replacing tools and not an overall system improvement effort. In this research, a framework of sustainable energy reduction work in companies that have or have not implemented energy management system (EnMS) will be conducted a systematic technical approach in evaluating accurately a compressed-air system and potential optimization through observation, measurement and verification environmental conditions and processes, then processing the physical quantities of systems such as air flow, pressure and electrical power energy at any given time measured using comparative analysis methods in this industry, to provide the potential savings of energy saving is greater than the component approach, with no cost to the lowest cost (no cost - low cost). The process of evaluating energy utilization and energy saving opportunities will provide recommendations for increasing efficiency in the industry and reducing CO2 emissions and improving environmental quality.

Optimization of blade motion of vertical axis turbine

NASA Astrophysics Data System (ADS)

Ma, Yong; Zhang, Liang; Zhang, Zhi-yang; Han, Duan-feng

2016-04-01

In this paper, a method is proposed to improve the energy efficiency of the vertical axis turbine. First of all, a single disk multiple stream-tube model is used to calculate individual fitness. Genetic algorithm is adopted to optimize blade pitch motion of vertical axis turbine with the maximum energy efficiency being selected as the optimization objective. Then, a particular data processing method is proposed, fitting the result data into a cosine-like curve. After that, a general formula calculating the blade motion is developed. Finally, CFD simulation is used to validate the blade pitch motion formula. The results show that the turbine's energy efficiency becomes higher after the optimization of blade pitch motion; compared with the fixed pitch turbine, the efficiency of variable-pitch turbine is significantly improved by the active blade pitch control; the energy efficiency declines gradually with the growth of speed ratio; besides, compactness has lager effect on the blade motion while the number of blades has little effect on it.

Bi-level Optimization Method of Air-conditioning System Based on Office Building Energy Storage Characteristics

NASA Astrophysics Data System (ADS)

Wang, Qingze; Chen, Xingying; Ji, Li; Liao, Yingchen; Yu, Kun

2017-05-01

The air-conditioning system of office building is a large power consumption terminal equipment, whose unreasonable operation mode leads to low energy efficiency. Realizing the optimization of the air-conditioning system has become one of the important research contents of the electric power demand response. In this paper, in order to save electricity cost and improve energy efficiency, bi-level optimization method of air-conditioning system based on TOU price is put forward by using the energy storage characteristics of the office building itself. In the upper level, the operation mode of the air-conditioning system is optimized in order to minimize the uses’ electricity cost in the premise of ensuring user’ comfort according to the information of outdoor temperature and TOU price, and the cooling load of the air-conditioning is output to the lower level; In the lower level, the distribution mode of cooling load among the multi chillers is optimized in order to maximize the energy efficiency according to the characteristics of each chiller. Finally, the experimental results under different modes demonstrate that the strategy can improve the energy efficiency of chillers and save the electricity cost for users.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks.

PubMed

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-04-19

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs. However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks

PubMed Central

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-01-01

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs). However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%. PMID:28422062

Basic aspects and contributions to the optimization of energy systems exploitation of a super tanker ship

NASA Astrophysics Data System (ADS)

Faitar, C.; Novac, I.

2017-08-01

Today, the concept of energy efficiency or energy optimization in ships has become one of the main problems of engineers in the whole world. To increase the fiability of a crude oil super tanker ship it means, among other things, to improve the energy performance and optimize the fuel consumption of ship through the development of engines and propulsion system or using alternative energies. Also, the importance of having an effective and reliable Power Management System (PMS) in a vessel operating system means to reduce operational costs and maintain power system of machine parts working in minimum stress in all operating conditions. Studying the Energy Efficiency Design Index and Energy Efficiency Operational Indicator for a crude oil super tanker ship, it allows us to study the reconfiguration of ship power system introducing new generation systems.

Energy-saving management modelling and optimization for lead-acid battery formation process

NASA Astrophysics Data System (ADS)

Wang, T.; Chen, Z.; Xu, J. Y.; Wang, F. Y.; Liu, H. M.

2017-11-01

In this context, a typical lead-acid battery producing process is introduced. Based on the formation process, an efficiency management method is proposed. An optimization model with the objective to minimize the formation electricity cost in a single period is established. This optimization model considers several related constraints, together with two influencing factors including the transformation efficiency of IGBT charge-and-discharge machine and the time-of-use price. An example simulation is shown using PSO algorithm to solve this mathematic model, and the proposed optimization strategy is proved to be effective and learnable for energy-saving and efficiency optimization in battery producing industries.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.

PubMed

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-05-21

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-01-01

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods. PMID:29883410

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

EFFICIENCY OPTIMIZATIN CONTROL OF AC INDUCTION MOTORS: INITIAL LABORATORY RESULTS

EPA Science Inventory

The report discusses the development of a fuzzy logic, energy-optimizing controller to improve the efficiency of motor/drive combinations that operate at varying loads and speeds. This energy optimizer is complemented by a sensorless speed controller that maintains motor shaft re...

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals

NASA Astrophysics Data System (ADS)

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals.

PubMed

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Lermusiaux, Pierre F. J.

2016-04-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

Energy Harvesting Based Body Area Networks for Smart Health.

PubMed

Hao, Yixue; Peng, Limei; Lu, Huimin; Hassan, Mohammad Mehedi; Alamri, Atif

2017-07-10

Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device's battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive.

Energy Harvesting Based Body Area Networks for Smart Health

PubMed Central

Hao, Yixue; Peng, Limei; Alamri, Atif

2017-01-01

Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device’s battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive. PMID:28698501

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

PubMed Central

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

BUILDING ENVELOPE OPTIMIZATION USING EMERGY ANALYSIS

EPA Science Inventory

Energy analysis is an integral component of sustainable building practices. Energy analysis coupled with optimization techniques may offer solutions for greater energy efficiency over the lifetime of the building. However, all such computationsemploy the energy used for operation...

The assessment of global thermo-energy performances of existing district heating systems optimized by harnessing renewable energy sources

NASA Astrophysics Data System (ADS)

Şoimoşan, Teodora M.; Danku, Gelu; Felseghi, Raluca A.

2017-12-01

Within the thermo-energy optimization process of an existing heating system, the increase of the system's energy efficiency and speeding-up the transition to green energy use are pursued. The concept of multi-energy district heating system, with high harnessing levels of the renewable energy sources (RES) in order to produce heat, is expected to be the key-element in the future urban energy infrastructure, due to the important role it can have in the strategies of optimizing and decarbonizing the existing district heating systems. The issues that arise are related to the efficient integration of different technologies of harnessing renewable energy sources in the energy mix and to the increase of the participation levels of RES, respectively. For the holistic modeling of the district heating system, the concept of the energy hub was used, where the synergy of different primary forms of entered energy provides the system a high degree energy security and flexibility in operation. The optimization of energy flows within the energy hub allows the optimization of the thermo-energy district system in order to approach the dual concept of smart city & smart energy.

[Research on the photoelectric conversion efficiency of grating antireflective layer solar cells].

PubMed

Zhong, Hui; Gao, Yong-Yi; Zhou, Ren-Long; Zhou, Bing-ju; Tang, Li-qiang; Wu, Ling-xi; Li, Hong-jian

2011-07-01

A numerical investigation of the effect of grating antireflective layer structure on the photoelectric conversion efficiency of solar cells was carried out by the finite-difference time-domain method. The influence of grating shape, height and the metal film thickness coated on grating surface on energy storage was analyzed in detail. It was found that the comparison between unoptimized and optimized surface grating structure on solar cells shows that the optimization of surface by grating significantly increases the energy storage capability and greatly improves the efficiency, especially of the photoelectric conversion efficiency and energy storage of the triangle grating. As the film thickness increases, energy storage effect increases, while as the film thickness is too thick, energy storage effect becomes lower and lower.

Experiences in autotuning matrix multiplication for energy minimization on GPUs

DOE PAGES

Anzt, Hartwig; Haugen, Blake; Kurzak, Jakub; ...

2015-05-20

In this study, we report extensive results and analysis of autotuning the computationally intensive graphics processing units kernel for dense matrix–matrix multiplication in double precision. In contrast to traditional autotuning and/or optimization for runtime performance only, we also take the energy efficiency into account. For kernels achieving equal performance, we show significant differences in their energy balance. We also identify the memory throughput as the most influential metric that trades off performance and energy efficiency. Finally, as a result, the performance optimal case ends up not being the most efficient kernel in overall resource use.

A novel vortex tube-based N2-expander liquefaction process for enhancing the energy efficiency of natural gas liquefaction

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Wei, Feng; Hussain, Arif; Ali, Wahid; Sehee, Oh; Lee, Moonyong

2017-11-01

This research work unfolds a simple, safe, and environment-friendly energy efficient novel vortex tube-based natural gas liquefaction process (LNG). A vortex tube was introduced to the popular N2-expander liquefaction process to enhance the liquefaction efficiency. The process structure and condition were modified and optimized to take a potential advantage of the vortex tube on the natural gas liquefaction cycle. Two commercial simulators ANSYS® and Aspen HYSYS® were used to investigate the application of vortex tube in the refrigeration cycle of LNG process. The Computational fluid dynamics (CFD) model was used to simulate the vortex tube with nitrogen (N2) as a working fluid. Subsequently, the results of the CFD model were embedded in the Aspen HYSYS® to validate the proposed LNG liquefaction process. The proposed natural gas liquefaction process was optimized using the knowledge-based optimization (KBO) approach. The overall energy consumption was chosen as an objective function for optimization. The performance of the proposed liquefaction process was compared with the conventional N2-expander liquefaction process. The vortex tube-based LNG process showed a significant improvement of energy efficiency by 20% in comparison with the conventional N2-expander liquefaction process. This high energy efficiency was mainly due to the isentropic expansion of the vortex tube. It turned out that the high energy efficiency of vortex tube-based process is totally dependent on the refrigerant cold fraction, operating conditions as well as refrigerant cycle configurations.

An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks

PubMed Central

Penumalli, Chakradhar; Palanichamy, Yogesh

2015-01-01

A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results. PMID:26221627

Data on cost-optimal Nearly Zero Energy Buildings (NZEBs) across Europe.

PubMed

D'Agostino, Delia; Parker, Danny

2018-04-01

This data article refers to the research paper A model for the cost-optimal design of Nearly Zero Energy Buildings (NZEBs) in representative climates across Europe [1]. The reported data deal with the design optimization of a residential building prototype located in representative European locations. The study focus on the research of cost-optimal choices and efficiency measures in new buildings depending on the climate. The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data allow to visualize energy consumption before and after the optimization, selected efficiency measures, costs and renewable production. The reduction of electricity and natural gas consumption towards the NZEB target can be visualized together with incremental and cumulative costs in each location. Further data is available about building geometry, costs, CO 2 emissions, envelope, materials, lighting, appliances and systems.

Efficiency of quantum vs. classical annealing in nonconvex learning problems

PubMed Central

Zecchina, Riccardo

2018-01-01

Quantum annealers aim at solving nonconvex optimization problems by exploiting cooperative tunneling effects to escape local minima. The underlying idea consists of designing a classical energy function whose ground states are the sought optimal solutions of the original optimization problem and add a controllable quantum transverse field to generate tunneling processes. A key challenge is to identify classes of nonconvex optimization problems for which quantum annealing remains efficient while thermal annealing fails. We show that this happens for a wide class of problems which are central to machine learning. Their energy landscapes are dominated by local minima that cause exponential slowdown of classical thermal annealers while simulated quantum annealing converges efficiently to rare dense regions of optimal solutions. PMID:29382764

NREL Leads Energy Systems Integration - Continuum Magazine | NREL

Science.gov Websites

performance data to manage and optimize campus energy use. Integrated Solutions for a Complex Energy World 03 Integrated Solutions for a Complex Energy World Energy systems integration optimizes the design and efficient data centers in the world. Sustainability through Dynamic Energy Management Sustainability through

Bacterial growth laws reflect the evolutionary importance of energy efficiency.

PubMed

Maitra, Arijit; Dill, Ken A

2015-01-13

We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized in Escherichia coli. Is E. coli optimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit, E. coli produces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell's fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions.

Optimizing Irregular Applications for Energy and Performance on the Tilera Many-core Architecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavarría-Miranda, Daniel; Panyala, Ajay R.; Halappanavar, Mahantesh

Optimizing applications simultaneously for energy and performance is a complex problem. High performance, parallel, irregular applications are notoriously hard to optimize due to their data-dependent memory accesses, lack of structured locality and complex data structures and code patterns. Irregular kernels are growing in importance in applications such as machine learning, graph analytics and combinatorial scientific computing. Performance- and energy-efficient implementation of these kernels on modern, energy efficient, multicore and many-core platforms is therefore an important and challenging problem. We present results from optimizing two irregular applications { the Louvain method for community detection (Grappolo), and high-performance conjugate gradient (HPCCG) {more » on the Tilera many-core system. We have significantly extended MIT's OpenTuner auto-tuning framework to conduct a detailed study of platform-independent and platform-specific optimizations to improve performance as well as reduce total energy consumption. We explore the optimization design space along three dimensions: memory layout schemes, compiler-based code transformations, and optimization of parallel loop schedules. Using auto-tuning, we demonstrate whole node energy savings of up to 41% relative to a baseline instantiation, and up to 31% relative to manually optimized variants.« less

Planning energy-efficient bipedal locomotion on patterned terrain

NASA Astrophysics Data System (ADS)

Zamani, Ali; Bhounsule, Pranav A.; Taha, Ahmad

2016-05-01

Energy-efficient bipedal walking is essential in realizing practical bipedal systems. However, current energy-efficient bipedal robots (e.g., passive-dynamics-inspired robots) are limited to walking at a single speed and step length. The objective of this work is to address this gap by developing a method of synthesizing energy-efficient bipedal locomotion on patterned terrain consisting of stepping stones using energy-efficient primitives. A model of Cornell Ranger (a passive-dynamics inspired robot) is utilized to illustrate our technique. First, an energy-optimal trajectory control problem for a single step is formulated and solved. The solution minimizes the Total Cost Of Transport (TCOT is defined as the energy used per unit weight per unit distance travelled) subject to various constraints such as actuator limits, foot scuffing, joint kinematic limits, ground reaction forces. The outcome of the optimization scheme is a table of TCOT values as a function of step length and step velocity. Next, we parameterize the terrain to identify the location of the stepping stones. Finally, the TCOT table is used in conjunction with the parameterized terrain to plan an energy-efficient stepping strategy.

BEopt-CA (Ex) -- A Tool for Optimal Integration of EE/DR/ES+PV in Existing California Homes. Cooperative Research and Development Final Report, CRADA Number CRD-11-429

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christensen, Craig

Opportunities for combining energy efficiency, demand response, and energy storage with PV are often missed, because the required knowledge and expertise for these different technologies exist in separate organizations or individuals. Furthermore, there is a lack of quantitative tools to optimize energy efficiency, demand response and energy storage with PV, especially for existing buildings. Our goal is to develop a modeling tool, BEopt-CA (Ex), with capabilities to facilitate identification and implementation of a balanced integration of energy efficiency (EE), demand response (DR), and energy storage (ES) with photovoltaics (PV) within the residential retrofit market. To achieve this goal, we willmore » adapt and extend an existing tool -- BEopt -- that is designed to identify optimal combinations of efficiency and PV in new home designs. In addition, we will develop multifamily residential modeling capabilities for use in California, to facilitate integration of distributed solar power into the grid in order to maximize its value to California ratepayers. The project is follow-on research that leverages previous California Solar Initiative RD&D investment in the BEopt software. BEopt facilitates finding the least cost combination of energy efficiency and renewables to support integrated DSM (iDSM) and Zero Net Energy (ZNE) in California residential buildings. However, BEopt is currently focused on modeling single-family houses and does not include satisfactory capabilities for modeling multifamily homes. The project brings BEopt's existing modeling and optimization capabilities to multifamily buildings, including duplexes, triplexes, townhouses, flats, and low-rise apartment buildings.« less

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications

NASA Technical Reports Server (NTRS)

Aldrich, Jack B.; Okon, Avi B.

2012-01-01

The need to maintain optimal energy efficiency is critical during the drilling operations performed on future and current planetary rover missions (see figure). Specifically, this innovation seeks to solve the following problem. Given a spring-loaded percussive drill driven by a voice-coil motor, one needs to determine the optimal input voltage waveform (periodic function) and the optimal hammering period that minimizes the dissipated energy, while ensuring that the hammer-to-rock impacts are made with sufficient (user-defined) impact velocity (or impact energy). To solve this problem, it was first observed that when voice-coil-actuated percussive drills are driven at high power, it is of paramount importance to ensure that the electrical current of the device remains in phase with the velocity of the hammer. Otherwise, negative work is performed and the drill experiences a loss of performance (i.e., reduced impact energy) and an increase in Joule heating (i.e., reduction in energy efficiency). This observation has motivated many drilling products to incorporate the standard bang-bang control approach for driving their percussive drills. However, the bang-bang control approach is significantly less efficient than the optimal energy-efficient control approach solved herein. To obtain this solution, the standard tools of classical optimal control theory were applied. It is worth noting that these tools inherently require the solution of a two-point boundary value problem (TPBVP), i.e., a system of differential equations where half the equations have unknown boundary conditions. Typically, the TPBVP is impossible to solve analytically for high-dimensional dynamic systems. However, for the case of the spring-loaded vibro-impactor, this approach yields the exact optimal control solution as the sum of four analytic functions whose coefficients are determined using a simple, easy-to-implement algorithm. Once the optimal control waveform is determined, it can be used optimally in the context of both open-loop and closed-loop control modes (using standard realtime control hardware).

Energy management and cooperation in microgrids

NASA Astrophysics Data System (ADS)

Rahbar, Katayoun

Microgrids are key components of future smart power grids, which integrate distributed renewable energy generators to efficiently serve the load demand locally. However, random and intermittent characteristics of renewable energy generations may hinder the reliable operation of microgrids. This thesis is thus devoted to investigating new strategies for microgrids to optimally manage their energy consumption, energy storage system (ESS) and cooperation in real time to achieve the reliable and cost-effective operation. This thesis starts with a single microgrid system. The optimal energy scheduling and ESS management policy is derived to minimize the energy cost of the microgrid resulting from drawing conventional energy from the main grid under both the off-line and online setups, where the renewable energy generation/load demand are assumed to be non-causally known and causally known at the microgrid, respectively. The proposed online algorithm is designed based on the optimal off-line solution and works under arbitrary (even unknown) realizations of future renewable energy generation/load demand. Therefore, it is more practically applicable as compared to solutions based on conventional techniques such as dynamic programming and stochastic programming that require the prior knowledge of renewable energy generation and load demand realizations/distributions. Next, for a group of microgrids that cooperate in energy management, we study efficient methods for sharing energy among them for both fully and partially cooperative scenarios, where microgrids are of common interests and self-interested, respectively. For the fully cooperative energy management, the off-line optimization problem is first formulated and optimally solved, where a distributed algorithm is proposed to minimize the total (sum) energy cost of microgrids. Inspired by the results obtained from the off-line optimization, efficient online algorithms are proposed for the real-time energy management, which are of low complexity and work given arbitrary realizations of renewable energy generation/load demand. On the other hand, for self-interested microgrids, the partially cooperative energy management is formulated and a distributed algorithm is proposed to optimize the energy cooperation such that energy costs of individual microgrids reduce simultaneously over the case without energy cooperation while limited information is shared among the microgrids and the central controller.

Optimization of Thermal Object Nonlinear Control Systems by Energy Efficiency Criterion.

NASA Astrophysics Data System (ADS)

Velichkin, Vladimir A.; Zavyalov, Vladimir A.

2018-03-01

This article presents the results of thermal object functioning control analysis (heat exchanger, dryer, heat treatment chamber, etc.). The results were used to determine a mathematical model of the generalized thermal control object. The appropriate optimality criterion was chosen to make the control more energy-efficient. The mathematical programming task was formulated based on the chosen optimality criterion, control object mathematical model and technological constraints. The “maximum energy efficiency” criterion helped avoid solving a system of nonlinear differential equations and solve the formulated problem of mathematical programming in an analytical way. It should be noted that in the case under review the search for optimal control and optimal trajectory reduces to solving an algebraic system of equations. In addition, it is shown that the optimal trajectory does not depend on the dynamic characteristics of the control object.

Optimization of gear ratio and power distribution for a multimotor powertrain of an electric vehicle

NASA Astrophysics Data System (ADS)

Urbina Coronado, Pedro Daniel; Orta Castañón, Pedro; Ahuett-Garza, Horacio

2018-02-01

The architecture and design of the propulsion system of electric vehicles are highly important for the reduction of energy losses. This work presents a powertrain composed of four electric motors in which each motor is connected with a different gear ratio to the differential of the rear axle. A strategy to reduce energy losses is proposed, in which two phases are applied. Phase 1 uses a divide-and-conquer approach to increase the overall output efficiency by obtaining the optimal torque distribution for the electric motors. Phase 2 applies a genetic algorithm to find the optimal value of the gear ratios, in which each individual of each generation applies Phase 1. The results show an optimized efficiency map for the output torque and speed of the powertrain. The increase in efficiency and the reduction of energy losses are validated by the use of numerical experiments in various driving cycles.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

PubMed

Meng, Qing-chun; Rong, Xiao-xia; Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants

PubMed Central

Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996–2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated. PMID:27010658

Performance Analysis and Optimization of Concentrating Solar Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Lamba, Ravita; Manikandan, S.; Kaushik, S. C.

2018-06-01

A thermodynamic model for a concentrating solar thermoelectric generator considering the Thomson effect combined with Fourier heat conduction, Peltier, and Joule heating has been developed and optimized in MATLAB environment. The temperatures at the hot and cold junctions of the thermoelectric generator were evaluated by solving the energy balance equations at both junctions. The effects of the solar concentration ratio, input electrical current, number of thermocouples, and electrical load resistance ratio on the power output and energy and exergy efficiencies of the system were studied. Optimization studies were carried out for the STEG system, and the optimum number of thermocouples, concentration ratio, and resistance ratio determined. The results showed that the optimum values of these parameters are different for conditions of maximum power output and maximum energy and exergy efficiency. The optimum values of the concentration ratio and load resistance ratio for maximum energy efficiency of 5.85% and maximum exergy efficiency of 6.29% were found to be 180 and 1.3, respectively, with corresponding power output of 4.213 W. Furthermore, at higher concentration ratio (C = 600), the optimum number of thermocouples was found to be 101 for maximum power output of 13.75 W, maximum energy efficiency of 5.73%, and maximum exergy efficiency of 6.16%. Moreover, the optimum number of thermocouple was the same for conditions of maximum power output and energy and exergy efficiency. The results of this study may provide insight for design of actual concentrated solar thermoelectric generator systems.

Scott Horowitz | NREL

Science.gov Websites

area, which includes work on whole building energy modeling, cost-based optimization, model accuracy optimization tool used to provide support for the Building America program's teams and energy efficiency goals Colorado graduate student exploring enhancements to building optimization in terms of robustness and speed

Cross-layer cluster-based energy-efficient protocol for wireless sensor networks.

PubMed

Mammu, Aboobeker Sidhik Koyamparambil; Hernandez-Jayo, Unai; Sainz, Nekane; de la Iglesia, Idoia

2015-04-09

Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).

Application configuration selection for energy-efficient execution on multicore systems

DOE PAGES

Wang, Shinan; Luo, Bing; Shi, Weisong; ...

2015-09-21

Balanced performance and energy consumption are incorporated in the design of modern computer systems. Several runtime factors, such as concurrency levels, thread mapping strategies, and dynamic voltage and frequency scaling (DVFS) should be considered in order to achieve optimal energy efficiency fora workload. Selecting appropriate run-time factors, however, is one of the most challenging tasks because the run-time factors are architecture-specific and workload-specific. And while most existing works concentrate on either static analysis of the workload or run-time prediction results, we present a hybrid two-step method that utilizes concurrency levels and DVFS settings to achieve the energy efficiency configuration formore » a worldoad. The experimental results based on a Xeon E5620 server with NPB and PARSEC benchmark suites show that the model is able to predict the energy efficient configuration accurately. On average, an additional 10% EDP (Energy Delay Product) saving is obtained by using run-time DVFS for the entire system. An off-line optimal solution is used to compare with the proposed scheme. Finally, the experimental results show that the average extra EDP saved by the optimal solution is within 5% on selective parallel benchmarks.« less

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks

PubMed Central

Cheng, Wenchi; Zhang, Hailin

2017-01-01

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks. PMID:28832509

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

PubMed

Gao, Ya; Cheng, Wenchi; Zhang, Hailin

2017-08-23

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

Energy efficiency analysis of the manipulation process by the industrial objects with the use of Bernoulli gripping devices

NASA Astrophysics Data System (ADS)

Savkiv, Volodymyr; Mykhailyshyn, Roman; Duchon, Frantisek; Mikhalishin, Mykhailo

2017-11-01

The article deals with the topical issue of reducing energy consumption for transportation of industrial objects. The energy efficiency of the process of objects manipulation with the use of the orientation optimization method while gripping with the help of different methods has been studied. The analysis of the influence of the constituent parts of inertial forces, that affect the object of manipulation, on the necessary force characteristics and energy consumption of Bernoulli gripping device has been proposed. The economic efficiency of the use of the optimal orientation of Bernoulli gripping device while transporting the object of manipulation in comparison to the transportation without re-orientation has been proved.

Passive designs and renewable energy systems optimization of a net zero energy building in Embrun/France

NASA Astrophysics Data System (ADS)

Harkouss, F.; Biwole, P. H.; Fardoun, F.

2018-05-01

Buildings’ optimization is a smart method to inspect the available design choices starting from passive strategies, to energy efficient systems and finally towards the adequate renewable energy system to be implemented. This paper outlines the methodology and the cost-effectiveness potential for optimizing the design of net-zero energy building in a French city; Embrun. The non-dominated sorting genetic algorithm is chosen in order to minimize thermal, electrical demands and life cycle cost while reaching the net zero energy balance; and thus getting the Pareto-front. Elimination and Choice Expressing the Reality decision making method is applied to the Pareto-front so as to obtain one optimal solution. A wide range of energy efficiency measures are investigated, besides solar energy systems are employed to produce required electricity and hot water for domestic purposes. The results indicate that the appropriate selection of the passive parameters is very important and critical in reducing the building energy consumption. The optimum design parameters yield to a decrease of building’s thermal loads and life cycle cost by 32.96% and 14.47% respectively.

Overall Traveling-Wave-Tube Efficiency Improved By Optimized Multistage Depressed Collector Design

NASA Technical Reports Server (NTRS)

Vaden, Karl R.

2002-01-01

Depressed Collector Design The microwave traveling wave tube (TWT) is used widely for space communications and high-power airborne transmitting sources. One of the most important features in designing a TWT is overall efficiency. Yet, overall TWT efficiency is strongly dependent on the efficiency of the electron beam collector, particularly for high values of collector efficiency. For these reasons, the NASA Glenn Research Center developed an optimization algorithm based on simulated annealing to quickly design highly efficient multistage depressed collectors (MDC's). Simulated annealing is a strategy for solving highly nonlinear combinatorial optimization problems. Its major advantage over other methods is its ability to avoid becoming trapped in local minima. Simulated annealing is based on an analogy to statistical thermodynamics, specifically the physical process of annealing: heating a material to a temperature that permits many atomic rearrangements and then cooling it carefully and slowly, until it freezes into a strong, minimum-energy crystalline structure. This minimum energy crystal corresponds to the optimal solution of a mathematical optimization problem. The TWT used as a baseline for optimization was the 32-GHz, 10-W, helical TWT developed for the Cassini mission to Saturn. The method of collector analysis and design used was a 2-1/2-dimensional computational procedure that employs two types of codes, a large signal analysis code and an electron trajectory code. The large signal analysis code produces the spatial, energetic, and temporal distributions of the spent beam entering the MDC. An electron trajectory code uses the resultant data to perform the actual collector analysis. The MDC was optimized for maximum MDC efficiency and minimum final kinetic energy of all collected electrons (to reduce heat transfer). The preceding figure shows the geometric and electrical configuration of an optimized collector with an efficiency of 93.8 percent. The results show the improvement in collector efficiency from 89.7 to 93.8 percent, resulting in an increase of three overall efficiency points. In addition, the time to design a highly efficient MDC was reduced from a month to a few days. All work was done in-house at Glenn for the High Rate Data Delivery Program. Future plans include optimizing the MDC and TWT interaction circuit in tandem to further improve overall TWT efficiency.

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

PubMed Central

Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad

2013-01-01

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. PMID:23966194

Energy and operation management of a microgrid using particle swarm optimization

NASA Astrophysics Data System (ADS)

Radosavljević, Jordan; Jevtić, Miroljub; Klimenta, Dardan

2016-05-01

This article presents an efficient algorithm based on particle swarm optimization (PSO) for energy and operation management (EOM) of a microgrid including different distributed generation units and energy storage devices. The proposed approach employs PSO to minimize the total energy and operating cost of the microgrid via optimal adjustment of the control variables of the EOM, while satisfying various operating constraints. Owing to the stochastic nature of energy produced from renewable sources, i.e. wind turbines and photovoltaic systems, as well as load uncertainties and market prices, a probabilistic approach in the EOM is introduced. The proposed method is examined and tested on a typical grid-connected microgrid including fuel cell, gas-fired microturbine, wind turbine, photovoltaic and energy storage devices. The obtained results prove the efficiency of the proposed approach to solve the EOM of the microgrids.

Efficiency Analysis of Waveform Shape for Electrical Excitation of Nerve Fibers

PubMed Central

Wongsarnpigoon, Amorn; Woock, John P.; Grill, Warren M.

2011-01-01

Stimulation efficiency is an important consideration in the stimulation parameters of implantable neural stimulators. The objective of this study was to analyze the effects of waveform shape and duration on the charge, power, and energy efficiency of neural stimulation. Using a population model of mammalian axons and in vivo experiments on cat sciatic nerve, we analyzed the stimulation efficiency of four waveform shapes: square, rising exponential, decaying exponential, and rising ramp. No waveform was simultaneously energy-, charge-, and power-optimal, and differences in efficiency among waveform shapes varied with pulse width (PW) For short PWs (≤ 0.1 ms), square waveforms were no less energy-efficient than exponential waveforms, and the most charge-efficient shape was the ramp. For long PWs (≥0.5 ms), the square was the least energy-efficient and charge-efficient shape, but across most PWs, the square was the most power-efficient shape. Rising exponentials provided no practical gains in efficiency over the other shapes, and our results refute previous claims that the rising exponential is the energy-optimal shape. An improved understanding of how stimulation parameters affect stimulation efficiency will help improve the design and programming of implantable stimulators to minimize tissue damage and extend battery life. PMID:20388602

Vacuum Pump System Optimization Saves Energy at a Dairy Farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

In 1998, S&S Dairy optimized the vacuum pumping system at their dairy farm in Modesto, California. In an effort to reduce energy costs, S&S Dairy evaluated their vacuum pumping system to determine if efficiency gains and energy savings were possible.

Efficiency Optimization for FEL Oscillators,

DTIC Science & Technology

1987-12-01

I 7 -ŕvle 3IIATIONCIFOR FEL OSCILLATORS(U) MARYLAND i/1’ UNIV COLLEGE PARK LAS FOR PLASMIA AND FUSION ENERGY STUDIES A SERBETO ET AL DEC 87 UMLPF-88...University of Maryland, By3 f *O- 0Laboratory for Plasrra and Fusion Energy Studies D i~ Avciil adi r "UnOUIO SAEMNT A APPrOVed for public reloe...Distribution Unlimited EFFICIENCY OPTIMIZATION FOR FEL OSCILLATORS A. Serbeto, B. Levush, and T. M. Antonsen, Jr. Laboratory for Plasma and Fusion Energy Studies

Increasing energy efficiency level of building production based on applying modern mechanization facilities

NASA Astrophysics Data System (ADS)

Prokhorov, Sergey

2017-10-01

Building industry in a present day going through the hard times. Machine and mechanism exploitation cost, on a field of construction and installation works, takes a substantial part in total building construction expenses. There is a necessity to elaborate high efficient method, which allows not only to increase production, but also to reduce direct costs during machine fleet exploitation, and to increase its energy efficiency. In order to achieve the goal we plan to use modern methods of work production, hi-tech and energy saving machine tools and technologies, and use of optimal mechanization sets. As the optimization criteria there are exploitation prime cost and set efficiency. During actual task-solving process we made a conclusion, which shows that mechanization works, energy audit with production juxtaposition, prime prices and costs for energy resources allow to make complex machine fleet supply, improve ecological level and increase construction and installation work quality.

Sensitivity analysis and optimization method for the fabrication of one-dimensional beam-splitting phase gratings

PubMed Central

Pacheco, Shaun; Brand, Jonathan F.; Zaverton, Melissa; Milster, Tom; Liang, Rongguang

2015-01-01

A method to design one-dimensional beam-spitting phase gratings with low sensitivity to fabrication errors is described. The method optimizes the phase function of a grating by minimizing the integrated variance of the energy of each output beam over a range of fabrication errors. Numerical results for three 1x9 beam splitting phase gratings are given. Two optimized gratings with low sensitivity to fabrication errors were compared with a grating designed for optimal efficiency. These three gratings were fabricated using gray-scale photolithography. The standard deviation of the 9 outgoing beam energies in the optimized gratings were 2.3 and 3.4 times lower than the optimal efficiency grating. PMID:25969268

Energy Efficiency Optimization in Relay-Assisted MIMO Systems With Perfect and Statistical CSI

NASA Astrophysics Data System (ADS)

Zappone, Alessio; Cao, Pan; Jorswieck, Eduard A.

2014-01-01

A framework for energy-efficient resource allocation in a single-user, amplify-and-forward relay-assisted MIMO system is devised in this paper. Previous results in this area have focused on rate maximization or sum power minimization problems, whereas fewer results are available when bits/Joule energy efficiency (EE) optimization is the goal. The performance metric to optimize is the ratio between the system's achievable rate and the total consumed power. The optimization is carried out with respect to the source and relay precoding matrices, subject to QoS and power constraints. Such a challenging non-convex problem is tackled by means of fractional programming and and alternating maximization algorithms, for various CSI assumptions at the source and relay. In particular the scenarios of perfect CSI and those of statistical CSI for either the source-relay or the relay-destination channel are addressed. Moreover, sufficient conditions for beamforming optimality are derived, which is useful in simplifying the system design. Numerical results are provided to corroborate the validity of the theoretical findings.

Energy efficient LED layout optimization for near-uniform illumination

NASA Astrophysics Data System (ADS)

Ali, Ramy E.; Elgala, Hany

2016-09-01

In this paper, we consider the problem of designing energy efficient light emitting diodes (LEDs) layout while satisfying the illumination constraints. Towards this objective, we present a simple approach to the illumination design problem based on the concept of the virtual LED. We formulate a constrained optimization problem for minimizing the power consumption while maintaining a near-uniform illumination throughout the room. By solving the resulting constrained linear program, we obtain the number of required LEDs and the optimal output luminous intensities that achieve the desired illumination constraints.

Minimum energy control and optimal-satisfactory control of Boolean control network

NASA Astrophysics Data System (ADS)

Li, Fangfei; Lu, Xiwen

2013-12-01

In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.

Data-Driven Sampling Matrix Boolean Optimization for Energy-Efficient Biomedical Signal Acquisition by Compressive Sensing.

PubMed

Wang, Yuhao; Li, Xin; Xu, Kai; Ren, Fengbo; Yu, Hao

2017-04-01

Compressive sensing is widely used in biomedical applications, and the sampling matrix plays a critical role on both quality and power consumption of signal acquisition. It projects a high-dimensional vector of data into a low-dimensional subspace by matrix-vector multiplication. An optimal sampling matrix can ensure accurate data reconstruction and/or high compression ratio. Most existing optimization methods can only produce real-valued embedding matrices that result in large energy consumption during data acquisition. In this paper, we propose an efficient method that finds an optimal Boolean sampling matrix in order to reduce the energy consumption. Compared to random Boolean embedding, our data-driven Boolean sampling matrix can improve the image recovery quality by 9 dB. Moreover, in terms of sampling hardware complexity, it reduces the energy consumption by 4.6× and the silicon area by 1.9× over the data-driven real-valued embedding.

Efficiency optimization of wireless power transmission systems for active capsule endoscopes.

PubMed

Zhiwei, Jia; Guozheng, Yan; Jiangpingping; Zhiwu, Wang; Hua, Liu

2011-10-01

Multipurpose active capsule endoscopes have drawn considerable attention in recent years, but these devices continue to suffer from energy limitations. A wireless power supply system is regarded as a practical way to overcome the power shortage problem in such devices. This paper focuses on the efficiency optimization of a wireless energy supply system with size and safety constraints. A mathematical programming model in which these constraints are considered is proposed for transmission efficiency, optimal frequency and current, and overall system effectiveness. To verify the feasibility of the proposed method, we use a wireless active capsule endoscope as an illustrative example. The achieved efficiency can be regarded as an index for evaluating the system, and the proposed approach can be used to direct the design of transmitting and receiving coils.

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

PubMed

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-03-20

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

PubMed Central

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-01-01

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments. PMID:23519351

Exergy Based Analysis for the Environmental Control and Life Support Systems of the International Space Station

NASA Technical Reports Server (NTRS)

Clem, Kirk A.; Nelson, George J.; Mesmer, Bryan L.; Watson, Michael D.; Perry, Jay L.

2016-01-01

When optimizing the performance of complex systems, a logical area for concern is improving the efficiency of useful energy. The energy available for a system to perform work is defined as a system's energy content. Interactions between a system's subsystems and the surrounding environment can be accounted for by understanding various subsystem energy efficiencies. Energy balance of reactants and products, and enthalpies and entropies, can be used to represent a chemical process. Heat transfer energy represents heat loads, and flow energy represents system flows and filters. These elements allow for a system level energy balance. The energy balance equations are developed for the subsystems of the Environmental Control and Life Support (ECLS) system aboard the International Space Station (ISS). The use of these equations with system information would allow for the calculation of the energy efficiency of the system, enabling comparisons of the ISS ECLS system to other systems as well as allows for an integrated systems analysis for system optimization.

Design and Implementation of a Wireless Sensor and Actuator Network to Support the Intelligent Control of Efficient Energy Usage.

PubMed

Blanco, Jesús; García, Andrés; Morenas, Javier de Las

2018-06-09

Energy saving has become a major concern for the developed society of our days. This paper presents a Wireless Sensor and Actuator Network (WSAN) designed to provide support to an automatic intelligent system, based on the Internet of Things (IoT), which enables a responsible consumption of energy. The proposed overall system performs an efficient energetic management of devices, machines and processes, optimizing their operation to achieve a reduction in their overall energy usage at any given time. For this purpose, relevant data is collected from intelligent sensors, which are in-stalled at the required locations, as well as from the energy market through the Internet. This information is analysed to provide knowledge about energy utilization, and to improve efficiency. The system takes autonomous decisions automatically, based on the available information and the specific requirements in each case. The proposed system has been implanted and tested in a food factory. Results show a great optimization of energy efficiency and a substantial improvement on energy and costs savings.

Simulation based energy-resource efficient manufacturing integrated with in-process virtual management

NASA Astrophysics Data System (ADS)

Katchasuwanmanee, Kanet; Cheng, Kai; Bateman, Richard

2016-09-01

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow (productivity) and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.

Efficient Round-Trip Time Optimization for Replica-Exchange Enveloping Distribution Sampling (RE-EDS).

PubMed

Sidler, Dominik; Cristòfol-Clough, Michael; Riniker, Sereina

2017-06-13

Replica-exchange enveloping distribution sampling (RE-EDS) allows the efficient estimation of free-energy differences between multiple end-states from a single molecular dynamics (MD) simulation. In EDS, a reference state is sampled, which can be tuned by two types of parameters, i.e., smoothness parameters(s) and energy offsets, such that all end-states are sufficiently sampled. However, the choice of these parameters is not trivial. Replica exchange (RE) or parallel tempering is a widely applied technique to enhance sampling. By combining EDS with the RE technique, the parameter choice problem could be simplified and the challenge shifted toward an optimal distribution of the replicas in the smoothness-parameter space. The choice of a certain replica distribution can alter the sampling efficiency significantly. In this work, global round-trip time optimization (GRTO) algorithms are tested for the use in RE-EDS simulations. In addition, a local round-trip time optimization (LRTO) algorithm is proposed for systems with slowly adapting environments, where a reliable estimate for the round-trip time is challenging to obtain. The optimization algorithms were applied to RE-EDS simulations of a system of nine small-molecule inhibitors of phenylethanolamine N-methyltransferase (PNMT). The energy offsets were determined using our recently proposed parallel energy-offset (PEOE) estimation scheme. While the multistate GRTO algorithm yielded the best replica distribution for the ligands in water, the multistate LRTO algorithm was found to be the method of choice for the ligands in complex with PNMT. With this, the 36 alchemical free-energy differences between the nine ligands were calculated successfully from a single RE-EDS simulation 10 ns in length. Thus, RE-EDS presents an efficient method for the estimation of relative binding free energies.

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

An optimized surface plasmon photovoltaic structure using energy transfer between discrete nano-particles.

PubMed

Lin, Albert; Fu, Sze-Ming; Chung, Yen-Kai; Lai, Shih-Yun; Tseng, Chi-Wei

2013-01-14

Surface plasmon enhancement has been proposed as a way to achieve higher absorption for thin-film photovoltaics, where surface plasmon polariton(SPP) and localized surface plasmon (LSP) are shown to provide dense near field and far field light scattering. Here it is shown that controlled far-field light scattering can be achieved using successive coupling between surface plasmonic (SP) nano-particles. Through genetic algorithm (GA) optimization, energy transfer between discrete nano-particles (ETDNP) is identified, which enhances solar cell efficiency. The optimized energy transfer structure acts like lumped-element transmission line and can properly alter the direction of photon flow. Increased in-plane component of wavevector is thus achieved and photon path length is extended. In addition, Wood-Rayleigh anomaly, at which transmission minimum occurs, is avoided through GA optimization. Optimized energy transfer structure provides 46.95% improvement over baseline planar cell. It achieves larger angular scattering capability compared to conventional surface plasmon polariton back reflector structure and index-guided structure due to SP energy transfer through mode coupling. Via SP mediated energy transfer, an alternative way to control the light flow inside thin-film is proposed, which can be more efficient than conventional index-guided mode using total internal reflection (TIR).

Optimal Rate Schedules with Data Sharing in Energy Harvesting Communication Systems.

PubMed

Wu, Weiwei; Li, Huafan; Shan, Feng; Zhao, Yingchao

2017-12-20

Despite the abundant research on energy-efficient rate scheduling polices in energy harvesting communication systems, few works have exploited data sharing among multiple applications to further enhance the energy utilization efficiency, considering that the harvested energy from environments is limited and unstable. In this paper, to overcome the energy shortage of wireless devices at transmitting data to a platform running multiple applications/requesters, we design rate scheduling policies to respond to data requests as soon as possible by encouraging data sharing among data requests and reducing the redundancy. We formulate the problem as a transmission completion time minimization problem under constraints of dynamical data requests and energy arrivals. We develop offline and online algorithms to solve this problem. For the offline setting, we discover the relationship between two problems: the completion time minimization problem and the energy consumption minimization problem with a given completion time. We first derive the optimal algorithm for the min-energy problem and then adopt it as a building block to compute the optimal solution for the min-completion-time problem. For the online setting without future information, we develop an event-driven online algorithm to complete the transmission as soon as possible. Simulation results validate the efficiency of the proposed algorithm.

Optimal Rate Schedules with Data Sharing in Energy Harvesting Communication Systems

PubMed Central

Wu, Weiwei; Li, Huafan; Shan, Feng; Zhao, Yingchao

2017-01-01

Despite the abundant research on energy-efficient rate scheduling polices in energy harvesting communication systems, few works have exploited data sharing among multiple applications to further enhance the energy utilization efficiency, considering that the harvested energy from environments is limited and unstable. In this paper, to overcome the energy shortage of wireless devices at transmitting data to a platform running multiple applications/requesters, we design rate scheduling policies to respond to data requests as soon as possible by encouraging data sharing among data requests and reducing the redundancy. We formulate the problem as a transmission completion time minimization problem under constraints of dynamical data requests and energy arrivals. We develop offline and online algorithms to solve this problem. For the offline setting, we discover the relationship between two problems: the completion time minimization problem and the energy consumption minimization problem with a given completion time. We first derive the optimal algorithm for the min-energy problem and then adopt it as a building block to compute the optimal solution for the min-completion-time problem. For the online setting without future information, we develop an event-driven online algorithm to complete the transmission as soon as possible. Simulation results validate the efficiency of the proposed algorithm. PMID:29261135

High-energy high-efficiency Nd:YLF laser end-pump by 808 nm diode

NASA Astrophysics Data System (ADS)

Ma, Qinglei; Mo, Haiding; Zhao, Jay

2018-04-01

A model is developed to calculate the optimal pump position for end-pump configuration. The 808 nm wing pump is employed to spread the absorption inside the crystal. By the optimal laser cavity design, a high-energy high-efficiency Nd:YLF laser operating at 1053 nm is presented. In cw operation, a 13.6 W power is obtained with a slope efficiency of 51% with respect to 30 W incident pump power. The beam quality is near diffraction limited with M2 ∼ 1.02. In Q-switch operation, a pulse energy of 5 mJ is achieved with a peak power of 125 kW at 1 kHz repetition rate.

Study on key technologies of optimization of big data for thermal power plant performance

NASA Astrophysics Data System (ADS)

Mao, Mingyang; Xiao, Hong

2018-06-01

Thermal power generation accounts for 70% of China's power generation, the pollutants accounted for 40% of the same kind of emissions, thermal power efficiency optimization needs to monitor and understand the whole process of coal combustion and pollutant migration, power system performance data show explosive growth trend, The purpose is to study the integration of numerical simulation of big data technology, the development of thermal power plant efficiency data optimization platform and nitrogen oxide emission reduction system for the thermal power plant to improve efficiency, energy saving and emission reduction to provide reliable technical support. The method is big data technology represented by "multi-source heterogeneous data integration", "large data distributed storage" and "high-performance real-time and off-line computing", can greatly enhance the energy consumption capacity of thermal power plants and the level of intelligent decision-making, and then use the data mining algorithm to establish the boiler combustion mathematical model, mining power plant boiler efficiency data, combined with numerical simulation technology to find the boiler combustion and pollutant generation rules and combustion parameters of boiler combustion and pollutant generation Influence. The result is to optimize the boiler combustion parameters, which can achieve energy saving.

Mechanical power efficiency of modified turbine blades

NASA Astrophysics Data System (ADS)

Mahmud, Syahir; Sampebatu, Limbran; Kwang, Suendy Ciayadi

2017-01-01

Abstract-The problem of energy crisis has become one of the unsolved issues until today. Indonesia has a lot of non-conventional energy sources that does not utilized effectively yet. For that the available resources must utilized efficiently due to the energy crisis and the growing energy needs. Among the abundant resources of energy, one potential source of energy is hydroelectric energy. This research compares the mechanical power efficiency generated by the Darrieus turbine, Savonius turbine and the Darrieus-Savonius turbine. The comparation of the mechanical power amongst the three turbine starts from the measurement of the water flow rate, water temperature, turbine rotation and force on the shaft on each type of turbine. The comparison will show the mechanical power efficiency of each turbine to find the most efficient turbine that can work optimally. The results show that with 0.637m/s flow velocity and 44.827 Watt of water flow power, the Darrieus-Savonius turbine can generate power equal to 29.927 Watt and shaft force around by 17 N. The Darrieus-Savonius turbine provides around 66.76% efficiency betwen the three turbines; Darrieus turbine, Savonius turbine and the Darrieus-Savonius turbine. Overall, the Darrieus Savonius turbine has the ability to work optimally at the research location.

Design and analysis of electricity markets

NASA Astrophysics Data System (ADS)

Sioshansi, Ramteen Mehr

Restructured competitive electricity markets rely on designing market-based mechanisms which can efficiently coordinate the power system and minimize the exercise of market power. This dissertation is a series of essays which develop and analyze models of restructured electricity markets. Chapter 2 studies the incentive properties of a co-optimized market for energy and reserves that pays reserved generators their implied opportunity cost---which is the difference between their stated energy cost and the market-clearing price for energy. By analyzing the market as a competitive direct revelation mechanism we examine the properties of efficient equilibria and demonstrate that generators have incentives to shade their stated costs below actual costs. We further demonstrate that the expected energy payments of our mechanism is less than that in a disjoint market for energy only. Chapter 3 is an empirical validation of a supply function equilibrium (SFE) model. By comparing theoretically optimal supply functions and actual generation offers into the Texas spot balancing market, we show the SFE to fit the actual behavior of the largest generators in market. This not only serves to validate the model, but also demonstrates the extent to which firms exercise market power. Chapters 4 and 5 examine equity, incentive, and efficiency issues in the design of non-convex commitment auctions. We demonstrate that different near-optimal solutions to a central unit commitment problem which have similar-sized optimality gaps will generally yield vastly different energy prices and payoffs to individual generators. Although solving the mixed integer program to optimality will overcome such issues, we show that this relies on achieving optimality of the commitment---which may not be tractable for large-scale problems within the allotted timeframe. We then simulate and compare a competitive benchmark for a market with centralized and self commitment in order to bound the efficiency losses stemming from coordination losses (cost of anarchy) in a decentralized market.

Energy efficiency analysis and optimization for mobile platforms

NASA Astrophysics Data System (ADS)

Metri, Grace Camille

The introduction of mobile devices changed the landscape of computing. Gradually, these devices are replacing traditional personal computer (PCs) to become the devices of choice for entertainment, connectivity, and productivity. There are currently at least 45.5 million people in the United States who own a mobile device, and that number is expected to increase to 1.5 billion by 2015. Users of mobile devices expect and mandate that their mobile devices have maximized performance while consuming minimal possible power. However, due to the battery size constraints, the amount of energy stored in these devices is limited and is only growing by 5% annually. As a result, we focused in this dissertation on energy efficiency analysis and optimization for mobile platforms. We specifically developed SoftPowerMon, a tool that can power profile Android platforms in order to expose the power consumption behavior of the CPU. We also performed an extensive set of case studies in order to determine energy inefficiencies of mobile applications. Through our case studies, we were able to propose optimization techniques in order to increase the energy efficiency of mobile devices and proposed guidelines for energy-efficient application development. In addition, we developed BatteryExtender, an adaptive user-guided tool for power management of mobile devices. The tool enables users to extend battery life on demand for a specific duration until a particular task is completed. Moreover, we examined the power consumption of System-on-Chips (SoCs) and observed the impact on the energy efficiency in the event of offloading tasks from the CPU to the specialized custom engines. Based on our case studies, we were able to demonstrate that current software-based power profiling techniques for SoCs can have an error rate close to 12%, which needs to be addressed in order to be able to optimize the energy consumption of the SoC. Finally, we summarize our contributions and outline possible direction for future research in this field.

An Efficient Power Regeneration and Drive Method of an Induction Motor by Means of an Optimal Torque Derived by Variational Method

NASA Astrophysics Data System (ADS)

Inoue, Kaoru; Ogata, Kenji; Kato, Toshiji

When the motor speed is reduced by using a regenerative brake, the mechanical energy of rotation is converted to the electrical energy. When the regenerative torque is large, the corresponding current increases so that the copper loss also becomes large. On the other hand, the damping effect of rotation increases according to the time elapse when the regenerative torque is small. In order to use the limited energy effectively, an optimal regenerative torque should be discussed in order to regenerate electrical energy as much as possible. This paper proposes a design methodology of a regenerative torque for an induction motor to maximize the regenerative electric energy by means of the variational method. Similarly, an optimal torque for acceleration is derived in order to minimize the energy to drive. Finally, an efficient motor drive system with the proposed optimal torque and the power storage system stabilizing the DC link voltage will be proposed. The effectiveness of the proposed methods are illustrated by both simulations and experiments.

Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks

PubMed Central

Li, Guangxia; An, Kang; Gao, Bin; Zheng, Gan

2017-01-01

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach’s method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint. PMID:28869546

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Optimal quantum operations at zero energy cost

NASA Astrophysics Data System (ADS)

Chiribella, Giulio; Yang, Yuxiang

2017-08-01

Quantum technologies are developing powerful tools to generate and manipulate coherent superpositions of different energy levels. Envisaging a new generation of energy-efficient quantum devices, here we explore how coherence can be manipulated without exchanging energy with the surrounding environment. We start from the task of converting a coherent superposition of energy eigenstates into another. We identify the optimal energy-preserving operations, both in the deterministic and in the probabilistic scenario. We then design a recursive protocol, wherein a branching sequence of energy-preserving filters increases the probability of success while reaching maximum fidelity at each iteration. Building on the recursive protocol, we construct efficient approximations of the optimal fidelity-probability trade-off, by taking coherent superpositions of the different branches generated by probabilistic filtering. The benefits of this construction are illustrated in applications to quantum metrology, quantum cloning, coherent state amplification, and ancilla-driven computation. Finally, we extend our results to transitions where the input state is generally mixed and we apply our findings to the task of purifying quantum coherence.

On Maximizing the Throughput of Packet Transmission under Energy Constraints.

PubMed

Wu, Weiwei; Dai, Guangli; Li, Yan; Shan, Feng

2018-06-23

More and more Internet of Things (IoT) wireless devices have been providing ubiquitous services over the recent years. Since most of these devices are powered by batteries, a fundamental trade-off to be addressed is the depleted energy and the achieved data throughput in wireless data transmission. By exploiting the rate-adaptive capacities of wireless devices, most existing works on energy-efficient data transmission try to design rate-adaptive transmission policies to maximize the amount of transmitted data bits under the energy constraints of devices. Such solutions, however, cannot apply to scenarios where data packets have respective deadlines and only integrally transmitted data packets contribute. Thus, this paper introduces a notion of weighted throughput, which measures how much total value of data packets are successfully and integrally transmitted before their own deadlines. By designing efficient rate-adaptive transmission policies, this paper aims to make the best use of the energy and maximize the weighted throughput. What is more challenging but with practical significance, we consider the fading effect of wireless channels in both offline and online scenarios. In the offline scenario, we develop an optimal algorithm that computes the optimal solution in pseudo-polynomial time, which is the best possible solution as the problem undertaken is NP-hard. In the online scenario, we propose an efficient heuristic algorithm based on optimal properties derived for the optimal offline solution. Simulation results validate the efficiency of the proposed algorithm.

Solar energy receiver

DOEpatents

Schwartz, Jacob

1978-01-01

An improved long-life design for solar energy receivers provides for greatly reduced thermally induced stress and permits the utilization of less expensive heat exchanger materials while maintaining receiver efficiencies in excess of 85% without undue expenditure of energy to circulate the working fluid. In one embodiment, the flow index for the receiver is first set as close as practical to a value such that the Graetz number yields the optimal heat transfer coefficient per unit of pumping energy, in this case, 6. The convective index for the receiver is then set as closely as practical to two times the flow index so as to obtain optimal efficiency per unit mass of material.

Optimal nonimaging integrated evacuated solar collector

NASA Astrophysics Data System (ADS)

Garrison, John D.; Duff, W. S.; O'Gallagher, Joseph J.; Winston, Roland

1993-11-01

A non imaging integrated evacuated solar collector for solar thermal energy collection is discussed which has the lower portion of the tubular glass vacuum enveloped shaped and inside surface mirrored to optimally concentrate sunlight onto an absorber tube in the vacuum. This design uses vacuum to eliminate heat loss from the absorber surface by conduction and convection of air, soda lime glass for the vacuum envelope material to lower cost, optimal non imaging concentration integrated with the glass vacuum envelope to lower cost and improve solar energy collection, and a selective absorber for the absorbing surface which has high absorptance and low emittance to lower heat loss by radiation and improve energy collection efficiency. This leads to a very low heat loss collector with high optical collection efficiency, which can operate at temperatures up to the order of 250 degree(s)C with good efficiency while being lower in cost than current evacuated solar collectors. Cost estimates are presented which indicate a cost for this solar collector system which can be competitive with the cost of fossil fuel heat energy sources when the collector system is produced in sufficient volume. Non imaging concentration, which reduces cost while improving performance, and which allows efficient solar energy collection without tracking the sun, is a key element in this solar collector design.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krueger, Jens; Micikevicius, Paulius; Williams, Samuel

Reverse Time Migration (RTM) is one of the main approaches in the seismic processing industry for imaging the subsurface structure of the Earth. While RTM provides qualitative advantages over its predecessors, it has a high computational cost warranting implementation on HPC architectures. We focus on three progressively more complex kernels extracted from RTM: for isotropic (ISO), vertical transverse isotropic (VTI) and tilted transverse isotropic (TTI) media. In this work, we examine performance optimization of forward wave modeling, which describes the computational kernels used in RTM, on emerging multi- and manycore processors and introduce a novel common subexpression elimination optimization formore » TTI kernels. We compare attained performance and energy efficiency in both the single-node and distributed memory environments in order to satisfy industry’s demands for fidelity, performance, and energy efficiency. Moreover, we discuss the interplay between architecture (chip and system) and optimizations (both on-node computation) highlighting the importance of NUMA-aware approaches to MPI communication. Ultimately, our results show we can improve CPU energy efficiency by more than 10× on Magny Cours nodes while acceleration via multiple GPUs can surpass the energy-efficient Intel Sandy Bridge by as much as 3.6×.« less

Measuring energy efficiency in economics: Shadow value approach

NASA Astrophysics Data System (ADS)

Khademvatani, Asgar

For decades, academic scholars and policy makers have commonly applied a simple average measure, energy intensity, for studying energy efficiency. In contrast, we introduce a distinctive marginal measure called energy shadow value (SV) for modeling energy efficiency drawn on economic theory. This thesis demonstrates energy SV advantages, conceptually and empirically, over the average measure recognizing marginal technical energy efficiency and unveiling allocative energy efficiency (energy SV to energy price). Using a dual profit function, the study illustrates how treating energy as quasi-fixed factor called quasi-fixed approach offers modeling advantages and is appropriate in developing an explicit model for energy efficiency. We address fallacies and misleading results using average measure and demonstrate energy SV advantage in inter- and intra-country energy efficiency comparison. Energy efficiency dynamics and determination of efficient allocation of energy use are shown through factors impacting energy SV: capital, technology, and environmental obligations. To validate the energy SV, we applied a dual restricted cost model using KLEM dataset for the 35 US sectors stretching from 1958 to 2000 and selected a sample of the four sectors. Following the empirical results, predicted wedges between energy price and the SV growth indicate a misallocation of energy use in stone, clay and glass (SCG) and communications (Com) sectors with more evidence in the SCG compared to the Com sector, showing overshoot in energy use relative to optimal paths and cost increases from sub-optimal energy use. The results show that energy productivity is a measure of technical efficiency and is void of information on the economic efficiency of energy use. Decomposing energy SV reveals that energy, capital and technology played key roles in energy SV increases helping to consider and analyze policy implications of energy efficiency improvement. Applying the marginal measure, we also contributed to energy efficiency convergence analysis employing the delta-convergence and unconditional & conditional beta-convergence concepts, investigating economic energy efficiency differences across the four US sectors using panel data models. The results show that, in terms of technical and allocative energy efficiency, the energy-intensive sectors, SCG and textile mill products, tend to catch the energy extensive sectors, the Com and furniture & fixtures, being conditional on sector-specific characteristics. Conditional convergence results indicate that technology, capital and energy are crucial factors in determining energy efficiency differences across the US sectors, implying that environmental or energy policies, and technological changes should be industry specific across the US sectors. The main finding is that the marginal value measure conveys information on both technical and allocative energy efficiency and accounts for all costs and benefits of energy consumption including environmental and externality costs.

A High-Efficiency Wind Energy Harvester for Autonomous Embedded Systems

PubMed Central

Brunelli, Davide

2016-01-01

Energy harvesting is currently a hot research topic, mainly as a consequence of the increasing attractiveness of computing and sensing solutions based on small, low-power distributed embedded systems. Harvesting may enable systems to operate in a deploy-and-forget mode, particularly when power grid is absent and the use of rechargeable batteries is unattractive due to their limited lifetime and maintenance requirements. This paper focuses on wind flow as an energy source feasible to meet the energy needs of a small autonomous embedded system. In particular the contribution is on the electrical converter and system integration. We characterize the micro-wind turbine, we define a detailed model of its behaviour, and then we focused on a highly efficient circuit to convert wind energy into electrical energy. The optimized design features an overall volume smaller than 64 cm3. The core of the harvester is a high efficiency buck-boost converter which performs an optimal power point tracking. Experimental results show that the wind generator boosts efficiency over a wide range of operating conditions. PMID:26959018

A High-Efficiency Wind Energy Harvester for Autonomous Embedded Systems.

PubMed

Brunelli, Davide

2016-03-04

Energy harvesting is currently a hot research topic, mainly as a consequence of the increasing attractiveness of computing and sensing solutions based on small, low-power distributed embedded systems. Harvesting may enable systems to operate in a deploy-and-forget mode, particularly when power grid is absent and the use of rechargeable batteries is unattractive due to their limited lifetime and maintenance requirements. This paper focuses on wind flow as an energy source feasible to meet the energy needs of a small autonomous embedded system. In particular the contribution is on the electrical converter and system integration. We characterize the micro-wind turbine, we define a detailed model of its behaviour, and then we focused on a highly efficient circuit to convert wind energy into electrical energy. The optimized design features an overall volume smaller than 64 cm³. The core of the harvester is a high efficiency buck-boost converter which performs an optimal power point tracking. Experimental results show that the wind generator boosts efficiency over a wide range of operating conditions.

Stochastic Control of Energy Efficient Buildings: A Semidefinite Programming Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Xiao; Dong, Jin; Djouadi, Seddik M

2015-01-01

The key goal in energy efficient buildings is to reduce energy consumption of Heating, Ventilation, and Air- Conditioning (HVAC) systems while maintaining a comfortable temperature and humidity in the building. This paper proposes a novel stochastic control approach for achieving joint performance and power control of HVAC. We employ a constrained Stochastic Linear Quadratic Control (cSLQC) by minimizing a quadratic cost function with a disturbance assumed to be Gaussian. The problem is formulated to minimize the expected cost subject to a linear constraint and a probabilistic constraint. By using cSLQC, the problem is reduced to a semidefinite optimization problem, wheremore » the optimal control can be computed efficiently by Semidefinite programming (SDP). Simulation results are provided to demonstrate the effectiveness and power efficiency by utilizing the proposed control approach.« less

An Energy Integrated Dispatching Strategy of Multi- energy Based on Energy Internet

NASA Astrophysics Data System (ADS)

Jin, Weixia; Han, Jun

2018-01-01

Energy internet is a new way of energy use. Energy internet achieves energy efficiency and low cost by scheduling a variety of different forms of energy. Particle Swarm Optimization (PSO) is an advanced algorithm with few parameters, high computational precision and fast convergence speed. By improving the parameters ω, c1 and c2, PSO can improve the convergence speed and calculation accuracy. The objective of optimizing model is lowest cost of fuel, which can meet the load of electricity, heat and cold after all the renewable energy is received. Due to the different energy structure and price in different regions, the optimization strategy needs to be determined according to the algorithm and model.

Optimal pitching axis location of flapping wings for efficient hovering flight.

PubMed

Wang, Q; Goosen, J F L; van Keulen, F

2017-09-01

Flapping wings can pitch passively about their pitching axes due to their flexibility, inertia, and aerodynamic loads. A shift in the pitching axis location can dynamically alter the aerodynamic loads, which in turn changes the passive pitching motion and the flight efficiency. Therefore, it is of great interest to investigate the optimal pitching axis for flapping wings to maximize the power efficiency during hovering flight. In this study, flapping wings are modeled as rigid plates with non-uniform mass distribution. The wing flexibility is represented by a linearly torsional spring at the wing root. A predictive quasi-steady aerodynamic model is used to evaluate the lift generated by such wings. Two extreme power consumption scenarios are modeled for hovering flight, i.e. the power consumed by a drive system with and without the capacity of kinetic energy recovery. For wings with different shapes, the optimal pitching axis location is found such that the cycle-averaged power consumption during hovering flight is minimized. Optimization results show that the optimal pitching axis is located between the leading edge and the mid-chord line, which shows close resemblance to insect wings. An optimal pitching axis can save up to 33% of power during hovering flight when compared to traditional wings used by most of flapping wing micro air vehicles (FWMAVs). Traditional wings typically use the straight leading edge as the pitching axis. With the optimized pitching axis, flapping wings show higher pitching amplitudes and start the pitching reversals in advance of the sweeping reversals. These phenomena lead to higher lift-to-drag ratios and, thus, explain the lower power consumption. In addition, the optimized pitching axis provides the drive system higher potential to recycle energy during the deceleration phases as compared to their counterparts. This observation underlines the particular importance of the wing pitching axis location for energy-efficient FWMAVs when using kinetic energy recovery drive systems.

Energy-efficient growth of phage Q Beta in Escherichia coli.

PubMed

Kim, Hwijin; Yin, John

2004-10-20

The role of natural selection in the optimal design of organisms is controversial. Optimal forms, functions, or behaviors of organisms have long been claimed without knowledge of how genotype contributes to phenotype, delineation of design constraints, or reference to alternative designs. Moreover, arguments for optimal designs have been often based on models that were difficult, if not impossible, to test. Here, we begin to address these issues by developing and probing a kinetic model for the intracellular growth of bacteriophage Q beta in Escherichia coli. The model accounts for the energetic costs of all template-dependent polymerization reactions, in ATP equivalents, including RNA-dependent RNA elongation by the phage replicase and synthesis of all phage proteins by the translation machinery of the E. coli host cell. We found that translation dominated phage growth, requiring 85% of the total energy expenditure. Only 10% of the total energy was applied to activities other than the direct synthesis of progeny phage components, reflecting primarily the cost of making the negative-strand RNA template that is needed for replication of phage genomic RNA. Further, we defined an energy efficiency of phage growth and showed its direct relationship to the yield of phage progeny. Finally, we performed a sensitivity analysis and found that the growth of wild-type phage was optimized for progeny yield or energy efficiency, suggesting that phage Q beta has evolved to optimally utilize the finite resources of its host cells.

Disorder-assisted quantum transport in suboptimal decoherence regimes

PubMed Central

Novo, Leonardo; Mohseni, Masoud; Omar, Yasser

2016-01-01

We investigate quantum transport in binary tree structures and in hypercubes for the disordered Frenkel-exciton Hamiltonian under pure dephasing noise. We compute the energy transport efficiency as a function of disorder and dephasing rates. We demonstrate that dephasing improves transport efficiency not only in the disordered case, but also in the ordered one. The maximal transport efficiency is obtained when the dephasing timescale matches the hopping timescale, which represent new examples of the Goldilocks principle at the quantum scale. Remarkably, we find that in weak dephasing regimes, away from optimal levels of environmental fluctuations, the average effect of increasing disorder is to improve the transport efficiency until an optimal value for disorder is reached. Our results suggest that rational design of the site energies statistical distributions could lead to better performances in transport systems at nanoscale when their natural environments are far from the optimal dephasing regime. PMID:26726133

A Method to Determine Supply Voltage of Permanent Magnet Motor at Optimal Design Stage

NASA Astrophysics Data System (ADS)

Matustomo, Shinya; Noguchi, So; Yamashita, Hideo; Tanimoto, Shigeya

The permanent magnet motors (PM motors) are widely used in electrical machinery, such as air conditioner, refrigerator and so on. In recent years, from the point of view of energy saving, it is necessary to improve the efficiency of PM motor by optimization. However, in the efficiency optimization of PM motor, many design variables and many restrictions are required. In this paper, the efficiency optimization of PM motor with many design variables was performed by using the voltage driven finite element analysis with the rotating simulation of the motor and the genetic algorithm.

On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

PubMed

Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

2015-08-11

Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

Optimal satisfaction degree in energy harvesting cognitive radio networks

NASA Astrophysics Data System (ADS)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Andy Walker | NREL

Science.gov Websites

efficiency and renewable energy projects. His patent on the Renewable Energy Optimization (REO) method of distribution function for time-series simulation Analytical and numerical optimization Project delivery with System Operations and Maintenance: 2nd Edition, 2016, NREL/Sandia/Sunspec Alliance SuNLaMP PV O&M

Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramachandran, Thiagarajan; Kundu, Soumya; Chen, Yan

This paper develops and utilizes an optimization based framework to investigate the maximal energy efficiency potentially attainable by HVAC system operation in a non-predictive context. Performance is evaluated relative to the existing state of the art set point reset strategies. The expected efficiency increase driven by operation constraints relaxations is evaluated.

Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramachandran, Thiagarajan; Kundu, Soumya; Chen, Yan

This paper develops and utilizes an optimization based framework to investigate the maximal energy efficiency potentially attainable by HVAC system operation in a non-predictive context. Performance is evaluated relative to the existing state of the art set-point reset strategies. The expected efficiency increase driven by operation constraints relaxations is evaluated.

Zero Energy Schools: Designing for the Future: Zero Energy Ready K-12 Schools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Torcellini, Paul A

Designing, building, and operating zero energy ready K-12 schools provides benefits for districts, students, and teachers. Optimizing energy efficiency is important in any building, but it's particularly important in K-12 schools. Many U.S. school districts struggle for funding, and improving a school building's energy efficiency can free up operational funds that may then be available for educational and other purposes.

Negative space charge effects in photon-enhanced thermionic emission solar converters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Segev, G.; Weisman, D.; Rosenwaks, Y.

2015-07-06

In thermionic energy converters, electrons in the gap between electrodes form a negative space charge and inhibit the emission of additional electrons, causing a significant reduction in conversion efficiency. However, in Photon Enhanced Thermionic Emission (PETE) solar energy converters, electrons that are reflected by the electric field in the gap return to the cathode with energy above the conduction band minimum. These electrons first occupy the conduction band from which they can be reemitted. This form of electron recycling makes PETE converters less susceptible to negative space charge loss. While the negative space charge effect was studied extensively in thermionicmore » converters, modeling its effect in PETE converters does not account for important issues such as this form of electron recycling, nor the cathode thermal energy balance. Here, we investigate the space charge effect in PETE solar converters accounting for electron recycling, with full coupling of the cathode and gap models, and addressing conservation of both electric and thermal energy. The analysis shows that the negative space charge loss is lower than previously reported, allowing somewhat larger gaps compared to previous predictions. For a converter with a specific gap, there is an optimal solar flux concentration. The optimal solar flux concentration, the cathode temperature, and the efficiency all increase with smaller gaps. For example, for a gap of 3 μm the maximum efficiency is 38% and the optimal flux concentration is 628, while for a gap of 5 μm the maximum efficiency is 31% and optimal flux concentration is 163.« less

Effective Energy Simulation and Optimal Design of Side-lit Buildings with Venetian Blinds

NASA Astrophysics Data System (ADS)

Cheng, Tian

Venetian blinds are popularly used in buildings to control the amount of incoming daylight for improving visual comfort and reducing heat gains in air-conditioning systems. Studies have shown that the proper design and operation of window systems could result in significant energy savings in both lighting and cooling. However, there is no convenient computer tool that allows effective and efficient optimization of the envelope of side-lit buildings with blinds now. Three computer tools, Adeline, DOE2 and EnergyPlus widely used for the above-mentioned purpose have been experimentally examined in this study. Results indicate that the two former tools give unacceptable accuracy due to unrealistic assumptions adopted while the last one may generate large errors in certain conditions. Moreover, current computer tools have to conduct hourly energy simulations, which are not necessary for life-cycle energy analysis and optimal design, to provide annual cooling loads. This is not computationally efficient, particularly not suitable for optimal designing a building at initial stage because the impacts of many design variations and optional features have to be evaluated. A methodology is therefore developed for efficient and effective thermal and daylighting simulations and optimal design of buildings with blinds. Based on geometric optics and radiosity method, a mathematical model is developed to reasonably simulate the daylighting behaviors of venetian blinds. Indoor illuminance at any reference point can be directly and efficiently computed. They have been validated with both experiments and simulations with Radiance. Validation results show that indoor illuminances computed by the new models agree well with the measured data, and the accuracy provided by them is equivalent to that of Radiance. The computational efficiency of the new models is much higher than that of Radiance as well as EnergyPlus. Two new methods are developed for the thermal simulation of buildings. A fast Fourier transform (FFT) method is presented to avoid the root-searching process in the inverse Laplace transform of multilayered walls. Generalized explicit FFT formulae for calculating the discrete Fourier transform (DFT) are developed for the first time. They can largely facilitate the implementation of FFT. The new method also provides a basis for generating the symbolic response factors. Validation simulations show that it can generate the response factors as accurate as the analytical solutions. The second method is for direct estimation of annual or seasonal cooling loads without the need for tedious hourly energy simulations. It is validated by hourly simulation results with DOE2. Then symbolic long-term cooling load can be created by combining the two methods with thermal network analysis. The symbolic long-term cooling load can keep the design parameters of interest as symbols, which is particularly useful for the optimal design and sensitivity analysis. The methodology is applied to an office building in Hong Kong for the optimal design of building envelope. Design variables such as window-to-wall ratio, building orientation, and glazing optical and thermal properties are included in the study. Results show that the selected design values could significantly impact the energy performance of windows, and the optimal design of side-lit buildings could greatly enhance energy savings. The application example also demonstrates that the developed methodology significantly facilitates the optimal building design and sensitivity analysis, and leads to high computational efficiency.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

Model Based Optimization of Integrated Low Voltage DC-DC Converter for Energy Harvesting Applications

NASA Astrophysics Data System (ADS)

Jayaweera, H. M. P. C.; Muhtaroğlu, Ali

2016-11-01

A novel model based methodology is presented to determine optimal device parameters for the fully integrated ultra low voltage DC-DC converter for energy harvesting applications. The proposed model feasibly contributes to determine the maximum efficient number of charge pump stages to fulfill the voltage requirement of the energy harvester application. The proposed DC-DC converter based power consumption model enables the analytical derivation of the charge pump efficiency when utilized simultaneously with the known LC tank oscillator behavior under resonant conditions, and voltage step up characteristics of the cross-coupled charge pump topology. The verification of the model has been done using a circuit simulator. The optimized system through the established model achieves more than 40% maximum efficiency yielding 0.45 V output with single stage, 0.75 V output with two stages, and 0.9 V with three stages for 2.5 kΩ, 3.5 kΩ and 5 kΩ loads respectively using 0.2 V input.

A Review of Industrial Heat Exchange Optimization

NASA Astrophysics Data System (ADS)

Yao, Junjie

2018-01-01

Heat exchanger is an energy exchange equipment, it transfers the heat from a working medium to another working medium, which has been wildly used in petrochemical industry, HVAC refrigeration, aerospace and so many other fields. The optimal design and efficient operation of the heat exchanger and heat transfer network are of great significance to the process industry to realize energy conservation, production cost reduction and energy consumption reduction. In this paper, the optimization of heat exchanger, optimal algorithm and heat exchanger optimization with different objective functions are discussed. Then, optimization of the heat exchanger and the heat exchanger network considering different conditions are compared and analysed. Finally, all the problems discussed are summarized and foresights are proposed.

The Next Breakthrough for Organic Photovoltaics?

PubMed

Jackson, Nicholas E; Savoie, Brett M; Marks, Tobin J; Chen, Lin X; Ratner, Mark A

2015-01-02

While the intense focus on energy level tuning in organic photovoltaic materials has afforded large gains in device performance, we argue here that strategies based on microstructural/morphological control are at least as promising in any rational design strategy. In this work, a meta-analysis of ∼150 bulk heterojunction devices fabricated with different materials combinations is performed and reveals strong correlations between power conversion efficiency and morphology-dominated properties (short-circuit current, fill factor) and surprisingly weak correlations between efficiency and energy level positioning (open-circuit voltage, enthalpic offset at the interface, optical gap). While energy level positioning should in principle provide the theoretical maximum efficiency, the optimization landscape that must be navigated to reach this maximum is unforgiving. Thus, research aimed at developing understanding-based strategies for more efficient optimization of an active layer microstructure and morphology are likely to be at least as fruitful.

Efficiency of broadband terahertz rectennas based on self-switching nanodiodes

NASA Astrophysics Data System (ADS)

Briones, Edgar; Cortes-Mestizo, Irving E.; Briones, Joel; Droopad, Ravindranath; Espinosa-Vega, Leticia I.; Vilchis, Heber; Mendez-Garcia, Victor H.

2017-04-01

The authors investigate the efficiency of a series of broadband rectennas designed to harvest the free-propagating electromagnetic energy at terahertz frequencies. We analyze by simulations the case of self-complementary square- and Archimedean-spiral antennas coupled to L-shaped self-switching diodes (L-SSDs). First, the geometry (i.e., the width and length of the channel) of the L-SSD was optimized to obtain a remarkable diode-like I-V response. Subsequently, the optimized L-SSD geometry was coupled to both types of spiral antennas and their characteristic impedance was studied. Finally, the energy conversion efficiency was evaluated for both rectenna architectures.

Industrial Energy Efficiency Practices in Indonesia: Lesson Learned from Astra Green Energy (AGen) Award

NASA Astrophysics Data System (ADS)

Telaga, A. S.; Hartanto, I. D.

2017-03-01

Many countries have used award system to promote energy efficiency practices in industry. The award system has been found to have significant impact to increase energy conservation and sustainability adoption in companies. Astra International (AI) as a holding company of more than 200 companies also organised Astra green energy (AGen) award to all affiliated companies (AFFCO) in Astra group. The event has been used to share energy efficiency best practices among AFFCO in Astra group. AFFCOs of Astra International are among the biggest and the leader in their industrial sectors Therefore, analyses from AFFO’s energy efficiency case studies represents current practices in Indonesia industrial sectors. Analyses are divided into industry, building, and renewable energy. The results from analyses found that AFFCOs already aware of energy conservation and have implemented projects to promote energy efficiency. However, the AFFCOs do not optimally use monitoring data for energy reduction.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

Smart City Energy Interconnection Technology Framework Preliminary Research

NASA Astrophysics Data System (ADS)

Zheng, Guotai; Zhao, Baoguo; Zhao, Xin; Li, Hao; Huo, Xianxu; Li, Wen; Xia, Yu

2018-01-01

to improve urban energy efficiency, improve the absorptive ratio of new energy resources and renewable energy sources, and reduce environmental pollution and other energy supply and consumption technology framework matched with future energy restriction conditions and applied technology level are required to be studied. Relative to traditional energy supply system, advanced information technology-based “Energy Internet” technical framework may give play to energy integrated application and load side interactive technology advantages, as a whole optimize energy supply and consumption and improve the overall utilization efficiency of energy.

Anaerobic digestion of food waste: A review focusing on process stability.

PubMed

Li, Lei; Peng, Xuya; Wang, Xiaoming; Wu, Di

2018-01-01

Food waste (FW) is rich in biomass energy, and increasing numbers of national programs are being established to recover energy from FW using anaerobic digestion (AD). However process instability is a common operational issue for AD of FW. Process monitoring and control as well as microbial management can be used to control instability and increase the energy conversion efficiency of anaerobic digesters. Here, we review research progress related to these methods and identify existing limitations to efficient AD; recommendations for future research are also discussed. Process monitoring and control are suitable for evaluating the current operational status of digesters, whereas microbial management can facilitate early diagnosis and process optimization. Optimizing and combining these two methods are necessary to improve AD efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficiency of energy conversion in model biological pumps. Optimization by linear nonequilibrium thermodynamic relations.

PubMed

Stucki, J W; Compiani, M; Caplan, S R

1983-09-01

Experimental investigations showed linear relations between flows and forces in some biological energy converters operating far from equilibrium. This observation cannot be understood on the basis of conventional nonequilibrium thermodynamics. Therefore, the efficiencies of a linear and a nonlinear mode of operation of an energy converter (a hypothetical redox-driven H+ pump) were compared. This comparison revealed that at physiological values of the forces and degrees of coupling (1) the force ratio permitting optimal efficiency was much higher in the linear than in the nonlinear mode and (2) the linear mode of operation was at least 10(6)-times more efficient that the nonlinear one. These observations suggest that the experimentally observed linear relations between flows and forces, particularly in the case of oxidative phosphorylation, may be due to a feedback regulation maintaining linear thermodynamic relations far from equilibrium. This regulation may have come about as the consequence of an evolutionary drive towards higher efficiency.

REopt: A Platform for Energy System Integration and Optimization: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simpkins, T.; Cutler, D.; Anderson, K.

2014-08-01

REopt is NREL's energy planning platform offering concurrent, multi-technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally-sized mix of conventional and renewable energy, andmore » energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.« less

Optimizing indoor illumination quality and energy efficiency using a spectrally tunable lighting system to augment natural daylight.

PubMed

Hertog, W; Llenas, A; Carreras, J

2015-11-30

This article demonstrates the benefits of complementing a daylight-lit environment with a spectrally tunable illumination system. The spectral components of daylight present in the room are measured by a low-cost miniature spectrophotometer and processed through a number of optimization algorithms, carefully trading color fidelity for energy efficiency. Spectrally-tunable luminaires provide only those wavelengths that ensure that either the final illumination spectrum inside the room is kept constant or carefully follows the dynamic spectral pattern of natural daylight. Analyzing the measured data proves that such a hybrid illumination system brings both unprecendented illumination quality and significant energy savings.

Software augmented buildings: Exploiting existing infrastructure to improve energy efficiency and comfort in commercial buildings

NASA Astrophysics Data System (ADS)

Balaji, Bharathan

Commercial buildings consume 19% of energy in the US as of 2010, and traditionally, their energy use has been optimized through improved equipment efficiency and retrofits. Beyond improved hardware and infrastructure, there exists a tremendous potential in reducing energy use through better monitoring and operation. We present several applications that we developed and deployed to support our thesis that building energy use can be reduced through sensing, monitoring and optimization software that modulates use of building subsystems including HVAC. We focus on HVAC systems as these constitute 48-55% of building energy use. Specifically, in case of sensing, we describe an energy apportionment system that enables us to estimate real-time zonal HVAC power consumption by analyzing existing sensor information. With this energy breakdown, we can measure effectiveness of optimization solutions and identify inefficiencies. Central to energy efficiency improvement is determination of human occupancy in buildings. But this information is often unavailable or expensive to obtain using wide scale sensor deployment. We present our system that infers room level occupancy inexpensively by leveraging existing WiFi infrastructure. Occupancy information can be used not only to directly control HVAC but also to infer state of the building for predictive control. Building energy use is strongly influenced by human behaviors, and timely feedback mechanisms can encourage energy saving behavior. Occupants interact with HVAC using thermostats which has shown to be inadequate for thermal comfort. Building managers are responsible for incorporating energy efficiency measures, but our interviews reveal that they struggle to maintain efficiency due to lack of analytical tools and contextual information. We present our software services that provide energy feedback to occupants and building managers, improves comfort with personalized control and identifies energy wasting faults. For wide scale deployment of such energy saving software, they need to be portable across multiple buildings. However, buildings consist of heterogeneous equipment and use inconsistent naming schema, and developers need extensive domain knowledge to map sensor information to a standard format. To enable portability, we present an active learning algorithm that automates mapping building sensor metadata to a standard naming schema.

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning

PubMed Central

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach. PMID:24616695

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning.

PubMed

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach.

Improved Planning and Programming for Energy Efficient New Army Facilities

DTIC Science & Technology

1988-10-01

setpoints to occupant comfort must be considered carefully. Cutting off the HVAC system to the bedrooms during the day produced only small savings...functions of a building and minimizing the energy usage through optimization . It includes thermostats, time switches, programmable con- trollers...microprocessor systems, computers, and sensing devices that are linked with control and power components to manage energy use. This system optimizes load

Universal optimal working cycles of molecular motors.

PubMed

Efremov, Artem; Wang, Zhisong

2011-04-07

Molecular motors capable of directional track-walking or rotation are abundant in living cells, and inspire the emerging field of artificial nanomotors. Some biomotors can convert 90% of free energy from chemical fuels into usable mechanical work, and the same motors still maintain a speed sufficient for cellular functions. This study exposed a new regime of universal optimization that amounts to a thermodynamically best working regime for molecular motors but is unfamiliar in macroscopic engines. For the ideal case of zero energy dissipation, the universally optimized working cycle for molecular motors is infinitely slow like Carnot cycle for heat engines. But when a small amount of energy dissipation reduces energy efficiency linearly from 100%, the speed is recovered exponentially due to Boltzmann's law. Experimental data on a major biomotor (kinesin) suggest that the regime of universal optimization has been largely approached in living cells, underpinning the extreme efficiency-speed trade-off in biomotors. The universal optimization and its practical approachability are unique thermodynamic advantages of molecular systems over macroscopic engines in facilitating motor functions. The findings have important implications for the natural evolution of biomotors as well as the development of artificial counterparts.

Directed Diffusion Modelling for Tesso Nilo National Parks Case Study

NASA Astrophysics Data System (ADS)

Yasri, Indra; Safrianti, Ery

2018-01-01

— Directed Diffusion (DD has ability to achieve energy efficiency in Wireless Sensor Network (WSN). This paper proposes Directed Diffusion (DD) modelling for Tesso Nilo National Parks (TNNP) case study. There are 4 stages of scenarios involved in this modelling. It’s started by appointing of sampling area through GPS coordinate. The sampling area is determined by optimization processes from 500m x 500m up to 1000m x 1000m with 100m increment in between. The next stage is sensor node placement. Sensor node is distributed in sampling area with three different quantities i.e. 20 nodes, 30 nodes and 40 nodes. One of those quantities is choose as an optimized sensor node placement. The third stage is to implement all scenarios in stages 1 and stages 2 on DD modelling. In the last stage, the evaluation process to achieve most energy efficient in the combination of optimized sampling area and optimized sensor node placement on Direct Diffusion (DD) routing protocol. The result shows combination between sampling area 500m x 500m and 20 nodes able to achieve energy efficient to support a forest preventive fire system at Tesso Nilo National Parks.

Co-Optimization of Fuels & Engines for Tomorrow's Energy-Efficient Vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-03-01

A new U.S. Department of Energy (DOE) initiative is accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) is designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, nine national laboratories, and numerous industry and academic partners to more rapidly identify commercially viable solutions. This multi-year project will provide industry with the scientific underpinnings required tomore » move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions.« less

Steam gasification of acid-hydrolysis biomass CAHR for clean syngas production.

PubMed

Chen, Guanyi; Yao, Jingang; Yang, Huijun; Yan, Beibei; Chen, Hong

2015-03-01

Main characteristics of gaseous product from steam gasification of acid-hydrolysis biomass CAHR have been investigated experimentally. The comparison in terms of evolution of syngas flow rate, syngas quality and apparent thermal efficiency was made between steam gasification and pyrolysis in the lab-scale apparatus. The aim of this study was to determine the effects of temperature and steam to CAHR ratio on gas quality, syngas yield and energy conversion. The results showed that syngas and energy yield were better with gasification compared to pyrolysis under identical thermal conditions. Both high gasification temperature and introduction of proper steam led to higher gas quality, higher syngas yield and higher energy conversion efficiency. However, excessive steam reduced hydrogen yield and energy conversion efficiency. The optimal value of S/B was found to be 3.3. The maximum value of energy ratio was 0.855 at 800°C with the optimal S/B value. Copyright © 2014 Elsevier Ltd. All rights reserved.

An extended continuum model considering optimal velocity change with memory and numerical tests

NASA Astrophysics Data System (ADS)

Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

2018-01-01

In this paper, an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory. The new model's stability condition and KdV-Burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis, respectively. Numerical simulation is carried out to study the extended continuum model, which explores how optimal velocity changes with memory affected velocity, density and energy consumption. Numerical results show that when considering the effects of optimal velocity changes with memory, the traffic jams can be suppressed efficiently. Both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently. Furthermore, numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information, which increases the stability of traffic flow on road, and so it improve the traffic flow stability and minimize cars' energy consumptions.

Three Essays on Macroeconomics

NASA Astrophysics Data System (ADS)

Doda, Lider Baran

This dissertation consists of three independent essays in macroeconomics. The first essay studies the transition to a low carbon economy using an extension of the neoclassical growth model featuring endogenous energy efficiency, exhaustible energy and explicit climate-economy interaction. I derive the properties of the laissez faire equilibrium and compare them to the optimal allocations of a social planner who internalizes the climate change externality. Three main results emerge. First, the exhaustibility of energy generates strong market based incentives to improve energy efficiency and reduce CO 2 emissions without any government intervention. Second, the market and optimal allocations are substantially different suggesting a role for the government. Third, high and persistent taxes are required to implement the optimal allocations as a competitive equilibrium with taxes. The second essay focuses on coal fired power plants (CFPP) - one of the largest sources of CO2 emissions globally - and their generation efficiency using a macroeconomic model with an embedded CFPP sector. A key feature of the model is the endogenous choice of production technologies which differ in their energy efficiency. After establishing four empirical facts about the CFPP sector, I analyze the long run quantitative effects of energy taxes. Using the calibrated model, I find that sector-specific coal taxes have large effects on generation efficiency by inducing the use of more efficient technologies. Moreover, such taxes achieve large CO2 emissions reductions with relatively small effects on consumption and output. The final essay studies the procyclicality of fiscal policy in developing countries, which is a well-documented empirical observation seemingly at odds with Neoclassical and Keynesian policy prescriptions. I examine this issue by solving the optimal fiscal policy problem of a small open economy government when the interest rates on external debt are endogenous. Given an incomplete asset market, endogeneity is achieved by removing the government's ability to commit to repaying its external obligations. When calibrated to Argentina, the model generates procyclical government spending and countercyclical labor income tax rates. Simultaneously, the model's implications for key business cycle moments align well with the data.

Hybrid Pressure Retarded Osmosis-Membrane Distillation System for Power Generation from Low-Grade Heat: Thermodynamic Analysis and Energy Efficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, SH; Yip, NY; Cath, TY

2014-05-06

We present a novel hybrid membrane system that operates as a heat engine capable of utilizing low-grade thermal energy, which is not readily recoverable with existing technologies. The closed-loop system combines membrane distillation (MD), which generates concentrated and pure water streams by thermal separation, and pressure retarded osmosis (PRO), which converts the energy of mixing to electricity by a hydro-turbine. The PRO-MD system was modeled by coupling the mass and energy flows between the thermal separation (MD) and power generation (PRO) stages for heat source temperatures ranging from 40 to 80 degrees C and working concentrations of 1.0, 2.0, andmore » 4.0 mol/kg NaCl. The factors controlling the energy efficiency of the heat engine were evaluated for both limited and unlimited mass and heat transfer kinetics in the thermal separation stage. In both cases, the relative flow rate between the MD permeate (distillate) and feed streams is identified as an important operation parameter. There is an optimal relative flow rate that maximizes the overall energy efficiency of the PRO-MD system for given working temperatures and concentration. In the case of unlimited mass and heat transfer kinetics, the energy efficiency of the system can be analytically determined based on thermodynamics. Our assessment indicates that the hybrid PRO-MD system can theoretically achieve an energy efficiency of 9.8% (81.6% of the Carnot efficiency) with hot and cold working temperatures of 60 and 20 degrees C, respectively, and a working solution of 1.0 M NaCl. When mass and heat transfer kinetics are limited, conditions that more closely represent actual operations, the practical energy efficiency will be lower than the theoretically achievable efficiency. In such practical operations, utilizing a higher working concentration will yield greater energy efficiency. Overall, our study demonstrates the theoretical viability of the PRO-MD system and identifies the key factors for performance optimization.« less

Hybrid pressure retarded osmosis-membrane distillation system for power generation from low-grade heat: thermodynamic analysis and energy efficiency.

PubMed

Lin, Shihong; Yip, Ngai Yin; Cath, Tzahi Y; Osuji, Chinedum O; Elimelech, Menachem

2014-05-06

We present a novel hybrid membrane system that operates as a heat engine capable of utilizing low-grade thermal energy, which is not readily recoverable with existing technologies. The closed-loop system combines membrane distillation (MD), which generates concentrated and pure water streams by thermal separation, and pressure retarded osmosis (PRO), which converts the energy of mixing to electricity by a hydro-turbine. The PRO-MD system was modeled by coupling the mass and energy flows between the thermal separation (MD) and power generation (PRO) stages for heat source temperatures ranging from 40 to 80 °C and working concentrations of 1.0, 2.0, and 4.0 mol/kg NaCl. The factors controlling the energy efficiency of the heat engine were evaluated for both limited and unlimited mass and heat transfer kinetics in the thermal separation stage. In both cases, the relative flow rate between the MD permeate (distillate) and feed streams is identified as an important operation parameter. There is an optimal relative flow rate that maximizes the overall energy efficiency of the PRO-MD system for given working temperatures and concentration. In the case of unlimited mass and heat transfer kinetics, the energy efficiency of the system can be analytically determined based on thermodynamics. Our assessment indicates that the hybrid PRO-MD system can theoretically achieve an energy efficiency of 9.8% (81.6% of the Carnot efficiency) with hot and cold working temperatures of 60 and 20 °C, respectively, and a working solution of 1.0 M NaCl. When mass and heat transfer kinetics are limited, conditions that more closely represent actual operations, the practical energy efficiency will be lower than the theoretically achievable efficiency. In such practical operations, utilizing a higher working concentration will yield greater energy efficiency. Overall, our study demonstrates the theoretical viability of the PRO-MD system and identifies the key factors for performance optimization.

Optimized efficiency of all-electric ships by dc hybrid power systems

NASA Astrophysics Data System (ADS)

Zahedi, Bijan; Norum, Lars E.; Ludvigsen, Kristine B.

2014-06-01

Hybrid power systems with dc distribution are being considered for commercial marine vessels to comply with new stringent environmental regulations, and to achieve higher fuel economy. In this paper, detailed efficiency analysis of a shipboard dc hybrid power system is carried out. An optimization algorithm is proposed to minimize fuel consumption under various loading conditions. The studied system includes diesel engines, synchronous generator-rectifier units, a full-bridge bidirectional converter, and a Li-Ion battery bank as energy storage. In order to evaluate potential fuel saving provided by such a system, an online optimization strategy for fuel consumption is implemented. An Offshore Support Vessel (OSV) is simulated over different operating modes using the online control strategy. The resulted consumed fuel in the simulation is compared to that of a conventional ac power system, and also a dc power system without energy storage. The results show that while the dc system without energy storage provides noticeable fuel saving compared to the conventional ac system, optimal utilization of the energy storage in the dc system results in twice as much fuel saving.

Optimality principle for the coupled chemical reactions of ATP synthesis and its molecular interpretation

NASA Astrophysics Data System (ADS)

Nath, Sunil

2018-05-01

Metabolic energy obtained from the coupled chemical reactions of oxidative phosphorylation (OX PHOS) is harnessed in the form of ATP by cells. We experimentally measured thermodynamic forces and fluxes during ATP synthesis, and calculated the thermodynamic efficiency, η and the rate of free energy dissipation, Φ. We show that the OX PHOS system is tuned such that the coupled nonequilibrium processes operate at optimal η. This state does not coincide with the state of minimum Φ but is compatible with maximum Φ under the imposed constraints. Conditions that must hold for species concentration in order to satisfy the principle of optimal efficiency are derived analytically and a molecular explanation based on Nath's torsional mechanism of energy transduction and ATP synthesis is suggested. Differences of the proposed principle with Prigogine's principle are discussed.

An optimization method of VON mapping for energy efficiency and routing in elastic optical networks

NASA Astrophysics Data System (ADS)

Liu, Huanlin; Xiong, Cuilian; Chen, Yong; Li, Changping; Chen, Derun

2018-03-01

To improve resources utilization efficiency, network virtualization in elastic optical networks has been developed by sharing the same physical network for difference users and applications. In the process of virtual nodes mapping, longer paths between physical nodes will consume more spectrum resources and energy. To address the problem, we propose a virtual optical network mapping algorithm called genetic multi-objective optimize virtual optical network mapping algorithm (GM-OVONM-AL), which jointly optimizes the energy consumption and spectrum resources consumption in the process of virtual optical network mapping. Firstly, a vector function is proposed to balance the energy consumption and spectrum resources by optimizing population classification and crowding distance sorting. Then, an adaptive crossover operator based on hierarchical comparison is proposed to improve search ability and convergence speed. In addition, the principle of the survival of the fittest is introduced to select better individual according to the relationship of domination rank. Compared with the spectrum consecutiveness-opaque virtual optical network mapping-algorithm and baseline-opaque virtual optical network mapping algorithm, simulation results show the proposed GM-OVONM-AL can achieve the lowest bandwidth blocking probability and save the energy consumption.

A new approach on the upgrade of energetic system based on green energy. A complex comparative analysis of the EEDI and EEOI

NASA Astrophysics Data System (ADS)

Faitar, C.; Novac, I.

2016-08-01

In recent years, many environmental organizations was interested to optimize the energy consumption which has become, today, one of the main concerns to the whole world. From this point of view, the maritime industry, has strove to optimize the fuel consumption of ship through the development of engines and propulsion system, improve the hull design, or using alternative energies, this way making a reduction in the amount of CO2 released to the atmosphere. The main idea of this paper is to realize a complex comparative analysis of Energy Efficiency Design Index and Energy Efficiency Operational Indicator which are calculated in two cases: first, in a classical approach for a crude oil super tanker ship and second, after the energy performance of this ship has been improved by introducing alternative energy sources on board.

A paradigm for viewing biologic systems as scale-free networks based on energy efficiency: implications for present therapies and the future of evolution.

PubMed

Yun, Anthony J; Lee, Patrick Y; Doux, John D

2006-01-01

A network constitutes an abstract description of the relationships among entities, respectively termed links and nodes. If a power law describes the probability distribution of the number of links per node, the network is said to be scale-free. Scale-free networks feature link clustering around certain hubs based on preferential attachments that emerge due either to merit or legacy. Biologic systems ranging from sub-atomic to ecosystems represent scale-free networks in which energy efficiency forms the basis of preferential attachments. This paradigm engenders a novel scale-free network theory of evolution based on energy efficiency. As environmental flux induces fitness dislocations and compels a new meritocracy, new merit-based hubs emerge, previously merit-based hubs become legacy hubs, and network recalibration occurs to achieve system optimization. To date, Darwinian evolution, characterized by innovation sampling, variation, and selection through filtered termination, has enabled biologic progress through optimization of energy efficiency. However, as humans remodel their environment, increasing the level of unanticipated fitness dislocations and inducing evolutionary stress, the tendency of networks to exhibit inertia and retain legacy hubs engender maladaptations. Many modern diseases may fundamentally derive from these evolutionary displacements. Death itself may constitute a programmed adaptation, terminating individuals who represent legacy hubs and recalibrating the network. As memes replace genes as the basis of innovation, death itself has become a legacy hub. Post-Darwinian evolution may favor indefinite persistence to optimize energy efficiency. We describe strategies to reprogram or decommission legacy hubs that participate in human disease and death.

Investigation of Cost and Energy Optimization of Drinking Water Distribution Systems.

PubMed

Cherchi, Carla; Badruzzaman, Mohammad; Gordon, Matthew; Bunn, Simon; Jacangelo, Joseph G

2015-11-17

Holistic management of water and energy resources through energy and water quality management systems (EWQMSs) have traditionally aimed at energy cost reduction with limited or no emphasis on energy efficiency or greenhouse gas minimization. This study expanded the existing EWQMS framework and determined the impact of different management strategies for energy cost and energy consumption (e.g., carbon footprint) reduction on system performance at two drinking water utilities in California (United States). The results showed that optimizing for cost led to cost reductions of 4% (Utility B, summer) to 48% (Utility A, winter). The energy optimization strategy was successfully able to find the lowest energy use operation and achieved energy usage reductions of 3% (Utility B, summer) to 10% (Utility A, winter). The findings of this study revealed that there may be a trade-off between cost optimization (dollars) and energy use (kilowatt-hours), particularly in the summer, when optimizing the system for the reduction of energy use to a minimum incurred cost increases of 64% and 184% compared with the cost optimization scenario. Water age simulations through hydraulic modeling did not reveal any adverse effects on the water quality in the distribution system or in tanks from pump schedule optimization targeting either cost or energy minimization.

Exploring efficacy of residential energy efficiency programs in Florida

NASA Astrophysics Data System (ADS)

Taylor, Nicholas Wade

Electric utilities, government agencies, and private interests in the U.S. have committed and continue to invest substantial resources in the pursuit of energy efficiency and conservation through demand-side management (DSM) programs. Program investments, and the demand for impact evaluations that accompany them, are projected to grow in coming years due to increased pressure from state-level energy regulation, costs and challenges of building additional production capacity, fuel costs and potential carbon or renewable energy regulation. This dissertation provides detailed analyses of ex-post energy savings from energy efficiency programs in three key sectors of residential buildings: new, single-family, detached homes; retrofits to existing single-family, detached homes; and retrofits to existing multifamily housing units. Each of the energy efficiency programs analyzed resulted in statistically significant energy savings at the full program group level, yet savings for individual participants and participant subgroups were highly variable. Even though savings estimates were statistically greater than zero, those energy savings did not always meet expectations. Results also show that high variability in energy savings among participant groups or subgroups can negatively impact overall program performance and can undermine marketing efforts for future participation. Design, implementation, and continued support of conservation programs based solely on deemed or projected savings is inherently counter to the pursuit of meaningful energy conservation and reductions in greenhouse gas emissions. To fully understand and optimize program impacts, consistent and robust measurement and verification protocols must be instituted in the design phase and maintained over time. Furthermore, marketing for program participation must target those who have the greatest opportunity for savings. In most utility territories it is not possible to gain access to the type of large scale datasets that would facilitate robust program analysis. Along with measuring and optimizing energy conservation programs, utilities should provide public access to historical consumption data. Open access to data, program optimization, consistent measurement and verification and transparency in reported savings are essential to reducing energy use and its associated environmental impacts.

Optimization of Energy Efficiency and Conservation in Green Building Design Using Duelist, Killer-Whale and Rain-Water Algorithms

NASA Astrophysics Data System (ADS)

Biyanto, T. R.; Matradji; Syamsi, M. N.; Fibrianto, H. Y.; Afdanny, N.; Rahman, A. H.; Gunawan, K. S.; Pratama, J. A. D.; Malwindasari, A.; Abdillah, A. I.; Bethiana, T. N.; Putra, Y. A.

2017-11-01

The development of green building has been growing in both design and quality. The development of green building was limited by the issue of expensive investment. Actually, green building can reduce the energy usage inside the building especially in utilization of cooling system. External load plays major role in reducing the usage of cooling system. External load is affected by type of wall sheathing, glass and roof. The proper selection of wall, type of glass and roof material are very important to reduce external load. Hence, the optimization of energy efficiency and conservation in green building design is required. Since this optimization consist of integer and non-linear equations, this problem falls into Mixed-Integer-Non-Linear-Programming (MINLP) that required global optimization technique such as stochastic optimization algorithms. In this paper the optimized variables i.e. type of glass and roof were chosen using Duelist, Killer-Whale and Rain-Water Algorithms to obtain the optimum energy and considering the minimal investment. The optimization results exhibited the single glass Planibel-G with the 3.2 mm thickness and glass wool insulation provided maximum ROI of 36.8486%, EUI reduction of 54 kWh/m2·year, CO2 emission reduction of 486.8971 tons/year and reduce investment of 4,078,905,465 IDR.

Optimal Time-Resource Allocation for Energy-Efficient Physical Activity Detection

PubMed Central

Thatte, Gautam; Li, Ming; Lee, Sangwon; Emken, B. Adar; Annavaram, Murali; Narayanan, Shrikanth; Spruijt-Metz, Donna; Mitra, Urbashi

2011-01-01

The optimal allocation of samples for physical activity detection in a wireless body area network for health-monitoring is considered. The number of biometric samples collected at the mobile device fusion center, from both device-internal and external Bluetooth heterogeneous sensors, is optimized to minimize the transmission power for a fixed number of samples, and to meet a performance requirement defined using the probability of misclassification between multiple hypotheses. A filter-based feature selection method determines an optimal feature set for classification, and a correlated Gaussian model is considered. Using experimental data from overweight adolescent subjects, it is found that allocating a greater proportion of samples to sensors which better discriminate between certain activity levels can result in either a lower probability of error or energy-savings ranging from 18% to 22%, in comparison to equal allocation of samples. The current activity of the subjects and the performance requirements do not significantly affect the optimal allocation, but employing personalized models results in improved energy-efficiency. As the number of samples is an integer, an exhaustive search to determine the optimal allocation is typical, but computationally expensive. To this end, an alternate, continuous-valued vector optimization is derived which yields approximately optimal allocations and can be implemented on the mobile fusion center due to its significantly lower complexity. PMID:21796237

Efficiency optimization in a correlation ratchet with asymmetric unbiased fluctuations

NASA Astrophysics Data System (ADS)

Ai, Bao-Quan; Wang, Xian-Ju; Liu, Guo-Tao; Wen, De-Hua; Xie, Hui-Zhang; Chen, Wei; Liu, Liang-Gang

2003-12-01

The efficiency of a Brownian particle moving in a periodic potential in the presence of asymmetric unbiased fluctuations is investigated. We found that even on the quasistatic limit there is a regime where the efficiency can be a peaked function of temperature, which proves that thermal fluctuations facilitate the efficiency of energy transformation, contradicting the earlier findings [H. Kamegawa et al., Phys. Rev. Lett. 80, 5251 (1998)]. It is also found that the mutual interplay between temporal asymmetry and spatial asymmetry may induce optimized efficiency at finite temperatures. The ratchet is not most efficient when it gives maximum current.

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

DOE PAGES

Stadler, M.; Groissböck, M.; Cardoso, G.; ...

2014-08-05

The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables tomore » 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This document shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic investment results are presented and compared to the observed investment decision at the test site. Results obtained considering building shell improvement options suggest an optimal weighted average U value of about 0.53 W/(m 2K) for the test site. This result is approximately 25% higher than what is currently observed in the building, suggesting that the retrofits made in 2002 were not optimal. Furthermore, the results obtained with DER-CAM illustrate the complexity of interactions between DER and passive measure options, showcasing the need for a holistic optimization approach to effectively optimize energy costs and CO 2 emissions. Lastly, the simultaneous optimization of building shell improvements and DER investments enables building owners to take one step further towards nearly zero energy buildings (nZEB) or nearly zero carbon emission buildings (nZCEB), and therefore support the 20/20/20 goals.« less

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stadler, M.; Groissböck, M.; Cardoso, G.

The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables tomore » 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This document shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic investment results are presented and compared to the observed investment decision at the test site. Results obtained considering building shell improvement options suggest an optimal weighted average U value of about 0.53 W/(m 2K) for the test site. This result is approximately 25% higher than what is currently observed in the building, suggesting that the retrofits made in 2002 were not optimal. Furthermore, the results obtained with DER-CAM illustrate the complexity of interactions between DER and passive measure options, showcasing the need for a holistic optimization approach to effectively optimize energy costs and CO 2 emissions. Lastly, the simultaneous optimization of building shell improvements and DER investments enables building owners to take one step further towards nearly zero energy buildings (nZEB) or nearly zero carbon emission buildings (nZCEB), and therefore support the 20/20/20 goals.« less

Analysis and Optimization of Building Energy Consumption

NASA Astrophysics Data System (ADS)

Chuah, Jun Wei

Energy is one of the most important resources required by modern human society. In 2010, energy expenditures represented 10% of global gross domestic product (GDP). By 2035, global energy consumption is expected to increase by more than 50% from current levels. The increased pace of global energy consumption leads to significant environmental and socioeconomic issues: (i) carbon emissions, from the burning of fossil fuels for energy, contribute to global warming, and (ii) increased energy expenditures lead to reduced standard of living. Efficient use of energy, through energy conservation measures, is an important step toward mitigating these effects. Residential and commercial buildings represent a prime target for energy conservation, comprising 21% of global energy consumption and 40% of the total energy consumption in the United States. This thesis describes techniques for the analysis and optimization of building energy consumption. The thesis focuses on building retrofits and building energy simulation as key areas in building energy optimization and analysis. The thesis first discusses and evaluates building-level renewable energy generation as a solution toward building energy optimization. The thesis next describes a novel heating system, called localized heating. Under localized heating, building occupants are heated individually by directed radiant heaters, resulting in a considerably reduced heated space and significant heating energy savings. To support localized heating, a minimally-intrusive indoor occupant positioning system is described. The thesis then discusses occupant-level sensing (OLS) as the next frontier in building energy optimization. OLS captures the exact environmental conditions faced by each building occupant, using sensors that are carried by all building occupants. The information provided by OLS enables fine-grained optimization for unprecedented levels of energy efficiency and occupant comfort. The thesis also describes a retrofit-oriented building energy simulator, ROBESim, that natively supports building retrofits. ROBESim extends existing building energy simulators by providing a platform for the analysis of novel retrofits, in addition to simulating existing retrofits. Using ROBESim, retrofits can be automatically applied to buildings, obviating the need for users to manually update building characteristics for comparisons between different building retrofits. ROBESim also includes several ease-of-use enhancements to support users of all experience levels.

Designing train-speed trajectory with energy efficiency and service quality

NASA Astrophysics Data System (ADS)

Jia, Jiannan; Yang, Kai; Yang, Lixing; Gao, Yuan; Li, Shukai

2018-05-01

With the development of automatic train operations, optimal trajectory design is significant to the performance of train operations in railway transportation systems. Considering energy efficiency and service quality, this article formulates a bi-objective train-speed trajectory optimization model to minimize simultaneously the energy consumption and travel time in an inter-station section. This article is distinct from previous studies in that more sophisticated train driving strategies characterized by the acceleration/deceleration gear, the cruising speed, and the speed-shift site are specifically considered. For obtaining an optimal train-speed trajectory which has equal satisfactory degree on both objectives, a fuzzy linear programming approach is applied to reformulate the objectives. In addition, a genetic algorithm is developed to solve the proposed train-speed trajectory optimization problem. Finally, a series of numerical experiments based on a real-world instance of Beijing-Tianjin Intercity Railway are implemented to illustrate the practicability of the proposed model as well as the effectiveness of the solution methodology.

Online energy management strategy of fuel cell hybrid electric vehicles based on data fusion approach

NASA Astrophysics Data System (ADS)

Zhou, Daming; Al-Durra, Ahmed; Gao, Fei; Ravey, Alexandre; Matraji, Imad; Godoy Simões, Marcelo

2017-10-01

Energy management strategy plays a key role for Fuel Cell Hybrid Electric Vehicles (FCHEVs), it directly affects the efficiency and performance of energy storages in FCHEVs. For example, by using a suitable energy distribution controller, the fuel cell system can be maintained in a high efficiency region and thus saving hydrogen consumption. In this paper, an energy management strategy for online driving cycles is proposed based on a combination of the parameters from three offline optimized fuzzy logic controllers using data fusion approach. The fuzzy logic controllers are respectively optimized for three typical driving scenarios: highway, suburban and city in offline. To classify patterns of online driving cycles, a Probabilistic Support Vector Machine (PSVM) is used to provide probabilistic classification results. Based on the classification results of the online driving cycle, the parameters of each offline optimized fuzzy logic controllers are then fused using Dempster-Shafer (DS) evidence theory, in order to calculate the final parameters for the online fuzzy logic controller. Three experimental validations using Hardware-In-the-Loop (HIL) platform with different-sized FCHEVs have been performed. Experimental comparison results show that, the proposed PSVM-DS based online controller can achieve a relatively stable operation and a higher efficiency of fuel cell system in real driving cycles.

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

NASA Astrophysics Data System (ADS)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Simulation model for assessing the efficiency of a combined power installation based on a geothermal heat pump and a vacuum solar collector

NASA Astrophysics Data System (ADS)

Vaysman, Ya I.; Surkov, AA; Surkova, Yu I.; Kychkin, AV

2017-06-01

The article is devoted to the use of renewable energy sources and the assessment of the feasibility of their use in the climatic conditions of the Western Urals. A simulation model that calculates the efficiency of a combined power installations (CPI) was (RES) developed. The CPI consists of the geothermal heat pump (GHP) and the vacuum solar collector (VCS) and is based on the research model. This model allows solving a wide range of problems in the field of energy and resource efficiency, and can be applied to other objects using RES. Based on the research recommendations for optimizing the management and the application of CPI were given. The optimization system will give a positive effect in the energy and resource consumption of low-rise residential buildings projects.

Irrelevance of the Power Stroke for the Directionality, Stopping Force, and Optimal Efficiency of Chemically Driven Molecular Machines

PubMed Central

Astumian, R. Dean

2015-01-01

A simple model for a chemically driven molecular walker shows that the elastic energy stored by the molecule and released during the conformational change known as the power-stroke (i.e., the free-energy difference between the pre- and post-power-stroke states) is irrelevant for determining the directionality, stopping force, and efficiency of the motor. Further, the apportionment of the dependence on the externally applied force between the forward and reverse rate constants of the power-stroke (or indeed among all rate constants) is irrelevant for determining the directionality, stopping force, and efficiency of the motor. Arguments based on the principle of microscopic reversibility demonstrate that this result is general for all chemically driven molecular machines, and even more broadly that the relative energies of the states of the motor have no role in determining the directionality, stopping force, or optimal efficiency of the machine. Instead, the directionality, stopping force, and optimal efficiency are determined solely by the relative heights of the energy barriers between the states. Molecular recognition—the ability of a molecular machine to discriminate between substrate and product depending on the state of the machine—is far more important for determining the intrinsic directionality and thermodynamics of chemo-mechanical coupling than are the details of the internal mechanical conformational motions of the machine. In contrast to the conclusions for chemical driving, a power-stroke is very important for the directionality and efficiency of light-driven molecular machines and for molecular machines driven by external modulation of thermodynamic parameters. PMID:25606678

Renewable energy sources, the internet of things and the third industrial revolution: Smart grid and contemporary information and communication technologies

NASA Astrophysics Data System (ADS)

Kitsios, Aristidis; Bousakas, Konstantinos; Salame, Takla; Bogno, Bachirou; Papageorgas, Panagiotis; Vokas, Georgios A.; Mauffay, Fabrice; Petit, Pierre; Aillerie, Michel; Charles, Jean-Pierre

2017-02-01

In this paper, the energy efficiency of a contemporary Smart Grid that is based on Distributed Renewable Energy Sources (DRES) is examined under the scope of the communication systems utilized between the energy loads and the energy sources. What is evident is that the Internet of Things (IoT) technologies that are based on the existing Web infrastructure can be heavily introduced in this direction especially when combined with long range low bandwidth networking technologies, power line communication technologies and optimization methodologies for renewable energy generation. The renewable energy generation optimization will be based on devices embedded in the PV panels and the wind power generators, which will rely on bidirectional communications with local gateways and remote control stations for achieving energy efficiency. Smart meters and DRES combined with IoT communications will be the enabling technologies for the ultimate fusion of Internet technology and renewable energy generation realizing the Energy Internet.

Federal roles to realize national energy-efficiency opportunities in the 1990s

NASA Astrophysics Data System (ADS)

Hirst, Eric

1989-10-01

Improving energy efficiency throughout the U.S. economy is a vital component of our nation's energy future, with many benefits. Improving efficiency can: save money consumers, increase economic productivity and international competitiveness, reduce oil and gas prices by reducing the demand for foreign oil, enhance national security by lowering oil imports, reduce the adverse environmental consequences of fuel cycles, especially acid rain and global warming, add diversity and flexibility to the nation's portfolio of energy resources, respond to public interest in, and support of, energy efficiency. The primary purpose of this report is to suggest expanded roles for the U.S. Department of Energy (DOE) in improving energy efficiency during the 1990s. In an ideal world, the normal workings of the market place would yield optimal energy-efficiency purchase and operating decisions. Unfortunately, distortions in fuel prices, limited access to capital, misplaced incentives, lack of information, and difficulty in processing information complicate energy-related decision making. Thus, consumers in all sectors of the economy underinvest in energy-efficient systems. These market barriers, coupled with growing concern about environmental quality, justify a larger Federal role.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

Scheduling for energy and reliability management on multiprocessor real-time systems

NASA Astrophysics Data System (ADS)

Qi, Xuan

Scheduling algorithms for multiprocessor real-time systems have been studied for years with many well-recognized algorithms proposed. However, it is still an evolving research area and many problems remain open due to their intrinsic complexities. With the emergence of multicore processors, it is necessary to re-investigate the scheduling problems and design/develop efficient algorithms for better system utilization, low scheduling overhead, high energy efficiency, and better system reliability. Focusing cluster schedulings with optimal global schedulers, we study the utilization bound and scheduling overhead for a class of cluster-optimal schedulers. Then, taking energy/power consumption into consideration, we developed energy-efficient scheduling algorithms for real-time systems, especially for the proliferating embedded systems with limited energy budget. As the commonly deployed energy-saving technique (e.g. dynamic voltage frequency scaling (DVFS)) will significantly affect system reliability, we study schedulers that have intelligent mechanisms to recuperate system reliability to satisfy the quality assurance requirements. Extensive simulation is conducted to evaluate the performance of the proposed algorithms on reduction of scheduling overhead, energy saving, and reliability improvement. The simulation results show that the proposed reliability-aware power management schemes could preserve the system reliability while still achieving substantial energy saving.

Simulation of value stream mapping and discrete optimization of energy consumption in modular construction

NASA Astrophysics Data System (ADS)

Chowdhury, Md Mukul

With the increased practice of modularization and prefabrication, the construction industry gained the benefits of quality management, improved completion time, reduced site disruption and vehicular traffic, and improved overall safety and security. Whereas industrialized construction methods, such as modular and manufactured buildings, have evolved over decades, core techniques used in prefabrication plants vary only slightly from those employed in traditional site-built construction. With a focus on energy and cost efficient modular construction, this research presents the development of a simulation, measurement and optimization system for energy consumption in the manufacturing process of modular construction. The system is based on Lean Six Sigma principles and loosely coupled system operation to identify the non-value adding tasks and possible causes of low energy efficiency. The proposed system will also include visualization functions for demonstration of energy consumption in modular construction. The benefits of implementing this system include a reduction in the energy consumption in production cost, decrease of energy cost in the production of lean-modular construction, and increase profit. In addition, the visualization functions will provide detailed information about energy efficiency and operation flexibility in modular construction. A case study is presented to validate the reliability of the system.

Ion collector design for an energy recovery test proposal with the negative ion source NIO1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Variale, V., E-mail: vincenzo.variale@ba.infn.it; Cavenago, M.; Agostinetti, P.

2016-02-15

Commercial viability of thermonuclear fusion power plants depends also on minimizing the recirculation power used to operate the reactor. The neutral beam injector (NBI) remains one of the most important method for plasma heating and control. For the future fusion power plant project DEMO, a NBI wall plug efficiency at least of 0.45 is required, while efficiency of present NBI project is about 0.25. The D{sup −} beam from a negative ion source is partially neutralized by a gas cell, which leaves more than 40% of energy in residual beams (D{sup −} and D{sup +}), so that an ion beammore » energy recovery system can significantly contribute to optimize efficiency. Recently, the test negative ion source NIO1 (60 keV, 9 beamlets with 15 mA H{sup −} each) has been designed and built at RFX (Padua) for negative ion production efficiency and the beam quality optimization. In this paper, a study proposal to use the NIO1 source also for a beam energy recovery test experiment is presented and a preliminary design of a negative ion beam collector with simulations of beam energy recovery is discussed.« less

Optimal energy-utilization ratio for long-distance cruising of a model fish

NASA Astrophysics Data System (ADS)

Liu, Geng; Yu, Yong-Liang; Tong, Bing-Gang

2012-07-01

The efficiency of total energy utilization and its optimization for long-distance migration of fish have attracted much attention in the past. This paper presents theoretical and computational research, clarifying the above well-known classic questions. Here, we specify the energy-utilization ratio (fη) as a scale of cruising efficiency, which consists of the swimming speed over the sum of the standard metabolic rate and the energy consumption rate of muscle activities per unit mass. Theoretical formulation of the function fη is made and it is shown that based on a basic dimensional analysis, the main dimensionless parameters for our simplified model are the Reynolds number (Re) and the dimensionless quantity of the standard metabolic rate per unit mass (Rpm). The swimming speed and the hydrodynamic power output in various conditions can be computed by solving the coupled Navier-Stokes equations and the fish locomotion dynamic equations. Again, the energy consumption rate of muscle activities can be estimated by the quotient of dividing the hydrodynamic power by the muscle efficiency studied by previous researchers. The present results show the following: (1) When the value of fη attains a maximum, the dimensionless parameter Rpm keeps almost constant for the same fish species in different sizes. (2) In the above cases, the tail beat period is an exponential function of the fish body length when cruising is optimal, e.g., the optimal tail beat period of Sockeye salmon is approximately proportional to the body length to the power of 0.78. Again, the larger fish's ability of long-distance cruising is more excellent than that of smaller fish. (3) The optimal swimming speed we obtained is consistent with previous researchers’ estimations.

Impedance Matching Antenna-Integrated High-Efficiency Energy Harvesting Circuit

PubMed Central

Shinki, Yuharu; Shibata, Kyohei; Mansour, Mohamed

2017-01-01

This paper describes the design of a high-efficiency energy harvesting circuit with an integrated antenna. The circuit is composed of series resonance and boost rectifier circuits for converting radio frequency power into boosted direct current (DC) voltage. The measured output DC voltage is 5.67 V for an input of 100 mV at 900 MHz. Antenna input impedance matching is optimized for greater efficiency and miniaturization. The measured efficiency of this antenna-integrated energy harvester is 60% for −4.85 dBm input power and a load resistance equal to 20 kΩ at 905 MHz. PMID:28763043

Impedance Matching Antenna-Integrated High-Efficiency Energy Harvesting Circuit.

PubMed

Shinki, Yuharu; Shibata, Kyohei; Mansour, Mohamed; Kanaya, Haruichi

2017-08-01

This paper describes the design of a high-efficiency energy harvesting circuit with an integrated antenna. The circuit is composed of series resonance and boost rectifier circuits for converting radio frequency power into boosted direct current (DC) voltage. The measured output DC voltage is 5.67 V for an input of 100 mV at 900 MHz. Antenna input impedance matching is optimized for greater efficiency and miniaturization. The measured efficiency of this antenna-integrated energy harvester is 60% for -4.85 dBm input power and a load resistance equal to 20 kΩ at 905 MHz.

Optimizing the ionization and energy absorption of laser-irradiated clusters

NASA Astrophysics Data System (ADS)

Kundu, M.; Bauer, D.

2008-03-01

It is known that rare-gas or metal clusters absorb incident laser energy very efficiently. However, due to the intricate dependencies on all the laser and cluster parameters, it is difficult to predict under which circumstances ionization and energy absorption are optimal. With the help of three-dimensional particle-in-cell simulations of xenon clusters (up to 17256 atoms), it is shown that for a given laser pulse energy and cluster, an optimum wavelength exists that corresponds to the approximate wavelength of the transient, linear Mie-resonance of the ionizing cluster at an early stage of negligible expansion. In a single ultrashort laser pulse, the linear resonance at this optimum wavelength yields much higher absorption efficiency than in the conventional, dual-pulse pump-probe setup of linear resonance during cluster expansion.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zitney, S.E.

Emerging fossil energy power generation systems must operate with unprecedented efficiency and near-zero emissions, while optimizing profitably amid cost fluctuations for raw materials, finished products, and energy. To help address these challenges, the fossil energy industry will have to rely increasingly on the use advanced computational tools for modeling and simulating complex process systems. In this paper, we present the computational research challenges and opportunities for the optimization of fossil energy power generation systems across the plant lifecycle from process synthesis and design to plant operations. We also look beyond the plant gates to discuss research challenges and opportunities formore » enterprise-wide optimization, including planning, scheduling, and supply chain technologies.« less

Feature-based Approach in Product Design with Energy Efficiency Consideration

NASA Astrophysics Data System (ADS)

Li, D. D.; Zhang, Y. J.

2017-10-01

In this paper, a method to measure the energy efficiency and ecological footprint metrics of features is proposed for product design. First the energy consumption models of various manufacturing features, like cutting feature, welding feature, etc. are studied. Then, the total energy consumption of a product is modeled and estimated according to its features. Finally, feature chains that combined by several sequence features based on the producing operation orders are defined and analyzed to calculate global optimal solution. The corresponding assessment model is also proposed to estimate their energy efficiency and ecological footprint. Finally, an example is given to validate the proposed approach in the improvement of sustainability.

Efficiency optimization of a photovoltaic water pumping system for irrigation in Ouargla, Algeria

NASA Astrophysics Data System (ADS)

Louazene, M. L.; Garcia, M. C. Alonso; Korichi, D.

2017-02-01

This work is technical study to contribute to the optimization of pumping systems powered by solar energy (clean) and used in the field of agriculture. To achieve our goals, we studied the techniques that must be entered on a photovoltaic system for maximum energy from solar panels. Our scientific contribution in this research is the realization of an efficient photovoltaic pumping system for irrigation needs. To achieve this and extract maximum power from the PV generator, two axes have been optimized: 1. Increase in the uptake of solar radiation by choice an optimum tilt angle of the solar panels, and 2. it is necessary to add an adaptation device, MPPT controller with a DC-DC converter, between the source and the load.

Optimization of the multi-turn injection efficiency for a medical synchrotron

NASA Astrophysics Data System (ADS)

Kim, J.; Yoon, M.; Yim, H.

2016-09-01

We present a method for optimizing the multi-turn injection efficiency for a medical synchrotron. We show that for a given injection energy, the injection efficiency can be greatly enhanced by choosing transverse tunes appropriately and by optimizing the injection bump and the number of turns required for beam injection. We verify our study by applying the method to the Korea Heavy Ion Medical Accelerator (KHIMA) synchrotron which is currently being built at the campus of Dongnam Institute of Radiological and Medical Sciences (DIRAMS) in Busan, Korea. First the frequency map analysis was performed with the help of the ELEGANT and the ACCSIM codes. The tunes that yielded good injection efficiency were then selected. With these tunes, the injection bump and the number of turns required for injection were then optimized by tracking a number of particles for up to one thousand turns after injection, beyond which no further beam loss occurred. Results for the optimization of the injection efficiency for proton ions are presented.

Optimization of joint energy micro-grid with cold storage

NASA Astrophysics Data System (ADS)

Xu, Bin; Luo, Simin; Tian, Yan; Chen, Xianda; Xiong, Botao; Zhou, Bowen

2018-02-01

To accommodate distributed photovoltaic (PV) curtailment, to make full use of the joint energy micro-grid with cold storage, and to reduce the high operating costs, the economic dispatch of joint energy micro-grid load is particularly important. Considering the different prices during the peak and valley durations, an optimization model is established, which takes the minimum production costs and PV curtailment fluctuations as the objectives. Linear weighted sum method and genetic-taboo Particle Swarm Optimization (PSO) algorithm are used to solve the optimization model, to obtain optimal power supply output. Taking the garlic market in Henan as an example, the simulation results show that considering distributed PV and different prices in different time durations, the optimization strategies are able to reduce the operating costs and accommodate PV power efficiently.

Peak power reduction and energy efficiency improvement with the superconducting flywheel energy storage in electric railway system

NASA Astrophysics Data System (ADS)

Lee, Hansang; Jung, Seungmin; Cho, Yoonsung; Yoon, Donghee; Jang, Gilsoo

2013-11-01

This paper proposes an application of the 100 kWh superconducting flywheel energy storage systems to reduce the peak power of the electric railway system. The electric railway systems have high-power characteristics and large amount of regenerative energy during vehicles’ braking. The high-power characteristic makes operating cost high as the system should guarantee the secure capacity of electrical equipment and the low utilization rate of regenerative energy limits the significant energy efficiency improvement. In this paper, it had been proved that the peak power reduction and energy efficiency improvement can be achieved by using 100 kWh superconducting flywheel energy storage systems with the optimally controlled charging or discharging operations. Also, economic benefits had been assessed.

Visual prosthesis wireless energy transfer system optimal modeling.

PubMed

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

Visual prosthesis wireless energy transfer system optimal modeling

PubMed Central

2014-01-01

Background Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. Methods On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling’s more accuracy for the actual application. Results The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. Conclusions The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system’s further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application. PMID:24428906

Combining gait optimization with passive system to increase the energy efficiency of a humanoid robot walking movement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pereira, Ana I.; ALGORITMI,University of Minho; Lima, José

There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The energy consumption can also be reduced with elastic elements coupled to each joint. The presented paper addresses an optimization method, the Stretched Simulated Annealing, that runs in an accurate and stable simulation model to find the optimal gait combined with elastic elements. Finalmore » results demonstrate that optimization is a valid gait planning technique.« less

Valuing uncertain cash flows from investments that enhance energy efficiency.

PubMed

Abadie, Luis M; Chamorro, José M; González-Eguino, Mikel

2013-02-15

There is a broad consensus that investments to enhance energy efficiency quickly pay for themselves in lower energy bills and spared emission allowances. However, investments that at first glance seem worthwhile usually are not undertaken. One of the plausible, non-excluding explanations is the numerous uncertainties that these investments face. This paper deals with the optimal time to invest in an energy efficiency enhancement at a facility already in place that consumes huge amounts of a fossil fuel (coal) and operates under carbon constraints. We follow the Real Options approach. Our model comprises three sources of uncertainty following different stochastic processes which allows for application in a broad range of settings. We assess the investment option by means of a three-dimensional binomial lattice. We compute the trigger investment cost, i.e., the threshold level below which immediate investment would be optimal. We analyze the major drivers of this decision thus aiming at the most promising policies in this regard. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Efficiency of industrial energy conservation and carbon emission reduction in Liaoning Pro-vince based on data envelopment analysis (DEA)method.

PubMed

Wang, Li; Xi, Feng Ming; Li, Jin Xin; Liu, Li Li

2016-09-01

Taking 39 industries as independent decision-making units in Liaoning Province from 2003 to 2012 and considering the benefits of energy, economy and environment, we combined direction distance function and radial DEA method to estimate and decompose the energy conservation and carbon emissions reduction efficiency of the industries. Carbon emission of each industry was calculated and defined as an undesirable output into the model of energy saving and carbon emission reduction efficiency. The results showed that energy saving and carbon emission reduction efficiency of industries had obvious heterogeneity in Liaoning Province. The whole energy conservation and carbon emissions reduction efficiency in each industry of Liaoning Province was not high, but it presented a rising trend. Improvements of pure technical efficiency and scale efficiency were the main measures to enhance energy saving and carbon emission reduction efficiency, especially scale efficiency improvement. In order to improve the energy saving and carbon emission reduction efficiency of each industry in Liaoning Province, we put forward that Liaoning Province should adjust industry structure, encourage the development of low carbon high benefit industries, improve scientific and technological level and adjust the industry scale reasonably, meanwhile, optimize energy structure, and develop renewable and clean energy.

Electrokinetic Analysis of Energy Harvest from Natural Salt Gradients in Nanochannels.

PubMed

He, Yuhui; Huang, Zhuo; Chen, Bowei; Tsutsui, Makusu; Shui Miao, Xiang; Taniguchi, Masateru

2017-10-13

The Gibbs free energy released during the mixing of river and sea water has been illustrated as a promising source of clean and renewable energy. Reverse electrodialysis (RED) is one major strategy to gain electrical power from this natural salinity, and recently by utilizing nanochannels a novel mode of this approach has shown improved power density and energy converting efficiency. In this work, we carry out an electrokinetic analysis of the work extracted from RED in the nanochannels. First, we outline the exclusion potential effect induced by the inhomogeneous distribution of extra-counterions along the channel axis. This effect is unique in nanochannel RED and how to optimize it for energy harvesting is the central topic of this work. We then discuss two important indexes of performance, which are the output power density and the energy converting efficiency, and their dependence on the nanochannel parameters such as channel material and geometry. In order to yield maximized output electrical power, we propose a device design by stepwise usage of the saline bias, and the lengths of the nanochannels are optimized to achieve the best trade-off between the input thermal power and the energy converting efficiency.

Ecodriving in hybrid electric vehicles--Exploring challenges for user-energy interaction.

PubMed

Franke, Thomas; Arend, Matthias Georg; McIlroy, Rich C; Stanton, Neville A

2016-07-01

Hybrid electric vehicles (HEVs) can help to reduce transport emissions; however, user behaviour has a significant effect on the energy savings actually achieved in everyday usage. The present research aimed to advance understanding of HEV drivers' ecodriving strategies, and the challenges for optimal user-energy interaction. We conducted interviews with 39 HEV drivers who achieved above-average fuel efficiencies. Regression analyses showed that technical system knowledge and ecodriving motivation were both important predictors for ecodriving efficiency. Qualitative data analyses showed that drivers used a plethora of ecodriving strategies and had diverse conceptualisations of HEV energy efficiency regarding aspects such as the efficiency of actively utilizing electric energy or the efficiency of different acceleration strategies. Drivers also reported several false beliefs regarding HEV energy efficiency that could impair ecodriving efforts. Results indicate that ecodriving support systems should facilitate anticipatory driving and help users locate and maintain drivetrain states of maximum efficiency. Copyright © 2016 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Layered host-guest long-afterglow ultrathin nanosheets: high-efficiency phosphorescence energy transfer at 2D confined interface.

PubMed

Gao, Rui; Yan, Dongpeng

2017-01-01

Tuning and optimizing the efficiency of light energy transfer play an important role in meeting modern challenges of minimizing energy loss and developing high-performance optoelectronic materials. However, attempts to fabricate systems giving highly efficient energy transfer between luminescent donor and acceptor have achieved limited success to date. Herein, we present a strategy towards phosphorescence energy transfer at a 2D orderly crystalline interface. We first show that new ultrathin nanosheet materials giving long-afterglow luminescence can be obtained by assembling aromatic guests into a layered double hydroxide host. Furthermore, we demonstrate that co-assembly of these long-lived energy donors with an energy acceptor in the same host generates an ordered arrangement of phosphorescent donor-acceptor pairs spatially confined within the 2D nanogallery, which affords energy transfer efficiency as high as 99.7%. Therefore, this work offers an alternative route to develop new types of long-afterglow nanohybrids and efficient light transfer systems with potential energy, illumination and sensor applications.

Sustaining Action and Optimizing Entropy: Coupling Efficiency for Energy and the Sustainability of Global Ecosystems

ERIC Educational Resources Information Center

Rose, Michael T.; Crossan, Angus N.; Kennedy, Ivan R.

2008-01-01

Consideration of the property of action is proposed to provide a more meaningful definition of efficient energy use and sustainable production in ecosystems. Action has physical dimensions similar to angular momentum, its magnitude varying with mass, spatial configuration and relative motion. In this article, the relationship of action to…

Optimal planning and design of a renewable energy based supply system for microgrids

DOE PAGES

Hafez, Omar; Bhattacharya, Kankar

2012-03-03

This paper presents a technique for optimal planning and design of hybrid renewable energy systems for microgrid applications. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is used to determine the optimal size and type of distributed energy resources (DERs) and their operating schedules for a sample utility distribution system. Using the DER-CAM results, an evaluation is performed to evaluate the electrical performance of the distribution circuit if the DERs selected by the DER-CAM optimization analyses are incorporated. Results of analyses regarding the economic benefits of utilizing the optimal locations identified for the selected DER within the system are alsomore » presented. The actual Brookhaven National Laboratory (BNL) campus electrical network is used as an example to show the effectiveness of this approach. The results show that these technical and economic analyses of hybrid renewable energy systems are essential for the efficient utilization of renewable energy resources for microgird applications.« less

Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks.

PubMed

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-12-13

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

Towards a Hybrid Energy Efficient Multi-Tree-Based Optimized Routing Protocol for Wireless Networks

PubMed Central

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-01-01

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. PMID:23443398

An Efficient Offloading Scheme For MEC System Considering Delay and Energy Consumption

NASA Astrophysics Data System (ADS)

Sun, Yanhua; Hao, Zhe; Zhang, Yanhua

2018-01-01

With the increasing numbers of mobile devices, mobile edge computing (MEC) which provides cloud computing capabilities proximate to mobile devices in 5G networks has been envisioned as a promising paradigm to enhance users experience. In this paper, we investigate a joint consideration of delay and energy consumption offloading scheme (JCDE) for MEC system in 5G heterogeneous networks. An optimization is formulated to minimize the delay as well as energy consumption of the offloading system, which the delay and energy consumption of transmitting and calculating tasks are taken into account. We adopt an iterative greedy algorithm to solve the optimization problem. Furthermore, simulations were carried out to validate the utility and effectiveness of our proposed scheme. The effect of parameter variations on the system is analysed as well. Numerical results demonstrate delay and energy efficiency promotion of our proposed scheme compared with another paper’s scheme.

The unlikely high efficiency of a molecular motor based on active motion

NASA Astrophysics Data System (ADS)

Ebeling, W.

2015-07-01

The efficiency of a simple model of a motor converting chemical into mechanical energy is studied analytically. The model motor shows interesting properties corresponding qualitatively to motors investigated in experiments. The efficiency increases with the load and may for low loss reach high values near to 100 percent in a narrow regime of optimal load. It is shown that the optimal load and the maximal efficiency depend by universal power laws on the dimensionless loss parameter. Stochastic effects decrease the stability of motor regimes with high efficiency and make them unlikely. Numerical studies show efficiencies below the theoretical optimum and demonstrate that special ratchet profiles my stabilize efficient regimes.

Eco-efficiency model for evaluating feedlot rations in the Great Plains, United States

USDA-ARS?s Scientific Manuscript database

Environmental impacts attributable to beef feedlot production provide an opportunity for economically-linked environmental efficiency optimization. An adaptable eco-efficiency model was developed to assess the impacts of dietary rations. The hybridized model utilized California Net Energy System m...

Conversion efficiency limits and bandgap designs for multi-junction solar cells with internal radiative efficiencies below unity.

PubMed

Zhu, Lin; Mochizuki, Toshimitsu; Yoshita, Masahiro; Chen, Shaoqiang; Kim, Changsu; Akiyama, Hidefumi; Kanemitsu, Yoshihiko

2016-05-16

We calculated the conversion-efficiency limit ηsc and the optimized subcell bandgap energies of 1 to 5 junction solar cells without and with intermediate reflectors under 1-sun AM1.5G and 1000-sun AM1.5D irradiations, particularly including the impact of internal radiative efficiency (ηint) below unity for realistic subcell materials on the basis of an extended detailed-balance theory. We found that the conversion-efficiency limit ηsc significantly drops when the geometric mean ηint* of all subcell ηint in the stack reduces from 1 to 0.1, and that ηsc degrades linearly to logηint* for ηint* below 0.1. For ηint*<0.1 differences in ηsc due to additional intermediate reflectors became very small if all subcells are optically thick for sun light. We obtained characteristic optimized bandgap energies, which reflect both ηint* decrease and AM1.5 spectral gaps. These results provide realistic efficiency targets and design principles.

Thermodynamic Performance and Cost Optimization of a Novel Hybrid Thermal-Compressed Air Energy Storage System Design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Houssainy, Sammy; Janbozorgi, Mohammad; Kavehpour, Pirouz

Compressed Air Energy Storage (CAES) can potentially allow renewable energy sources to meet electricity demands as reliably as coal-fired power plants. However, conventional CAES systems rely on the combustion of natural gas, require large storage volumes, and operate at high pressures, which possess inherent problems such as high costs, strict geological locations, and the production of greenhouse gas emissions. A novel and patented hybrid thermal-compressed air energy storage (HT-CAES) design is presented which allows a portion of the available energy, from the grid or renewable sources, to operate a compressor and the remainder to be converted and stored in themore » form of heat, through joule heating in a sensible thermal storage medium. The HT-CAES design incudes a turbocharger unit that provides supplementary mass flow rate alongside the air storage. The hybrid design and the addition of a turbocharger have the beneficial effect of mitigating the shortcomings of conventional CAES systems and its derivatives by eliminating combustion emissions and reducing storage volumes, operating pressures, and costs. Storage efficiency and cost are the two key factors, which upon integration with renewable energies would allow the sources to operate as independent forms of sustainable energy. The potential of the HT-CAES design is illustrated through a thermodynamic optimization study, which outlines key variables that have a major impact on the performance and economics of the storage system. The optimization analysis quantifies the required distribution of energy between thermal and compressed air energy storage, for maximum efficiency, and for minimum cost. This study provides a roundtrip energy and exergy efficiency map of the storage system and illustrates a trade off that exists between its capital cost and performance.« less

Expanding the detection efficiency of silicon drift detectors

NASA Astrophysics Data System (ADS)

Schlosser, D. M.; Lechner, P.; Lutz, G.; Niculae, A.; Soltau, H.; Strüder, L.; Eckhardt, R.; Hermenau, K.; Schaller, G.; Schopper, F.; Jaritschin, O.; Liebel, A.; Simsek, A.; Fiorini, C.; Longoni, A.

2010-12-01

To expand the detection efficiency Silicon Drift Detectors (SDDs) with various customized radiation entrance windows, optimized detector areas and geometries have been developed. Optimum values for energy resolution, peak to background ratio (P/B) and high count rate capability support the development. Detailed results on sensors optimized for light element detection down to Boron or even lower will be reported. New developments for detecting medium and high X-ray energies by increasing the effective detector thickness will be presented. Gamma-ray detectors consisting of a SDD coupled to scintillators like CsI(Tl) and LaBr 3(Ce) have been examined. Results of the energy resolution for the 137Cs 662 keV line and the light yield (LY) of such detector systems will be reported.

DEGAS: Dynamic Exascale Global Address Space Programming Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demmel, James

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speedmore » and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics.« less

On Some Aspects of Energy Conservation in Industries

NASA Astrophysics Data System (ADS)

Rai, Keerti; Seksena, S. B. L.; Thakur, A. N.

2016-06-01

Energy demand has increased continuously due to advancement in technology and living standards of a large section of people resulting in a wide gap between supply and demand. One of the approaches to reduce this gap would be the adoption of measures of energy conservation in general and the efficient use of energy particularly in motor. This paper presents a review of the research activity in the field of efficiency optimization of three-phase induction motor drive. The approach is analyzed and the better option of energy conservation are identified.

Control strategy optimization of HVAC plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio

In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components andmore » energy systems, and is sufficiently fast to make it applicable to real-time setting.« less

Active optimal control strategies for increasing the efficiency of photovoltaic cells

NASA Astrophysics Data System (ADS)

Aljoaba, Sharif Zidan Ahmad

Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module edsigns toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter.

[Modeling and analysis of volume conduction based on field-circuit coupling].

PubMed

Tang, Zhide; Liu, Hailong; Xie, Xiaohui; Chen, Xiufa; Hou, Deming

2012-08-01

Numerical simulations of volume conduction can be used to analyze the process of energy transfer and explore the effects of some physical factors on energy transfer efficiency. We analyzed the 3D quasi-static electric field by the finite element method, and developed A 3D coupled field-circuit model of volume conduction basing on the coupling between the circuit and the electric field. The model includes a circuit simulation of the volume conduction to provide direct theoretical guidance for energy transfer optimization design. A field-circuit coupling model with circular cylinder electrodes was established on the platform of the software FEM3.5. Based on this, the effects of electrode cross section area, electrode distance and circuit parameters on the performance of volume conduction system were obtained, which provided a basis for optimized design of energy transfer efficiency.

Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle

NASA Astrophysics Data System (ADS)

Wu, Xiaohua; Hu, Xiaosong; Teng, Yanqiong; Qian, Shide; Cheng, Rui

2017-09-01

Hybrid solar-battery power source is essential in the nexus of plug-in electric vehicle (PEV), renewables, and smart building. This paper devises an optimization framework for efficient energy management and components sizing of a single smart home with home battery, PEV, and potovoltatic (PV) arrays. We seek to maximize the home economy, while satisfying home power demand and PEV driving. Based on the structure and system models of the smart home nanogrid, a convex programming (CP) problem is formulated to rapidly and efficiently optimize both the control decision and parameters of the home battery energy storage system (BESS). Considering different time horizons of optimization, home BESS prices, types and control modes of PEVs, the parameters of home BESS and electric cost are systematically investigated. Based on the developed CP control law in home to vehicle (H2V) mode and vehicle to home (V2H) mode, the home with BESS does not buy electric energy from the grid during the electric price's peak periods.

Technology and Performance Analysis Tools | Energy Analysis | NREL

Science.gov Websites

optimize renewable energy and energy efficiency technologies for your project. Many of these tools can be the consumer or energy professional. Biomass Scenario Model (BSM) Determine which supply chain changes (BLCC) Analyze capital investments in buildings. Includes the Energy Escalation Rate Calculator 2.0-15

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

The Optimization Based Dynamic and Cyclic Working Strategies for Rechargeable Wireless Sensor Networks with Multiple Base Stations and Wireless Energy Transfer Devices

PubMed Central

Ding, Xu; Han, Jianghong; Shi, Lei

2015-01-01

In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The wireless sensor network is firstly divided into sub networks according to the concept of Voronoi diagram. Then, the entire energy replenishing procedure is split into the pre-normal and normal energy replenishing stages. With the objective of maximizing the sojourn time ratio of the wireless energy transfer device, a continuous time optimization problem for the normal energy replenishing cycle is formed according to constraints with which sensor nodes and wireless energy transfer devices should comply. Later on, the continuous time optimization problem is reshaped into a discrete multi-phased optimization problem, which yields the identical optimality. After linearizing it, we obtain a linear programming problem that can be solved efficiently. The working strategies of both sensor nodes and wireless energy transfer devices in the pre-normal replenishing stage are also discussed in this paper. The intensive simulations exhibit the dynamic and cyclic working schemes for the entire energy replenishing procedure. Additionally, a way of eliminating “bottleneck” sensor nodes is also developed in this paper. PMID:25785305

The optimization based dynamic and cyclic working strategies for rechargeable wireless sensor networks with multiple base stations and wireless energy transfer devices.

PubMed

Ding, Xu; Han, Jianghong; Shi, Lei

2015-03-16

In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The wireless sensor network is firstly divided into sub networks according to the concept of Voronoi diagram. Then, the entire energy replenishing procedure is split into the pre-normal and normal energy replenishing stages. With the objective of maximizing the sojourn time ratio of the wireless energy transfer device, a continuous time optimization problem for the normal energy replenishing cycle is formed according to constraints with which sensor nodes and wireless energy transfer devices should comply. Later on, the continuous time optimization problem is reshaped into a discrete multi-phased optimization problem, which yields the identical optimality. After linearizing it, we obtain a linear programming problem that can be solved efficiently. The working strategies of both sensor nodes and wireless energy transfer devices in the pre-normal replenishing stage are also discussed in this paper. The intensive simulations exhibit the dynamic and cyclic working schemes for the entire energy replenishing procedure. Additionally, a way of eliminating "bottleneck" sensor nodes is also developed in this paper.

Opportunities for Improving the Energy Efficiency of Multi-Modal Intra-City Freight Movement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walkowicz, Kevin; Duran, Adam

This poster focuses on the National Renewable Energy Laboratory's analysis of opportunities for freight movement energy savings via optimization and integration of existing/emerging intra-city goods delivery modes as well as an assessment of the efficacy and energy consumption impact of new technologies.

The pressure cold wind system on the impact of industrial boiler economy and security

NASA Astrophysics Data System (ADS)

Li, Henan; Qian, Hongli; Jiang, Lei; Yu, Dekai; Li, Guannan; Yuan, Hong

2017-05-01

Industrial boiler is one of the most energy-consuming equipment in china, the annual consumption of energy accounts for about one-third of the national energy consumption.Industrial boiler in service at present have several severe problems such as small capacity, low efficiency, high energy consumption and causing severe pollution on environment, the average industrial boiler operation efficiency is only 65%. If the efficiency increased by 15% ∼ 20%, which meet the international advanced level, each year 70 million tons of coal saving and reduce environmental pollution[1]. As energy conservation and emissions reduction becomes the basic national policy of our country, improving the efficiency of industrial boiler energy is facing opportunities and challenges, optimizing the operation mode of the existing units, it is necessary to increase the flexibility of the boiler control.

A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks.

PubMed

Rani, Shalli; Talwar, Rajneesh; Malhotra, Jyoteesh; Ahmed, Syed Hassan; Sarkar, Mahasweta; Song, Houbing

2015-11-12

One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT.

A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks

PubMed Central

Rani, Shalli; Talwar, Rajneesh; Malhotra, Jyoteesh; Ahmed, Syed Hassan; Sarkar, Mahasweta; Song, Houbing

2015-01-01

One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT. PMID:26569260

Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation.

PubMed

Farshchiansadegh, Ali; Melendez-Calderon, Alejandro; Ranganathan, Rajiv; Murphey, Todd D; Mussa-Ivaldi, Ferdinando A

2016-04-01

The laws of physics establish the energetic efficiency of our movements. In some cases, like locomotion, the mechanics of the body dominate in determining the energetically optimal course of action. In other tasks, such as manipulation, energetic costs depend critically upon the variable properties of objects in the environment. Can the brain identify and follow energy-optimal motions when these motions require moving along unfamiliar trajectories? What feedback information is required for such optimal behavior to occur? To answer these questions, we asked participants to move their dominant hand between different positions while holding a virtual mechanical system with complex dynamics (a planar double pendulum). In this task, trajectories of minimum kinetic energy were along curvilinear paths. Our findings demonstrate that participants were capable of finding the energy-optimal paths, but only when provided with veridical visual and haptic information pertaining to the object, lacking which the trajectories were executed along rectilinear paths.

Analytical Study on Multi-Tier 5G Heterogeneous Small Cell Networks: Coverage Performance and Energy Efficiency.

PubMed

Xiao, Zhu; Liu, Hongjing; Havyarimana, Vincent; Li, Tong; Wang, Dong

2016-11-04

In this paper, we investigate the coverage performance and energy efficiency of multi-tier heterogeneous cellular networks (HetNets) which are composed of macrocells and different types of small cells, i.e., picocells and femtocells. By virtue of stochastic geometry tools, we model the multi-tier HetNets based on a Poisson point process (PPP) and analyze the Signal to Interference Ratio (SIR) via studying the cumulative interference from pico-tier and femto-tier. We then derive the analytical expressions of coverage probabilities in order to evaluate coverage performance in different tiers and investigate how it varies with the small cells' deployment density. By taking the fairness and user experience into consideration, we propose a disjoint channel allocation scheme and derive the system channel throughput for various tiers. Further, we formulate the energy efficiency optimization problem for multi-tier HetNets in terms of throughput performance and resource allocation fairness. To solve this problem, we devise a linear programming based approach to obtain the available area of the feasible solutions. System-level simulations demonstrate that the small cells' deployment density has a significant effect on the coverage performance and energy efficiency. Simulation results also reveal that there exits an optimal small cell base station (SBS) density ratio between pico-tier and femto-tier which can be applied to maximize the energy efficiency and at the same time enhance the system performance. Our findings provide guidance for the design of multi-tier HetNets for improving the coverage performance as well as the energy efficiency.

Analytical Study on Multi-Tier 5G Heterogeneous Small Cell Networks: Coverage Performance and Energy Efficiency

PubMed Central

Xiao, Zhu; Liu, Hongjing; Havyarimana, Vincent; Li, Tong; Wang, Dong

2016-01-01

In this paper, we investigate the coverage performance and energy efficiency of multi-tier heterogeneous cellular networks (HetNets) which are composed of macrocells and different types of small cells, i.e., picocells and femtocells. By virtue of stochastic geometry tools, we model the multi-tier HetNets based on a Poisson point process (PPP) and analyze the Signal to Interference Ratio (SIR) via studying the cumulative interference from pico-tier and femto-tier. We then derive the analytical expressions of coverage probabilities in order to evaluate coverage performance in different tiers and investigate how it varies with the small cells’ deployment density. By taking the fairness and user experience into consideration, we propose a disjoint channel allocation scheme and derive the system channel throughput for various tiers. Further, we formulate the energy efficiency optimization problem for multi-tier HetNets in terms of throughput performance and resource allocation fairness. To solve this problem, we devise a linear programming based approach to obtain the available area of the feasible solutions. System-level simulations demonstrate that the small cells’ deployment density has a significant effect on the coverage performance and energy efficiency. Simulation results also reveal that there exits an optimal small cell base station (SBS) density ratio between pico-tier and femto-tier which can be applied to maximize the energy efficiency and at the same time enhance the system performance. Our findings provide guidance for the design of multi-tier HetNets for improving the coverage performance as well as the energy efficiency. PMID:27827917

Multi-parameter optimization of piezoelectric actuators for multi-mode active vibration control of cylindrical shells

NASA Astrophysics Data System (ADS)

Hu, K. M.; Li, Hua

2018-07-01

A novel technique for the multi-parameter optimization of distributed piezoelectric actuators is presented in this paper. The proposed method is designed to improve the performance of multi-mode vibration control in cylindrical shells. The optimization parameters of actuator patch configuration include position, size, and tilt angle. The modal control force of tilted orthotropic piezoelectric actuators is derived and the multi-parameter cylindrical shell optimization model is established. The linear quadratic energy index is employed as the optimization criterion. A geometric constraint is proposed to prevent overlap between tilted actuators, which is plugged into a genetic algorithm to search the optimal configuration parameters. A simply-supported closed cylindrical shell with two actuators serves as a case study. The vibration control efficiencies of various parameter sets are evaluated via frequency response and transient response simulations. The results show that the linear quadratic energy indexes of position and size optimization decreased by 14.0% compared to position optimization; those of position and tilt angle optimization decreased by 16.8%; and those of position, size, and tilt angle optimization decreased by 25.9%. It indicates that, adding configuration optimization parameters is an efficient approach to improving the vibration control performance of piezoelectric actuators on shells.

Method of optimizing performance of Rankine cycle power plants

DOEpatents

Pope, William L.; Pines, Howard S.; Doyle, Padraic A.; Silvester, Lenard F.

1982-01-01

A method for efficiently operating a Rankine cycle power plant (10) to maximize fuel utilization efficiency or energy conversion efficiency or minimize costs by selecting a turbine (22) fluid inlet state which is substantially in the area adjacent and including the transposed critical temperature line (46).

Genetic algorithm optimization of transcutaneous energy transmission systems for implantable ventricular assist devices.

PubMed

Byron, Kelly; Bluvshtein, Vlad; Lucke, Lori

2013-01-01

Transcutaneous energy transmission systems (TETS) wirelessly transmit power through the skin. TETS is particularly desirable for ventricular assist devices (VAD), which currently require cables through the skin to power the implanted pump. Optimizing the inductive link of the TET system is a multi-parameter problem. Most current techniques to optimize the design simplify the problem by combining parameters leading to sub-optimal solutions. In this paper we present an optimization method using a genetic algorithm to handle a larger set of parameters, which leads to a more optimal design. Using this approach, we were able to increase efficiency while also reducing power variability in a prototype, compared to a traditional manual design method.

Design and optimization of zero-energy-consumption based solar energy residential building systems

NASA Astrophysics Data System (ADS)

Zheng, D. L.; Yu, L. J.; Tan, H. W.

2017-11-01

Energy consumption of residential buildings has grown fast in recent years, thus raising a challenge on zero energy residential building (ZERB) systems, which aim at substantially reducing energy consumption of residential buildings. Thus, how to facilitate ZERB has become a hot but difficult topic. In the paper, we put forward the overall design principle of ZERB based on analysis of the systems’ energy demand. In particular, the architecture for both schematic design and passive technology is optimized and both energy simulation analysis and energy balancing analysis are implemented, followed by committing the selection of high-efficiency appliance and renewable energy sources for ZERB residential building. In addition, Chinese classical residential building has been investigated in the proposed case, in which several critical aspects such as building optimization, passive design, PV panel and HVAC system integrated with solar water heater, Phase change materials, natural ventilation, etc., have been taken into consideration.

Energy Performance Monitoring and Optimization System for DoD Campuses

DTIC Science & Technology

2014-02-01

estimated that, on average, the EPMO system exceeded the energy consumption reduction target of 20% and improved occupant thermal comfort by reducing the...dynamic models, operational and thermal comfort constraints, and plant efficiency in the same framework (Borrelli and Keviczky, 2008; Borrelli, Pekar...optimization modeling language uses the models described above in conjunction with information such as: thermal comfort constraints, equipment constraints, and

Distributed Wireless Power Transfer With Energy Feedback

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Zhang, Rui

2017-04-01

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they can be constructively combined at the energy receiver (ER) to achieve an EB gain that scales with the number of ETs. However, the optimal design of EB waveforms requires accurate channel state information (CSI) at the ETs, which is challenging to obtain practically, especially in a distributed system with ETs at separate locations. In this paper, we study practical and efficient channel training methods to achieve optimal EB in a distributed WET system. We propose two protocols with and without centralized coordination, respectively, where distributed ETs either sequentially or in parallel adapt their transmit phases based on a low-complexity energy feedback from the ER. The energy feedback only depends on the received power level at the ER, where each feedback indicates one particular transmit phase that results in the maximum harvested power over a set of previously used phases. Simulation results show that the two proposed training protocols converge very fast in practical WET systems even with a large number of distributed ETs, while the protocol with sequential ET phase adaptation is also analytically shown to converge to the optimal EB design with perfect CSI by increasing the training time. Numerical results are also provided to evaluate the performance of the proposed distributed EB and training designs as compared to other benchmark schemes.

Energy Efficiency Maximization of Practical Wireless Communication Systems

NASA Astrophysics Data System (ADS)

Eraslan, Eren

Energy consumption of the modern wireless communication systems is rapidly growing due to the ever-increasing data demand and the advanced solutions employed in order to address this demand, such as multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques. These MIMO systems are power hungry, however, they are capable of changing the transmission parameters, such as number of spatial streams, number of transmitter/receiver antennas, modulation, code rate, and transmit power. They can thus choose the best mode out of possibly thousands of modes in order to optimize an objective function. This problem is referred to as the link adaptation problem. In this work, we focus on the link adaptation for energy efficiency maximization problem, which is defined as choosing the optimal transmission mode to maximize the number of successfully transmitted bits per unit energy consumed by the link. We model the energy consumption and throughput performances of a MIMO-OFDM link and develop a practical link adaptation protocol, which senses the channel conditions and changes its transmission mode in real-time. It turns out that the brute force search, which is usually assumed in previous works, is prohibitively complex, especially when there are large numbers of transmit power levels to choose from. We analyze the relationship between the energy efficiency and transmit power, and prove that energy efficiency of a link is a single-peaked quasiconcave function of transmit power. This leads us to develop a low-complexity algorithm that finds a near-optimal transmit power and take this dimension out of the search space. We further prune the search space by analyzing the singular value decomposition of the channel and excluding the modes that use higher number of spatial streams than the channel can support. These algorithms and our novel formulations provide simpler computations and limit the search space into a much smaller set; hence reducing the computational complexity by orders of magnitude without sacrificing the performance. The result of this work is a highly practical link adaptation protocol for maximizing the energy efficiency of modern wireless communication systems. Simulation results show orders of magnitude gain in the energy efficiency of the link. We also implemented the link adaptation protocol on real-time MIMO-OFDM radios and we report on the experimental results. To the best of our knowledge, this is the first reported testbed that is capable of performing energy-efficient fast link adaptation using PHY layer information.

The optimization problems of CP operation

NASA Astrophysics Data System (ADS)

Kler, A. M.; Stepanova, E. L.; Maximov, A. S.

2017-11-01

The problem of enhancing energy and economic efficiency of CP is urgent indeed. One of the main methods for solving it is optimization of CP operation. To solve the optimization problems of CP operation, Energy Systems Institute, SB of RAS, has developed a software. The software makes it possible to make optimization calculations of CP operation. The software is based on the techniques and software tools of mathematical modeling and optimization of heat and power installations. Detailed mathematical models of new equipment have been developed in the work. They describe sufficiently accurately the processes that occur in the installations. The developed models include steam turbine models (based on the checking calculation) which take account of all steam turbine compartments and regeneration system. They also enable one to make calculations with regenerative heaters disconnected. The software for mathematical modeling of equipment and optimization of CP operation has been developed. It is based on the technique for optimization of CP operating conditions in the form of software tools and integrates them in the common user interface. The optimization of CP operation often generates the need to determine the minimum and maximum possible total useful electricity capacity of the plant at set heat loads of consumers, i.e. it is necessary to determine the interval on which the CP capacity may vary. The software has been applied to optimize the operating conditions of the Novo-Irkutskaya CP of JSC “Irkutskenergo”. The efficiency of operating condition optimization and the possibility for determination of CP energy characteristics that are necessary for optimization of power system operation are shown.

Complex-energy approach to sum rules within nuclear density functional theory

DOE PAGES

Hinohara, Nobuo; Kortelainen, Markus; Nazarewicz, Witold; ...

2015-04-27

The linear response of the nucleus to an external field contains unique information about the effective interaction, correlations governing the behavior of the many-body system, and properties of its excited states. To characterize the response, it is useful to use its energy-weighted moments, or sum rules. By comparing computed sum rules with experimental values, the information content of the response can be utilized in the optimization process of the nuclear Hamiltonian or nuclear energy density functional (EDF). But the additional information comes at a price: compared to the ground state, computation of excited states is more demanding. To establish anmore » efficient framework to compute energy-weighted sum rules of the response that is adaptable to the optimization of the nuclear EDF and large-scale surveys of collective strength, we have developed a new technique within the complex-energy finite-amplitude method (FAM) based on the quasiparticle random- phase approximation. The proposed sum-rule technique based on the complex-energy FAM is a tool of choice when optimizing effective interactions or energy functionals. The method is very efficient and well-adaptable to parallel computing. As a result, the FAM formulation is especially useful when standard theorems based on commutation relations involving the nuclear Hamiltonian and external field cannot be used.« less

Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels

NASA Technical Reports Server (NTRS)

Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.

2011-01-01

We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.

Energy neutral and low power wireless communications

NASA Astrophysics Data System (ADS)

Orhan, Oner

Wireless sensor nodes are typically designed to have low cost and small size. These design objectives impose restrictions on the capacity and efficiency of the transceiver components and energy storage units that can be used. As a result, energy becomes a bottleneck and continuous operation of the sensor network requires frequent battery replacements, increasing the maintenance cost. Energy harvesting and energy efficient transceiver architectures are able to overcome these challenges by collecting energy from the environment and utilizing the energy in an intelligent manner. However, due to the nature of the ambient energy sources, the amount of useful energy that can be harvested is limited and unreliable. Consequently, optimal management of the harvested energy and design of low power transceivers pose new challenges for wireless network design and operation. The first part of this dissertation is on energy neutral wireless networking, where optimal transmission schemes under different system setups and objectives are investigated. First, throughput maximization for energy harvesting two-hop networks with decode-and-forward half-duplex relays is studied. For a system with two parallel relays, various combinations of the following four transmission modes are considered: Broadcast from the source, multi-access from the relays, and successive relaying phases I and II. Next, the energy cost of the processing circuitry as well as the transmission energy are taken into account for communication over a broadband fading channel powered by an energy harvesting transmitter. Under this setup, throughput maximization, energy maximization, and transmission completion time minimization problems are studied. Finally, source and channel coding for an energy-limited wireless sensor node is investigated under various energy constraints including energy harvesting, processing and sampling costs. For each objective, optimal transmission policies are formulated as the solutions of a convex optimization problem, and the properties of these optimal policies are identified. In the second part of this thesis, low power transceiver design is considered for millimeter wave communication systems. In particular, using an additive quantization noise model, the effect of analog-digital conversion (ADC) resolution and bandwidth on the achievable rate is investigated for a multi-antenna system under a receiver power constraint. Two receiver architectures, analog and digital combining, are compared in terms of performance.

Imaging Tasks Scheduling for High-Altitude Airship in Emergency Condition Based on Energy-Aware Strategy

PubMed Central

Zhimeng, Li; Chuan, He; Dishan, Qiu; Jin, Liu; Manhao, Ma

2013-01-01

Aiming to the imaging tasks scheduling problem on high-altitude airship in emergency condition, the programming models are constructed by analyzing the main constraints, which take the maximum task benefit and the minimum energy consumption as two optimization objectives. Firstly, the hierarchy architecture is adopted to convert this scheduling problem into three subproblems, that is, the task ranking, value task detecting, and energy conservation optimization. Then, the algorithms are designed for the sub-problems, and the solving results are corresponding to feasible solution, efficient solution, and optimization solution of original problem, respectively. This paper makes detailed introduction to the energy-aware optimization strategy, which can rationally adjust airship's cruising speed based on the distribution of task's deadline, so as to decrease the total energy consumption caused by cruising activities. Finally, the application results and comparison analysis show that the proposed strategy and algorithm are effective and feasible. PMID:23864822

Efficient transportation for Vermont : optimal statewide transit networks.

DOT National Transportation Integrated Search

2011-01-01

"Public transit systems are receiving increased attention as viable solutions to problems with : transportation system robustness, energy-efficiency and equity. The over-reliance on a single : mode, the automobile, is a threat to system robustness. I...

Thermoelectric efficiency of nanoscale devices in the linear regime

NASA Astrophysics Data System (ADS)

Bevilacqua, G.; Grosso, G.; Menichetti, G.; Pastori Parravicini, G.

2016-12-01

We study quantum transport through two-terminal nanoscale devices in contact with two particle reservoirs at different temperatures and chemical potentials. We discuss the general expressions controlling the electric charge current, heat currents, and the efficiency of energy transmutation in steady conditions in the linear regime. With focus in the parameter domain where the electron system acts as a power generator, we elaborate workable expressions for optimal efficiency and thermoelectric parameters of nanoscale devices. The general concepts are set at work in the paradigmatic cases of Lorentzian resonances and antiresonances, and the encompassing Fano transmission function: the treatments are fully analytic, in terms of the trigamma functions and Bernoulli numbers. From the general curves here reported describing transport through the above model transmission functions, useful guidelines for optimal efficiency and thermopower can be inferred for engineering nanoscale devices in energy regions where they show similar transmission functions.

Optimal conditions for preparation of banana peels, sugarcane bagasse and watermelon rind in removing copper from water.

PubMed

Liu, Cong; Ngo, Huu Hao; Guo, Wenshan; Tung, Kuo-Lun

2012-09-01

In this study, three agro-waste materials were used as biosorbents for removal of copper (Cu) from water. This work aims to optimise conditions for preparation of these materials to obtain maximum Cu adsorption capacity. The optimal conditions were determined in terms of Cu removal efficiency and/or energy consumption. The results indicate that banana peels dried at 120°C for 2h and ground into powder form led to a better performance in terms of both copper removal efficiency and energy consumption. For sugarcane bagasse and watermelon rind, 120°C was the suitable drying temperature. However, the best drying time was 1h for sugarcane bagasse and 3h for watermelon rind. The powder form with size of <150 μm was optimal for all biosorbents in terms of removal efficiency and equilibration time. The findings are beneficial to the application of these agro-waste materials for Cu removal from water and wastewater treatment. Copyright © 2012. Published by Elsevier Ltd.

Optimal estimates of free energies from multistate nonequilibrium work data.

PubMed

Maragakis, Paul; Spichty, Martin; Karplus, Martin

2006-03-17

We derive the optimal estimates of the free energies of an arbitrary number of thermodynamic states from nonequilibrium work measurements; the work data are collected from forward and reverse switching processes and obey a fluctuation theorem. The maximum likelihood formulation properly reweights all pathways contributing to a free energy difference and is directly applicable to simulations and experiments. We demonstrate dramatic gains in efficiency by combining the analysis with parallel tempering simulations for alchemical mutations of model amino acids.

Optimization of the operating conditions of gas-turbine power stations considering the effect of equipment deterioration

NASA Astrophysics Data System (ADS)

Aminov, R. Z.; Kozhevnikov, A. I.

2017-10-01

In recent years in most power systems all over the world, a trend towards the growing nonuniformity of energy consumption and generation schedules has been observed. The increase in the portion of renewable energy sources is one of the important challenges for many countries. The ill-predictable character of such energy sources necessitates a search for practical solutions. Presently, the most efficient method for compensating for nonuniform generation of the electric power by the renewable energy sources—predominantly by the wind and solar energy—is generation of power at conventional fossil-fuel-fired power stations. In Russia, this problem is caused by the increasing portion in the generating capacity structure of the nuclear power stations, which are most efficient when operating under basic conditions. Introduction of hydropower and pumped storage hydroelectric power plants and other energy-storage technologies does not cover the demand for load-following power capacities. Owing to a simple design, low construction costs, and a sufficiently high economic efficiency, gas turbine plants (GTPs) prove to be the most suitable for covering the nonuniform electric-demand schedules. However, when the gas turbines are operated under varying duty conditions, the lifetime of the primary thermostressed components is considerably reduced and, consequently, the repair costs increase. A method is proposed for determination of the total operating costs considering the deterioration of the gas turbine equipment under varying duty and start-stop conditions. A methodology for optimization of the loading modes for the gas turbine equipment is developed. The consideration of the lifetime component allows varying the optimal operating conditions and, in some cases, rejecting short-time stops of the gas turbine plants. The calculations performed in a wide range of varying fuel prices and capital investments per gas turbine equipment unit show that the economic effectiveness can be increased by 5-15% by varying the operating conditions and switching to the optimal operating modes. Consequently, irrespective of the fuel price, the application of the proposed method results in selection of the most beneficial operating conditions. Consideration of the lifetime expenditure included in the optimization criterion enables enhancement of the operating efficiency.

Recovery Act: High-Efficiency, Wideband Three-Phase Rectifiers and Adaptive Rectifier Management for Telecomm Central Office and Large Data Center Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mark A. Johnson

2012-06-29

Lineage Power and Verizon teamed up to address a DOE funding opportunity focused on improving the power conversion chain in telecommunications facilities and data centers. The project had three significant elements: the design and development of high efficiency and high power three-phase rectifiers by Lineage Power, design and development of software to optimize overall plant energy efficiency by Lineage Power, and a field trial in active Verizon telecommunications facilities where energy consumption was measured before and after efficiency upgrades.

Biomechanical evaluation of an innovative spring-loaded axillary crutch design.

PubMed

Zhang, Yanxin; Liu, Guangyu; Xie, Shengquan; Liger, Aurélien

2011-01-01

We evaluated an innovative spring-loaded crutch design by comparing its performance with standard crutches through a biomechanical approach. Gait analysis was conducted for 7 male subjects under two conditions: walking with standard crutches and with spring-loaded crutches. Three-dimensional kinematic data and ground reaction force were recorded. Spatiotemporal variables, external mechanical work, and elastic energy (for spring crutches) were calculated based on recorded data. The trajectories of vertical ground reaction forces with standard crutches had two main peaks before and after mid-stance, and those with optimized spring-loaded crutches had only one main peak. The magnitude of external mechanical work was significantly higher with spring-loaded crutches than with standard crutches for all subjects, and the transferred elastic energy made an important contribution to the total external work for spring-loaded crutches. No significant differences in the spatiotemporal parameters were observed. Optimized spring-loaded crutches can efficiently propel crutch walkers and could reduce the total energy expenditure in crutch walking. Further research using optimized spring-loaded crutches with respect to energy efficiency is recommended.

Sustainable Mobility Initiative | Transportation Research | NREL

Science.gov Websites

optimize mobility and significantly reduce related energy consumption. This concept of an intelligent measures to explore these technologies' effects on transportation energy use, emissions, and overall system . Efficient driving with smoother starts, stops, and accelerations to reduce energy consumption and

Assessment of the Charging Policy in Energy Efficiency of the Enterprise

NASA Astrophysics Data System (ADS)

Shutov, E. A.; E Turukina, T.; Anisimov, T. S.

2017-04-01

The forecasting problem for energy facilities with a power exceeding 670 kW is currently one of the main. In connection with rules of the retail electricity market such customers also pay for actual energy consumption deviations from plan value. In compliance with the hierarchical stages of the electricity market a guaranteeing supplier is to respect the interests of distribution and generation companies that require load leveling. The answer to this question for industrial enterprise is possible only within technological process through implementation of energy-efficient processing chains with the adaptive function and forecasting tool. In such a circumstance the primary objective of a forecasting is reduce the energy consumption costs by taking account of the energy cost correlation for 24 hours for forming of pumping unit work schedule. The pumping unit virtual model with the variable frequency drive is considered. The forecasting tool and the optimizer are integrated into typical control circuit. Economic assessment of the optimization method was estimated.

High performance solutions and data for nZEBs offices located in warm climates.

PubMed

Congedo, Paolo Maria; Baglivo, Cristina; Zacà, Ilaria; D Agostino, Delia

2015-12-01

This data article contains eleven tables supporting the research article entitled: Cost-Optimal Design For Nearly Zero Energy Office Buildings Located In Warm Climates [1]. The data explain the procedure of minimum energy performance requirements presented by the European Directive (EPBD) [2] to establish several variants of energy efficiency measures with the integration of renewable energy sources in order to reach nZEBs (nearly zero energy buildings) by 2020. This files include the application of comparative methodological framework and give the cost-optimal solutions for non-residential building located in Southern Italy. The data describe office sector in which direct the current European policies and investments [3], [4]. In particular, the localization of the building, geometrical features, thermal properties of the envelope and technical systems for HVAC are reported in the first sections. Energy efficiency measures related to orientation, walls, windows, heating, cooling, dhw and RES are given in the second part of the group; this data article provides 256 combinations for a financial and macroeconomic analysis.

Method of optimizing performance of Rankine cycle power plants. [US DOE Patent

DOEpatents

Pope, W.L.; Pines, H.S.; Doyle, P.A.; Silvester, L.F.

1980-06-23

A method is described for efficiently operating a Rankine cycle power plant to maximize fuel utilization efficiency or energy conversion efficiency or minimize costs by selecting a turbine fluid inlet state which is substantially on the area adjacent and including the transposed critical temperature line.

An energy-based perturbation and a taboo strategy for improving the searching ability of stochastic structural optimization methods

NASA Astrophysics Data System (ADS)

Cheng, Longjiu; Cai, Wensheng; Shao, Xueguang

2005-03-01

An energy-based perturbation and a new idea of taboo strategy are proposed for structural optimization and applied in a benchmark problem, i.e., the optimization of Lennard-Jones (LJ) clusters. It is proved that the energy-based perturbation is much better than the traditional random perturbation both in convergence speed and searching ability when it is combined with a simple greedy method. By tabooing the most wide-spread funnel instead of the visited solutions, the hit rate of other funnels can be significantly improved. Global minima of (LJ) clusters up to 200 atoms are found with high efficiency.

Behavior-aware cache hierarchy optimization for low-power multi-core embedded systems

NASA Astrophysics Data System (ADS)

Zhao, Huatao; Luo, Xiao; Zhu, Chen; Watanabe, Takahiro; Zhu, Tianbo

2017-07-01

In modern embedded systems, the increasing number of cores requires efficient cache hierarchies to ensure data throughput, but such cache hierarchies are restricted by their tumid size and interference accesses which leads to both performance degradation and wasted energy. In this paper, we firstly propose a behavior-aware cache hierarchy (BACH) which can optimally allocate the multi-level cache resources to many cores and highly improved the efficiency of cache hierarchy, resulting in low energy consumption. The BACH takes full advantage of the explored application behaviors and runtime cache resource demands as the cache allocation bases, so that we can optimally configure the cache hierarchy to meet the runtime demand. The BACH was implemented on the GEM5 simulator. The experimental results show that energy consumption of a three-level cache hierarchy can be saved from 5.29% up to 27.94% compared with other key approaches while the performance of the multi-core system even has a slight improvement counting in hardware overhead.

Optimal Energy Consumption Analysis of Natural Gas Pipeline

PubMed Central

Liu, Enbin; Li, Changjun; Yang, Yi

2014-01-01

There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the operating parameters of many pipelines are determined empirically by dispatchers, resulting in high energy consumption. This practice does not abide by energy reduction policies. Therefore, based on a full understanding of the actual needs of pipeline companies, we introduce production unit consumption indicators to establish an objective function for achieving the goal of lowering energy consumption. By using a dynamic programming method for solving the model and preparing calculation software, we can ensure that the solution process is quick and efficient. Using established optimization methods, we analyzed the energy savings for the XQ gas pipeline. By optimizing the boot program, the import station pressure, and the temperature parameters, we achieved the optimal energy consumption. By comparison with the measured energy consumption, the pipeline now has the potential to reduce energy consumption by 11 to 16 percent. PMID:24955410

U.S. Air Force Energy Program

DTIC Science & Technology

2011-05-01

prepared to acquire 50% of domestic aviation fuel requirements via an alternative fuel blend by 2016 Installation Energy  Reduce energy intensity by...FY10  On track to certify fleet on synthetic fuel blend by early 2011 Installation Energy  Reduced installation energy intensity nearly 15% since... Winglets Manufacturing Methods Propulsion Integration Alt Fuels Analysis New Efficient Engines Legacy Aircraft Energy Harvesting Weight-optimized

Replacement policy of residential lighting optimized for cost, energy, and greenhouse gas emissions

NASA Astrophysics Data System (ADS)

Liu, Lixi; Keoleian, Gregory A.; Saitou, Kazuhiro

2017-11-01

Accounting for 10% of the electricity consumption in the US, artificial lighting represents one of the easiest ways to cut household energy bills and greenhouse gas (GHG) emissions by upgrading to energy-efficient technologies such as compact fluorescent lamps (CFL) and light emitting diodes (LED). However, given the high initial cost and rapidly improving trajectory of solid-state lighting today, estimating the right time to switch over to LEDs from a cost, primary energy, and GHG emissions perspective is not a straightforward problem. This is an optimal replacement problem that depends on many determinants, including how often the lamp is used, the state of the initial lamp, and the trajectories of lighting technology and of electricity generation. In this paper, multiple replacement scenarios of a 60 watt-equivalent A19 lamp are analyzed and for each scenario, a few replacement policies are recommended. For example, at an average use of 3 hr day-1 (US average), it may be optimal both economically and energetically to delay the adoption of LEDs until 2020 with the use of CFLs, whereas purchasing LEDs today may be optimal in terms of GHG emissions. In contrast, incandescent and halogen lamps should be replaced immediately. Based on expected LED improvement, upgrading LED lamps before the end of their rated lifetime may provide cost and environmental savings over time by taking advantage of the higher energy efficiency of newer models.

Expected Improvements in Work Truck Efficiency Through Connectivity and Automation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walkowicz, Kevin A

This presentation focuses on the potential impact of connected and automated technologies on commercial vehicle operations. It includes topics such as the U.S. Department of Energy's Energy Efficient Mobility Systems (EEMS) program and the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Initiative. It also describes National Renewable Energy Laboratory (NREL) research findings pertaining to the potential energy impacts of connectivity and automation and stresses the need for integration and optimization to take advantage of the benefits offered by these transformative technologies while mitigating the potential negative consequences.

Efficient monoenergetic proton beam from ultra-fast laser interaction with nanostructured targets

NASA Astrophysics Data System (ADS)

Fazeli, R.

2018-03-01

The broad energy spectrum of laser-accelerated proton beams is the most important difficulty associated with such particle sources on the way to future applications such as medical therapy, proton imaging, inertial fusion, and high-energy physics. The generation of proton beams with enhanced monoenergetic features through an ultra-intense laser interaction with optimized nanostructured targets is reported. Targets were irradiated by 40 fs laser pulses of intensity 5.5 ×1020 W c m -2 and wavelength 1 μm. The results of multi-parametric Particle-in-Cell calculations showed that proton beams with considerably reduced energy spread can be obtained by using the proposed nanostructured target. At optimized target dimensions, the proton spectrum was found to exhibit a narrow peak at about 63 MeV with a relative energy spread of ΔE /Epeak˜ 5 % which is efficiently lower than what is expected for unstructured double layer targets (˜70%).

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

PubMed

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors.

PubMed

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-07-08

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Highly efficient hybrid energy generator: coupled organic photovoltaic device and randomly oriented electrospun poly(vinylidene fluoride) nanofiber.

PubMed

Park, Boongik; Lee, Kihwan; Park, Jongjin; Kim, Jongmin; Kim, Ohyun

2013-03-01

A hybrid architecture consisting of an inverted organic photovoltaic device and a randomly-oriented electrospun PVDF piezoelectric device was fabricated as a highly-efficient energy generator. It uses the inverted photovoltaic device with coupled electrospun PVDF nanofibers as tandem structure to convert solar and mechanical vibrations energy to electricity simultaneously or individually. The power conversion efficiency of the photovoltaic device was also significantly improved up to 4.72% by optimized processes such as intrinsic ZnO, MoO3 and active layer. A simple electrospinning method with the two electrode technique was adopted to achieve a high voltage of - 300 mV in PVDF piezoelectric fibers. Highly-efficient HEG using voltage adder circuit provides the conceptual possibility of realizing multi-functional energy generator whenever and wherever various energy sources are available.

High Performance Artificial Muscles Using Nanofiber and Hybrid Yarns

DTIC Science & Technology

2015-07-14

provide 3.2% energy conversion efficiency (twice that of our CNT fiber muscles and 10X that of conducting polymer muscles ). They maintain stroke without...rubber dielectric muscle layer in twisted fiber drives torsional actuation. (2) One hundred times higher torsional stroke per muscle length...artificial muscles that provide giant stroke, fast response, high force generation, and long cycle life while optimizing energy conversion efficiencies

High Efficiency, 100 mJ per pulse, Nd:YAG Oscillator Optimized for Space-Based Earth and Planetary Remote Sensing

NASA Technical Reports Server (NTRS)

Coyle, D. Barry; Stysley, Paul R.; Poulios, Demetrios; Fredrickson, Robert M.; Kay, Richard B.; Cory, Kenneth C.

2014-01-01

We report on a newly solid state laser transmitter, designed and packaged for Earth and planetary space-based remote sensing applications for high efficiency, low part count, high pulse energy scalability/stability, and long life. Finally, we have completed a long term operational test which surpassed 2 Billion pulses with no measured decay in pulse energy.

4E analysis and multi objective optimization of a micro gas turbine and solid oxide fuel cell hybrid combined heat and power system

NASA Astrophysics Data System (ADS)

Sanaye, Sepehr; Katebi, Arash

2014-02-01

Energy, exergy, economic and environmental (4E) analysis and optimization of a hybrid solid oxide fuel cell and micro gas turbine (SOFC-MGT) system for use as combined generation of heat and power (CHP) is investigated in this paper. The hybrid system is modeled and performance related results are validated using available data in literature. Then a multi-objective optimization approach based on genetic algorithm is incorporated. Eight system design parameters are selected for the optimization procedure. System exergy efficiency and total cost rate (including capital or investment cost, operational cost and penalty cost of environmental emissions) are the two objectives. The effects of fuel unit cost, capital investment and system power output on optimum design parameters are also investigated. It is observed that the most sensitive and important design parameter in the hybrid system is fuel cell current density which has a significant effect on the balance between system cost and efficiency. The selected design point from the Pareto distribution of optimization results indicates a total system exergy efficiency of 60.7%, with estimated electrical energy cost 0.057 kW-1 h-1, and payback period of about 6.3 years for the investment.

Portfolio-Scale Optimization of Customer Energy Efficiency Incentive and Marketing: Cooperative Research and Development Final Report, CRADA Number CRD-13-535

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brackney, Larry J.

North East utility National Grid (NGrid) is developing a portfolio-scale application of OpenStudio designed to optimize incentive and marketing expenditures for their energy efficiency (EE) programs. NGrid wishes to leverage a combination of geographic information systems (GIS), public records, customer data, and content from the Building Component Library (BCL) to form a JavaScript Object Notation (JSON) input file that is consumed by an OpenStudio-based expert system for automated model generation. A baseline model for each customer building will be automatically tuned using electricity and gas consumption data, and a set of energy conservation measures (ECMs) associated with each NGrid incentivemore » program will be applied to the model. The simulated energy performance and return on investment (ROI) will be compared with customer hurdle rates and available incentives to A) optimize the incentive required to overcome the customer hurdle rate and B) determine if marketing activity associated with the specific ECM is warranted for that particular customer. Repeated across their portfolio, this process will enable NGrid to substantially optimize their marketing and incentive expenditures, targeting those customers that will likely adopt and benefit from specific EE programs.« less

Space-planning and structural solutions of low-rise buildings: Optimal selection methods

NASA Astrophysics Data System (ADS)

Gusakova, Natalya; Minaev, Nikolay; Filushina, Kristina; Dobrynina, Olga; Gusakov, Alexander

2017-11-01

The present study is devoted to elaboration of methodology used to select appropriately the space-planning and structural solutions in low-rise buildings. Objective of the study is working out the system of criteria influencing the selection of space-planning and structural solutions which are most suitable for low-rise buildings and structures. Application of the defined criteria in practice aim to enhance the efficiency of capital investments, energy and resource saving, create comfortable conditions for the population considering climatic zoning of the construction site. Developments of the project can be applied while implementing investment-construction projects of low-rise housing at different kinds of territories based on the local building materials. The system of criteria influencing the optimal selection of space-planning and structural solutions of low-rise buildings has been developed. Methodological basis has been also elaborated to assess optimal selection of space-planning and structural solutions of low-rise buildings satisfying the requirements of energy-efficiency, comfort and safety, and economical efficiency. Elaborated methodology enables to intensify the processes of low-rise construction development for different types of territories taking into account climatic zoning of the construction site. Stimulation of low-rise construction processes should be based on the system of approaches which are scientifically justified; thus it allows enhancing energy efficiency, comfort, safety and economical effectiveness of low-rise buildings.

Smart Manufacturing Technologies and Data Analytics for Improving Energy Efficiency in Industrial Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nimbalkar, Sachin U.; Guo, Wei; Wenning, Thomas J.

Smart manufacturing and advanced data analytics can help the manufacturing sector unlock energy efficiency from the equipment level to the entire manufacturing facility and the whole supply chain. These technologies can make manufacturing industries more competitive, with intelligent communication systems, real-time energy savings, and increased energy productivity. Smart manufacturing can give all employees in an organization the actionable information they need, when they need it, so that each person can contribute to the optimal operation of the corporation through informed, data-driven decision making. This paper examines smart technologies and data analytics approaches for improving energy efficiency and reducing energy costsmore » in process-supporting energy systems. It dives into energy-saving improvement opportunities through smart manufacturing technologies and sophisticated data collection and analysis. The energy systems covered in this paper include those with motors and drives, fans, pumps, air compressors, steam, and process heating.« less

Relay selection in energy harvesting cooperative networks with rateless codes

NASA Astrophysics Data System (ADS)

Zhu, Kaiyan; Wang, Fei

2018-04-01

This paper investigates the relay selection in energy harvesting cooperative networks, where the relays harvests energy from the radio frequency (RF) signals transmitted by a source, and the optimal relay is selected and uses the harvested energy to assist the information transmission from the source to its destination. Both source and the selected relay transmit information using rateless code, which allows the destination recover original information after collecting codes bits marginally surpass the entropy of original information. In order to improve transmission performance and efficiently utilize the harvested power, the optimal relay is selected. The optimization problem are formulated to maximize the achievable information rates of the system. Simulation results demonstrate that our proposed relay selection scheme outperform other strategies.

Optimization of HTS superconducting magnetic energy storage magnet volume

NASA Astrophysics Data System (ADS)

Korpela, Aki; Lehtonen, Jorma; Mikkonen, Risto

2003-08-01

Nonlinear optimization problems in the field of electromagnetics have been successfully solved by means of sequential quadratic programming (SQP) and the finite element method (FEM). For example, the combination of SQP and FEM has been proven to be an efficient tool in the optimization of low temperature superconductors (LTS) superconducting magnetic energy storage (SMES) magnets. The procedure can also be applied for the optimization of HTS magnets. However, due to a strongly anisotropic material and a slanted electric field, current density characteristic high temperature superconductors HTS optimization is quite different from that of the LTS. In this paper the volumes of solenoidal conduction-cooled Bi-2223/Ag SMES magnets have been optimized at the operation temperature of 20 K. In addition to the electromagnetic constraints the stress caused by the tape bending has also been taken into account. Several optimization runs with different initial geometries were performed in order to find the best possible solution for a certain energy requirement. The optimization constraints describe the steady-state operation, thus the presented coil geometries are designed for slow ramping rates. Different energy requirements were investigated in order to find the energy dependence of the design parameters of optimized solenoidal HTS coils. According to the results, these dependences can be described with polynomial expressions.

Optimal coupling and feasibility of a solar-powered year-round ejector air conditioner

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sokolov, M.; Hershgal, D.

1993-06-01

An ejector refrigeration system that uses a conventional refrigerant (R-114) is introduced as a possible mechanism for providing solar-based air-conditioning. Optimal coupling conditions between the collectors' energy output and energy requirements of the cooling system, are investigated. Operation at such optimal conditions assures maximized overall efficiency. Procedures leading to the evaluation of the performance of a real system are disclosed. Design curves for such a system with R-114 as refrigerant are provided. A multi-ejectors arrangement that provides an efficient adjustment for variations of ambient conditions, is described. Year-round air-conditioning is facilitated by rerouting the refrigerant flow through a heating modemore » of the system. Calculations are carried out for illustrative configurations in which relatively low condensing temperature (water reservoirs, cooling towers, or moderate climate) can be maintained.« less

Energy Efficiency and Performance Limiting Effects in Thermo-Osmotic Energy Conversion from Low-Grade Heat.

PubMed

Straub, Anthony P; Elimelech, Menachem

2017-11-07

Low-grade heat energy from sources below 100 °C is available in massive quantities around the world, but cannot be converted to electricity effectively using existing technologies due to variability in the heat output and the small temperature difference between the source and environment. The recently developed thermo-osmotic energy conversion (TOEC) process has the potential to harvest energy from low-grade heat sources by using a temperature difference to create a pressurized liquid flux across a membrane, which can be converted to mechanical work via a turbine. In this study, we perform the first analysis of energy efficiency and the expected performance of the TOEC technology, focusing on systems utilizing hydrophobic porous vapor-gap membranes and water as a working fluid. We begin by developing a framework to analyze realistic mass and heat transport in the process, probing the impact of various membrane parameters and system operating conditions. Our analysis reveals that an optimized system can achieve heat-to-electricity energy conversion efficiencies up to 4.1% (34% of the Carnot efficiency) with hot and cold working temperatures of 60 and 20 °C, respectively, and an operating pressure of 5 MPa (50 bar). Lower energy efficiencies, however, will occur in systems operating with high power densities (>5 W/m 2 ) and with finite-sized heat exchangers. We identify that the most important membrane properties for achieving high performance are an asymmetric pore structure, high pressure resistance, a high porosity, and a thickness of 30 to 100 μm. We also quantify the benefits in performance from utilizing deaerated water streams, strong hydrodynamic mixing in the membrane module, and high heat exchanger efficiencies. Overall, our study demonstrates the promise of full-scale TOEC systems to extract energy from low-grade heat and identifies key factors for performance optimization moving forward.

Staircase Quantum Dots Configuration in Nanowires for Optimized Thermoelectric Power

PubMed Central

Li, Lijie; Jiang, Jian-Hua

2016-01-01

The performance of thermoelectric energy harvesters can be improved by nanostructures that exploit inelastic transport processes. One prototype is the three-terminal hopping thermoelectric device where electron hopping between quantum-dots are driven by hot phonons. Such three-terminal hopping thermoelectric devices have potential in achieving high efficiency or power via inelastic transport and without relying on heavy-elements or toxic compounds. We show in this work how output power of the device can be optimized via tuning the number and energy configuration of the quantum-dots embedded in parallel nanowires. We find that the staircase energy configuration with constant energy-step can improve the power factor over a serial connection of a single pair of quantum-dots. Moreover, for a fixed energy-step, there is an optimal length for the nanowire. Similarly for a fixed number of quantum-dots there is an optimal energy-step for the output power. Our results are important for future developments of high-performance nanostructured thermoelectric devices. PMID:27550093

Enhanced red emission of 808 nm excited upconversion nanoparticles by optimizing the composition of shell for efficient generation of singlet oxygen

NASA Astrophysics Data System (ADS)

Liu, Jinxue; Zhang, Tingbin; Song, Xiaoyan; Xing, Jinfeng

2018-01-01

With the aim to enhance the upconversion luminescence (UCL) intensity, much attention was paid to reduce the energy-back transfer from Er3+ ions to Nd3+ ions by constructing various kinds of multilayer upconversion nanoparticles (UCNPs). However, the energy-back transfer was difficult to be completely eliminated. Also, the thick shell of multilayer UCNPs is not favourable for effective Förster resonance energy transfer (FRET) in photodynamic therapy (PDT) system. Herein, an effective and facile method was applied to prepare UCNPs by optimizing the composition to largely enhance the red emission (at 660 nm) for efficient generation of singlet oxygen (1O2). In detail, the concentrations of Nd3+ ions and Yb3+ ions doped in the sensitizing shell were systematically researched to balance the energy back-transfer and the light harvest ability. The optimal emission and a relatively high Red/Green (R/G) ratio of NaYF4:Yb,Er,Nd@NaYF4:Yb0.1Nd0.2 UCNPs were obtained simultaneously. Furthermore, the emission under 980 nm excitation demonstrated the energy back-transfer from Er3+ to Yb3+ ions was also notable which was largely ignored previously. Then, UCNPs were encapsulated into mesoporous silica shell, and the photosensitizer Chlorin e6 (Ce6) was covalently conjugated to form a non-leaking nanoplatform. The efficiency of 1O2 generation obviously increased with the enhanced emission of UCNPs.

Gallium Nitride Direct Energy Conversion Betavoltaic Modeling and Optimization

DTIC Science & Technology

2017-03-01

require high energy density battery systems. Radioisotopes are the most energy dense materials that can be converted into electrical energy. Pure...beta radioisotopes can be used towards making a long-lasting battery. However, the process to convert the energy provided by a pure beta radioisotope ...betavoltaic. Each energy conversion method has different challenges to overcome to improve thesystem efficiency. These energy conversion methods that are

Energy optimization analysis of the more electric aircraft

NASA Astrophysics Data System (ADS)

Liu, Yitao; Deng, Junxiang; Liu, Chao; Li, Sen

2018-02-01

The More Electric Aircraft (MEA) underlines the utilization of the electrical power to drive the non-propulsive aircraft systems. The critical features of the MEA including no-bleed engine architecture and advanced electrical system are introduced. Energy and exergy analysis is conducted for the MEA, and comparison of the effectiveness and efficiency of the energy usage between conventional aircraft and the MEA is conducted. The results indicate that one of the advantages of the MEA architecture is the greater efficiency gained in terms of reduced fuel consumption.

Optimizing Parameters of Axial Pressure-Compounded Ultra-Low Power Impulse Turbines at Preliminary Design

NASA Astrophysics Data System (ADS)

Kalabukhov, D. S.; Radko, V. M.; Grigoriev, V. A.

2018-01-01

Ultra-low power turbine drives are used as energy sources in auxiliary power systems, energy units, terrestrial, marine, air and space transport within the confines of shaft power N td = 0.01…10 kW. In this paper we propose a new approach to the development of surrogate models for evaluating the integrated efficiency of multistage ultra-low power impulse turbine with pressure stages. This method is based on the use of existing mathematical models of ultra-low power turbine stage efficiency and mass. It has been used in a method for selecting the rational parameters of two-stage axial ultra-low power turbine. The article describes the basic features of an algorithm for two-stage turbine parameters optimization and for efficiency criteria evaluating. Pledged mathematical models are intended for use at the preliminary design of turbine drive. The optimization method was tested at preliminary design of an air starter turbine. Validation was carried out by comparing the results of optimization calculations and numerical gas-dynamic simulation in the Ansys CFX package. The results indicate a sufficient accuracy of used surrogate models for axial two-stage turbine parameters selection

Integrated thermal and energy management of plug-in hybrid electric vehicles

NASA Astrophysics Data System (ADS)

Shams-Zahraei, Mojtaba; Kouzani, Abbas Z.; Kutter, Steffen; Bäker, Bernard

2012-10-01

In plug-in hybrid electric vehicles (PHEVs), the engine temperature declines due to reduced engine load and extended engine off period. It is proven that the engine efficiency and emissions depend on the engine temperature. Also, temperature influences the vehicle air-conditioner and the cabin heater loads. Particularly, while the engine is cold, the power demand of the cabin heater needs to be provided by the batteries instead of the waste heat of engine coolant. The existing energy management strategies (EMS) of PHEVs focus on the improvement of fuel efficiency based on hot engine characteristics neglecting the effect of temperature on the engine performance and the vehicle power demand. This paper presents a new EMS incorporating an engine thermal management method which derives the global optimal battery charge depletion trajectories. A dynamic programming-based algorithm is developed to enforce the charge depletion boundaries, while optimizing a fuel consumption cost function by controlling the engine power. The optimal control problem formulates the cost function based on two state variables: battery charge and engine internal temperature. Simulation results demonstrate that temperature and the cabin heater/air-conditioner power demand can significantly influence the optimal solution for the EMS, and accordingly fuel efficiency and emissions of PHEVs.

Energy systems research and development for petroleum refineries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, J.L.

1982-08-01

For the past several years, Exxon Reasearch and Engineering has carried out a specific RandD program aimed at improving refinery energy efficiency through optimization of energy systems. Energy systems include: steam/power systems, heat exchange systems including hot oil and hot water belts and fuel systems, as well as some of the processes. This paper will describe the three major thrusts of this program which are: development of methods to support Site Energy Survey activities; development of energy management methods; and energy system optimization, which includes development of consistent, realistic, economic incentives for energy system improvements. Project selection criteria will alsomore » be discussed. The technique of a site energy survey will also be described briefly.« less

Energy Systems Integration News | Energy Systems Integration Facility |

Science.gov Websites

for its novel approach to energy reduction. The ultra-efficient ESIF data center features a chiller "chips to bricks" approach to sustainability integrates the data center into the facility systems, rather than trying to optimize each in isolation. Key to the approach was collaboration with

Evaluating the quality of feed fats and oils and their effects on pig growth performance

USDA-ARS?s Scientific Manuscript database

Optimizing energy utilization efficiency of swine diets is essential because energy represents the greatest proportion of total diet cost. Various feed fats and oils, as well as other feed ingredients containing moderate amounts of lipid, provide significant amounts of energy to swine diets. However...

Varietal Variability for Cotton Ginning Efficiency

USDA-ARS?s Scientific Manuscript database

Energy consumption is one of the largest expenses of a cotton gin. In light of the rising cost of energy, all avenues should be exploited to optimize energy use in modern cotton gins. One option is to study genetic variability within the available germplasm to look for varieties that gin faster and ...

Design Optimization of an Electromagnetic Energy Harvester Backpack for Utilization of Human Walking Energy

NASA Astrophysics Data System (ADS)

Mullen, Christopher

Implementation of energy harvesting technology can provide a sustainable, remote power source for soldiers by reducing the battery weight and allowing them to stay in the field for longer periods of time. Among multiple energy conversion principles, electromagnetic induction can scavenge energy from wasted kinematic and vibration energy found from human motion. Hip displacement during human gait acts as a base excitation for an energy harvesting backpack system. The placement of a permanent magnet in this vibration environment results in relative motion of the magnet to the coil of copper wire, which induces an electric current. This current can be saved to a battery or capacitor bank installed on the backpack to be used to power electronic devices. The purpose of this research is to construct a reliable simulation model for an electromagnetic vibration energy harvester and use it for a multi-variable optimization algorithm to identify an optimal coil and magnet layout for highest power output. Key components of the coupled equations of motion such as the magnetic flux density and coil inductance are obtained using ANSYS multi-physics software or by measuring them. These components are fed into a harvester simulation model (e.g. coupled field equations of motion for the backpack harvester) that generates the electrical power output. The developed simulation model is verified with multiple case studies including an experimental test. Then the optimal design parameters in the simulation model (e.g., magnet layout, coil width, outer coil diameter, external load resistance) are identified for maximum power. Results from this study will pave the way for a more efficient energy harvesting backpack while providing better insight into the efficiency of magnet and coil layout for electromagnetic applications.

Optimization of output power and transmission efficiency of magnetically coupled resonance wireless power transfer system

NASA Astrophysics Data System (ADS)

Yan, Rongge; Guo, Xiaoting; Cao, Shaoqing; Zhang, Changgeng

2018-05-01

Magnetically coupled resonance (MCR) wireless power transfer (WPT) system is a promising technology in electric energy transmission. But, if its system parameters are designed unreasonably, output power and transmission efficiency will be low. Therefore, optimized parameters design of MCR WPT has important research value. In the MCR WPT system with designated coil structure, the main parameters affecting output power and transmission efficiency are the distance between the coils, the resonance frequency and the resistance of the load. Based on the established mathematical model and the differential evolution algorithm, the change of output power and transmission efficiency with parameters can be simulated. From the simulation results, it can be seen that output power and transmission efficiency of the two-coil MCR WPT system and four-coil one with designated coil structure are improved. The simulation results confirm the validity of the optimization method for MCR WPT system with designated coil structure.

High probability neurotransmitter release sites represent an energy efficient design

PubMed Central

Lu, Zhongmin; Chouhan, Amit K.; Borycz, Jolanta A.; Lu, Zhiyuan; Rossano, Adam J; Brain, Keith L.; Zhou, You; Meinertzhagen, Ian A.; Macleod, Gregory T.

2016-01-01

Nerve terminals contain multiple sites specialized for the release of neurotransmitters. Release usually occurs with low probability, a design thought to confer many advantages. High probability release sites are not uncommon but their advantages are not well understood. Here we test the hypothesis that high probability release sites represent an energy efficient design. We examined release site probabilities and energy efficiency at the terminals of two glutamatergic motor neurons synapsing on the same muscle fiber in Drosophila larvae. Through electrophysiological and ultrastructural measurements we calculated release site probabilities to differ considerably between terminals (0.33 vs. 0.11). We estimated the energy required to release and recycle glutamate from the same measurements. The energy required to remove calcium and sodium ions subsequent to nerve excitation was estimated through microfluorimetric and morphological measurements. We calculated energy efficiency as the number of glutamate molecules released per ATP molecule hydrolyzed, and high probability release site terminals were found to be more efficient (0.13 vs. 0.06). Our analytical model indicates that energy efficiency is optimal (~0.15) at high release site probabilities (~0.76). As limitations in energy supply constrain neural function, high probability release sites might ameliorate such constraints by demanding less energy. Energy efficiency can be viewed as one aspect of nerve terminal function, in balance with others, because high efficiency terminals depress significantly during episodic bursts of activity. PMID:27593375

Charging System Optimization of Triboelectric Nanogenerator for Water Wave Energy Harvesting and Storage.

PubMed

Yao, Yanyan; Jiang, Tao; Zhang, Limin; Chen, Xiangyu; Gao, Zhenliang; Wang, Zhong Lin

2016-08-24

Ocean waves are one of the most promising renewable energy sources for large-scope applications due to the abundant water resources on the earth. Triboelectric nanogenerator (TENG) technology could provide a new strategy for water wave energy harvesting. In this work, we investigated the charging characteristics of utilizing a wavy-structured TENG to charge a capacitor under direct water wave impact and under enclosed ball collision, by combination of theoretical calculations and experimental studies. The analytical equations of the charging characteristics were theoretically derived for the two cases, and they were calculated for various load capacitances, cycle numbers, and structural parameters such as compression deformation depth and ball size or mass. Under the direct water wave impact, the stored energy and maximum energy storage efficiency were found to be controlled by deformation depth, while the stored energy and maximum efficiency can be optimized by the ball size under the enclosed ball collision. Finally, the theoretical results were well verified by the experimental tests. The present work could provide strategies for improving the charging performance of TENGs toward effective water wave energy harvesting and storage.

On the hydrophilicity of electrodes for capacitive energy extraction

NASA Astrophysics Data System (ADS)

Lian, Cheng; Kong, Xian; Liu, Honglai; Wu, Jianzhong

2016-11-01

The so-called Capmix technique for energy extraction is based on the cyclic expansion of electrical double layers to harvest dissipative energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the electrical potentials for the charging and discharging processes, which must be matched with the pore characteristics of the electrode materials. While a number of recent studies have examined the effects of the electrode pore size and geometry on the capacitive energy extraction processes, there is little knowledge on how the surface properties of the electrodes affect the thermodynamic efficiency. In this work, we investigate the Capmix processes using the classical density functional theory for a realistic model of electrolyte solutions. The theoretical predictions allow us to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different surface hydrophobicity. In agreement with recent experiments, we find that the thermodynamic efficiency can be much improved by using most hydrophilic electrodes.

On the hydrophilicity of electrodes for capacitive energy extraction

DOE PAGES

Lian, Cheng; East China Univ. of Science and Technology, Shanghai; Kong, Xian; ...

2016-09-14

The so-called Capmix technique for energy extraction is based on the cyclic expansion of electrical double layers to harvest dissipative energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the electrical potentials for the charging and discharging processes, which must be matched with the pore characteristics of the electrode materials. While a number of recent studies have examined the effects of the electrode pore size and geometry on the capacitive energy extraction processes, there is little knowledge on how the surface properties of the electrodes affect the thermodynamic efficiency. In thismore » paper, we investigate the Capmix processes using the classical density functional theory for a realistic model of electrolyte solutions. The theoretical predictions allow us to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different surface hydrophobicity. Finally, in agreement with recent experiments, we find that the thermodynamic efficiency can be much improved by using most hydrophilic electrodes.« less

An Energy Balanced and Lifetime Extended Routing Protocol for Underwater Sensor Networks.

PubMed

Wang, Hao; Wang, Shilian; Zhang, Eryang; Lu, Luxi

2018-05-17

Energy limitation is an adverse problem in designing routing protocols for underwater sensor networks (UWSNs). To prolong the network lifetime with limited battery power, an energy balanced and efficient routing protocol, called energy balanced and lifetime extended routing protocol (EBLE), is proposed in this paper. The proposed EBLE not only balances traffic loads according to the residual energy, but also optimizes data transmissions by selecting low-cost paths. Two phases are operated in the EBLE data transmission process: (1) candidate forwarding set selection phase and (2) data transmission phase. In candidate forwarding set selection phase, nodes update candidate forwarding nodes by broadcasting the position and residual energy level information. The cost value of available nodes is calculated and stored in each sensor node. Then in data transmission phase, high residual energy and relatively low-cost paths are selected based on the cost function and residual energy level information. We also introduce detailed analysis of optimal energy consumption in UWSNs. Numerical simulation results on a variety of node distributions and data load distributions prove that EBLE outperforms other routing protocols (BTM, BEAR and direct transmission) in terms of network lifetime and energy efficiency.

Wireless sensor and actuator networks for lighting energy efficiency and user satisfaction

NASA Astrophysics Data System (ADS)

Wen, Yao-Jung

Buildings consume more than one third of the primary energy generated in the U.S., and lighting alone accounts for approximately 30% of the energy usage in commercial buildings. As the largest electricity consumer of all building electrical systems, lighting harbors the greatest potential for energy savings in the commercial sector. Fifty percent of current energy consumption could be reduced with energy-efficient lighting management strategies. While commercial products do exist, they are poorly received due to exorbitant retrofitting cost and unsatisfactory performance. As a result, most commercial buildings, especially legacy buildings, have not taken advantage of the opportunity to generate savings from lighting. The emergence of wireless sensor and actuator network (WSAN) technologies presents an alternative that circumvents costly rewiring and promises better performance than existing commercial lighting systems. The goal of this dissertation research is to develop a framework for wireless-networked lighting systems with increased cost effectiveness, energy efficiency, and user satisfaction. This research is realized through both theoretical developments and implementations. The theoretical research aims at developing techniques for harnessing WSAN technologies to lighting hardware and control strategies. Leveraging redundancy, a sensor validation and fusion algorithm is developed for extracting pertinent lighting information from the disturbance-prone desktop-mounted photosensors. An adaptive sensing strategy optimizes the timing of data acquisition and power-hungry wireless transmission of sensory feedback in real-time lighting control. Exploiting the individual addressability of wireless-enabled luminaires, a lighting optimization algorithm is developed to create the optimal lighting that minimizes energy usage while satisfying occupants' diverse lighting preferences. The wireless-networked lighting system was implemented and tested in a number of real-life settings. A human subject study conducted in a private office concluded that the research system was competitive with the commercial lighting system with much fewer retrofitting requirements. The system implemented in a shared-space office realized a self-configuring mesh network with wireless photosensors and light actuators, and demonstrated a 50% energy savings and increased performance when harvesting daylight through windows is possible. The cost analysis revealed a reasonable payback period after the system is optimized for commercialization and confirms the marketing feasibility.

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

PubMed Central

Ahmed, Gulnaz; Zou, Jianhua; Zhao, Xi; Sadiq Fareed, Mian Muhammad

2017-01-01

The longer network lifetime of Wireless Sensor Networks (WSNs) is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs) selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED) clustering, Artificial Bee Colony (ABC), Zone Based Routing (ZBR), and Centralized Energy Efficient Clustering (CEEC) using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps) greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput. PMID:28241492

Optimal PGU operation strategy in CHP systems

NASA Astrophysics Data System (ADS)

Yun, Kyungtae

Traditional power plants only utilize about 30 percent of the primary energy that they consume, and the rest of the energy is usually wasted in the process of generating or transmitting electricity. On-site and near-site power generation has been considered by business, labor, and environmental groups to improve the efficiency and the reliability of power generation. Combined heat and power (CHP) systems are a promising alternative to traditional power plants because of the high efficiency and low CO2 emission achieved by recovering waste thermal energy produced during power generation. A CHP operational algorithm designed to optimize operational costs must be relatively simple to implement in practice such as to minimize the computational requirements from the hardware to be installed. This dissertation focuses on the following aspects pertaining the design of a practical CHP operational algorithm designed to minimize the operational costs: (a) real-time CHP operational strategy using a hierarchical optimization algorithm; (b) analytic solutions for cost-optimal power generation unit operation in CHP Systems; (c) modeling of reciprocating internal combustion engines for power generation and heat recovery; (d) an easy to implement, effective, and reliable hourly building load prediction algorithm.

Energy efficient motion control of the electric bus on route

NASA Astrophysics Data System (ADS)

Kotiev, G. O.; Butarovich, D. O.; Kositsyn, B. B.

2018-02-01

At present, the urgent problem is the reduction of energy costs of urban motor transport. The article proposes a method of solving this problem by developing an energy-efficient law governing the movement of an electric bus along a city route. To solve this problem, an algorithm is developed based on the dynamic programming method. The proposed method allows you to take into account the constraints imposed on the phase coordinates, control action, as well as on the time of the route. In the course of solving the problem, the model of rectilinear motion of an electric bus on a horizontal reference surface is considered, taking into account the assumptions that allow it to be adapted for the implementation of the method. For the formation of a control action in the equations of motion dynamics, an algorithm for changing the traction / braking torque on the wheels of an electric bus is considered, depending on the magnitude of the control parameter and the speed of motion. An optimal phase trajectory was obtained on a selected section of the road for the prototype of an electric bus. The article presents the comparison of simulation results obtained with the optimal energy efficient control law with the results obtained by a test driver. The comparison proved feasibility of the energy efficient control law for the automobile city electric transport.

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brigantic, Robert T.; Papatyi, Anthony F.; Perkins, Casey J.

This report summarizes a study and corresponding model development conducted in support of the United States Pacific Command (USPACOM) as part of the Federal Energy Management Program (FEMP) American Reinvestment and Recovery Act (ARRA). This research was aimed at developing a mathematical programming framework and accompanying optimization methodology in order to simultaneously evaluate energy efficiency (EE) and renewable energy (RE) opportunities. Once developed, this research then demonstrated this methodology at a USPACOM installation - Camp H.M. Smith, Hawaii. We believe this is the first time such an integrated, joint EE and RE optimization methodology has been constructed and demonstrated.

Human-motion energy harvester for autonomous body area sensors

NASA Astrophysics Data System (ADS)

Geisler, M.; Boisseau, S.; Perez, M.; Gasnier, P.; Willemin, J.; Ait-Ali, I.; Perraud, S.

2017-03-01

This paper reports on a method to optimize an electromagnetic energy harvester converting the low-frequency body motion and aimed at powering wireless body area sensors. This method is based on recorded accelerations, and mechanical and transduction models that enable an efficient joint optimization of the structural parameters. An optimized prototype of 14.8 mmØ × 52 mm, weighting 20 g, has generated up to 4.95 mW in a resistive load when worn at the arm during a run, and 6.57 mW when hand-shaken. Among the inertial electromagnetic energy harvesters reported so far, this one exhibits one of the highest power densities (up to 730 μW cm-3). The energy harvester was finally used to power a bluetooth low energy wireless sensor node with accelerations measurements at 25 Hz.

Hierarchical fuzzy control of low-energy building systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Zhen; Dexter, Arthur

2010-04-15

A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profilemore » can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort. (author)« less

Analyzing the Efficiency of Introduction of the Intermittent Heating Mode

NASA Astrophysics Data System (ADS)

Anisimova, E.; Shcherbak, A.

2017-11-01

The efficiency of introduction of an optimal intermittent heating mode for a service center building in Chelyabinsk is estimated. The optimal intermittent heating mode ensures heat energy saving while maintaining the required microclimate parameters. The graphical dependencies of the amount of heat energy saving on the heat retention of the building and the outdoor air temperature are shown. The fundamental formulas which were the basis for calculating the periods of cooling, warming and expenditures of heat energy for the two heating modes are given. The literature on the issue is reviewed, the main points, advantages and disadvantages in the works of both Russian and foreign authors are revealed. The calculation was carried out in compliance with the modern state standards and regulatory documents. The capital costs of a system construction with an intermittent heating mode are determined.

Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition.

PubMed

Janko, Vito; Luštrek, Mitja

2017-12-29

The recognition of the user's context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system's energy expenditure and the system's accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy.

Energy conversion in isothermal nonlinear irreversible processes - struggling for higher efficiency

NASA Astrophysics Data System (ADS)

Ebeling, W.; Feistel, R.

2017-06-01

First we discuss some early work of Ulrike Feudel on structure formation in nonlinear reactions including ions and the efficiency of the conversion of chemical into electrical energy. Then we give some survey about isothermal energy conversion from chemical to higher forms of energy like mechanical, electrical and ecological energy. Isothermal means here that there are no temperature gradients within the model systems. We consider examples of energy conversion in several natural processes and in some devices like fuel cells. Further, as an example, we study analytically the dynamics and efficiency of a simple "active circuit" converting chemical into electrical energy and driving currents which is roughly modeling fuel cells. Finally we investigate an analogous ecological system of Lotka-Volterra type consisting of an "active species" consuming some passive "chemical food". We show analytically for both these models that the efficiency increases with the load, reaches values higher then 50 percent in a narrow regime of optimal load and goes beyond some maximal load abruptly to zero.

Energy Efficiency Roadmap for Uganda, Making Energy Efficiency Count. Executive Summary

DOE Office of Scientific and Technical Information (OSTI.GOV)

de la Rue du Can, Stephane; Pudleiner, David; Jones, David

Like many countries in Sub-Saharan Africa, Uganda has focused its energy sector investments largely on increasing energy access by increasing energy supply. The links between energy efficiency and energy access, the importance of energy efficiency in new energy supply, and the multiple benefits of energy efficiency for the level and quality of energy available, have been largely overlooked. Implementing energy efficiency in parallel with expanding both the electricity grid and new clean energy generation reduces electricity demand and helps optimize the power supply so that it can serve more customers reliably at minimum cost. Ensuring efficient appliances are incorporated intomore » energy access efforts provides improved energy services to customers. Energy efficiency is an important contributor to access to modern energy. This Energy Efficiency Roadmap for Uganda (Roadmap) is a response to the important role that electrical energy efficiency can play in meeting Uganda’s energy goals. Power Africa and the United Nations Sustainable Energy for All (SEforALL) initiatives collaborated with more than 24 stakeholders in Uganda to develop this document. The document estimates that if the most efficient technologies on the market were adopted, 2,224 gigawatt hours could be saved in 2030 across all sectors, representing 31% of the projected load. This translates into 341 megawatts of peak demand reductions, energy access to an additional 6 million rural customers and reduction of carbon dioxide emissions by 10.6 million tonnes in 2030. The Roadmap also finds that 91% of this technical potential is cost-effective, and 47% is achievable under conservative assumptions. The Roadmap prioritizes recommendations for implementing energy efficiency and maximizing benefits to meet the goals and priorities established in Uganda’s 2015 SEforALL Action Agenda. One important step is to create and increase demand for efficiency through long-term enabling policies and financial incentives combined with development of technical expertise in the labor force to allow for the promotion of new business models, such as energy service companies. A combination of enabling policies, financial schemes, regulations, enforcement, and skill development are needed to open the energy efficiency market.« less

Synchronous Firefly Algorithm for Cluster Head Selection in WSN.

PubMed

Baskaran, Madhusudhanan; Sadagopan, Chitra

2015-01-01

Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH) offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC.

Estimating returns to scale and scale efficiency for energy consuming appliances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blum, Helcio; Okwelum, Edson O.

Energy consuming appliances accounted for over 40% of the energy use and $17 billion in sales in the U.S. in 2014. Whether such amounts of money and energy were optimally combined to produce household energy services is not straightforwardly determined. The efficient allocation of capital and energy to provide an energy service has been previously approached, and solved with Data Envelopment Analysis (DEA) under constant returns to scale. That approach, however, lacks the scale dimension of the problem and may restrict the economic efficient models of an appliance available in the market when constant returns to scale does not hold.more » We expand on that approach to estimate returns to scale for energy using appliances. We further calculate DEA scale efficiency scores for the technically efficient models that comprise the economic efficient frontier of the energy service delivered, under different assumptions of returns to scale. We then apply this approach to evaluate dishwashers available in the market in the U.S. Our results show that (a) for the case of dishwashers scale matters, and (b) the dishwashing energy service is delivered under non-decreasing returns to scale. The results further demonstrate that this method contributes to increase consumers’ choice of appliances.« less

Experimental verification and optimization of a linear electromagnetic energy harvesting device

NASA Astrophysics Data System (ADS)

Mullen, Christopher; Lee, Soobum

2017-04-01

Implementation of energy harvesting technology can provide a sustainable, remote power source for soldiers by reducing the battery weight and allowing them to stay in the field for longer periods of time. Among multiple energy conversion principles, electromagnetic induction can scavenge energy from wasted kinematic and vibration energy found from human motion. Hip displacement during human gait acts as a base excitation for an energy harvesting backpack system. The placement of a permanent magnet in this vibration environment results in relative motion of the magnet to the coil of copper wire, which induces an electric current. This current can be saved to a battery or capacitor bank installed on the backpack to be used to power electronic devices. The purpose of this research is to construct a reliable simulation model for an electromagnetic vibration energy harvester and use it for a multi-variable optimization algorithm to identify an optimal coil and magnet layout for highest power output. Key components of the coupled equations of motion such as the magnetic flux density and coil inductance are obtained using ANSYS multi-physics software or by measuring them. These components are fed into a harvester simulation model (e.g. coupled field equations of motion for the backpack harvester) that generates the electrical power output. The developed simulation model is verified with a case study including an experimental test. Then the optimal design parameters in the simulation model (e.g., magnet layout, coil width, outer coil diameter, external load resistance) are identified for maximum power. Results from this study will pave the way for a more efficient energy harvesting backpack while providing better insight into the efficiency of magnet and coil layout for electromagnetic applications.

Large size biogas-fed Solid Oxide Fuel Cell power plants with carbon dioxide management: Technical and economic optimization

NASA Astrophysics Data System (ADS)

Curletti, F.; Gandiglio, M.; Lanzini, A.; Santarelli, M.; Maréchal, F.

2015-10-01

This article investigates the techno-economic performance of large integrated biogas Solid Oxide Fuel Cell (SOFC) power plants. Both atmospheric and pressurized operation is analysed with CO2 vented or captured. The SOFC module produces a constant electrical power of 1 MWe. Sensitivity analysis and multi-objective optimization are the mathematical tools used to investigate the effects of Fuel Utilization (FU), SOFC operating temperature and pressure on the plant energy and economic performances. FU is the design variable that most affects the plant performance. Pressurized SOFC with hybridization with a gas turbine provides a notable boost in electrical efficiency. For most of the proposed plant configurations, the electrical efficiency ranges in the interval 50-62% (LHV biogas) when a trade-off of between energy and economic performances is applied based on Pareto charts obtained from multi-objective plant optimization. The hybrid SOFC is potentially able to reach an efficiency above 70% when FU is 90%. Carbon capture entails a penalty of more 10 percentage points in pressurized configurations mainly due to the extra energy burdens of captured CO2 pressurization and oxygen production and for the separate and different handling of the anode and cathode exhausts and power recovery from them.

QM/MM Geometry Optimization on Extensive Free-Energy Surfaces for Examination of Enzymatic Reactions and Design of Novel Functional Properties of Proteins.

PubMed

Hayashi, Shigehiko; Uchida, Yoshihiro; Hasegawa, Taisuke; Higashi, Masahiro; Kosugi, Takahiro; Kamiya, Motoshi

2017-05-05

Many remarkable molecular functions of proteins use their characteristic global and slow conformational dynamics through coupling of local chemical states in reaction centers with global conformational changes of proteins. To theoretically examine the functional processes of proteins in atomic detail, a methodology of quantum mechanical/molecular mechanical (QM/MM) free-energy geometry optimization is introduced. In the methodology, a geometry optimization of a local reaction center is performed with a quantum mechanical calculation on a free-energy surface constructed with conformational samples of the surrounding protein environment obtained by a molecular dynamics simulation with a molecular mechanics force field. Geometry optimizations on extensive free-energy surfaces by a QM/MM reweighting free-energy self-consistent field method designed to be variationally consistent and computationally efficient have enabled examinations of the multiscale molecular coupling of local chemical states with global protein conformational changes in functional processes and analysis and design of protein mutants with novel functional properties.

QM/MM Geometry Optimization on Extensive Free-Energy Surfaces for Examination of Enzymatic Reactions and Design of Novel Functional Properties of Proteins

NASA Astrophysics Data System (ADS)

Hayashi, Shigehiko; Uchida, Yoshihiro; Hasegawa, Taisuke; Higashi, Masahiro; Kosugi, Takahiro; Kamiya, Motoshi

2017-05-01

Many remarkable molecular functions of proteins use their characteristic global and slow conformational dynamics through coupling of local chemical states in reaction centers with global conformational changes of proteins. To theoretically examine the functional processes of proteins in atomic detail, a methodology of quantum mechanical/molecular mechanical (QM/MM) free-energy geometry optimization is introduced. In the methodology, a geometry optimization of a local reaction center is performed with a quantum mechanical calculation on a free-energy surface constructed with conformational samples of the surrounding protein environment obtained by a molecular dynamics simulation with a molecular mechanics force field. Geometry optimizations on extensive free-energy surfaces by a QM/MM reweighting free-energy self-consistent field method designed to be variationally consistent and computationally efficient have enabled examinations of the multiscale molecular coupling of local chemical states with global protein conformational changes in functional processes and analysis and design of protein mutants with novel functional properties.

Optimal mix of renewable power generation in the MENA region as a basis for an efficient electricity supply to europe

NASA Astrophysics Data System (ADS)

Alhamwi, Alaa; Kleinhans, David; Weitemeyer, Stefan; Vogt, Thomas

2014-12-01

Renewable Energy sources are gaining importance in the Middle East and North Africa (MENA) region. The purpose of this study is to quantify the optimal mix of renewable power generation in the MENA region, taking Morocco as a case study. Based on hourly meteorological data and load data, a 100% solar-plus-wind only scenario for Morocco is investigated. For the optimal mix analyses, a mismatch energy modelling approach is adopted with the objective to minimise the required storage capacities. For a hypothetical Moroccan energy supply system which is entirely based on renewable energy sources, our results show that the minimum storage capacity is achieved at a share of 63% solar and 37% wind power generations.

The importance of geospatial data to calculate the optimal distribution of renewable energies

NASA Astrophysics Data System (ADS)

Díaz, Paula; Masó, Joan

2013-04-01

Specially during last three years, the renewable energies are revolutionizing the international trade while they are geographically diversifying markets. Renewables are experiencing a rapid growth in power generation. According to REN21 (2012), during last six years, the total renewables capacity installed grew at record rates. In 2011, the EU raised its share of global new renewables capacity till 44%. The BRICS nations (Brazil, Russia, India and China) accounted for about 26% of the total global. Moreover, almost twenty countries in the Middle East, North Africa, and sub-Saharan Africa have currently active markets in renewables. The energy return ratios are commonly used to calculate the efficiency of the traditional energy sources. The Energy Return On Investment (EROI) compares the energy returned for a certain source and the energy used to get it (explore, find, develop, produce, extract, transform, harvest, grow, process, etc.). These energy return ratios have demonstrated a general decrease of efficiency of the fossil fuels and gas. When considering the limitations of the quantity of energy produced by some sources, the energy invested to obtain them and the difficulties of finding optimal locations for the establishment of renewables farms (e.g. due to an ever increasing scarce of appropriate land) the EROI becomes relevant in renewables. A spatialized EROI, which uses variables with spatial distribution, enables the optimal position in terms of both energy production and associated costs. It is important to note that the spatialized EROI can be mathematically formalized and calculated the same way for different locations in a reproducible way. This means that having established a concrete EROI methodology it is possible to generate a continuous map that will highlight the best productive zones for renewable energies in terms of maximum energy return at minimum cost. Relevant variables to calculate the real energy invested are the grid connections between production and consumption, transportation loses and efficiency of the grid. If appropriate, the spatialized EROI analysis could include any indirect costs that the source of energy might produce, such as visual impacts, food market impacts and land price. Such a spatialized study requires GIS tools to compute operations using both spatial relations like distances and frictions, and topological relations like connectivity, not easy to consider in the way that EROI is currently calculated. In a broader perspective, by applying the EROI to various energy sources, a comparative analysis of the efficiency to obtain different source can be done in a quantitative way. The increase in energy investment is also accompanied by the increase of manufactures and policies. Further efforts will be necessary in the coming years to provide energy access through smart grids and to determine the efficient areas in terms of cost of production and energy returned on investment. The authors present the EROI as a reliable solution to address the input and output energy relationship and increase the efficiency in energy investment considering the appropriate geospatial variables. The spatialized EROI can be a useful tool to consider by decision makers when designing energy policies and programming energy funds, because it is an objective demonstration of which energy sources are more convenient in terms of costs and efficiency.

Energy Efficient Image/Video Data Transmission on Commercial Multi-Core Processors

PubMed Central

Lee, Sungju; Kim, Heegon; Chung, Yongwha; Park, Daihee

2012-01-01

In transmitting image/video data over Video Sensor Networks (VSNs), energy consumption must be minimized while maintaining high image/video quality. Although image/video compression is well known for its efficiency and usefulness in VSNs, the excessive costs associated with encoding computation and complexity still hinder its adoption for practical use. However, it is anticipated that high-performance handheld multi-core devices will be used as VSN processing nodes in the near future. In this paper, we propose a way to improve the energy efficiency of image and video compression with multi-core processors while maintaining the image/video quality. We improve the compression efficiency at the algorithmic level or derive the optimal parameters for the combination of a machine and compression based on the tradeoff between the energy consumption and the image/video quality. Based on experimental results, we confirm that the proposed approach can improve the energy efficiency of the straightforward approach by a factor of 2∼5 without compromising image/video quality. PMID:23202181

An Analysis of the DER Adoption Climate in Japan UsingOptimization Results for Prototype Buildings with U.S. Comparisons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2006-06-16

This research demonstrates economically optimal distributedenergy resource (DER) system choice using the DER choice and operationsoptimization program, the Distributed Energy Resources Customer AdoptionModel (DER-CAM). DER-CAM finds the optimal combination of installedequipment given prevailing utility tariffs and fuel prices, siteelectrical and thermal loads (including absorption cooling), and a menuof available equipment. It provides a global optimization, albeitidealized, that shows how site useful energy loads can be served atminimum cost. Five prototype Japanese commercial buildings are examinedand DER-CAM is applied to select the economically optimal DER system foreach. Based on the optimization results, energy and emission reductionsare evaluated. Significant decreases in fuelmore » consumption, carbonemissions, and energy costs were seen in the DER-CAM results. Savingswere most noticeable in the prototype sports facility, followed by thehospital, hotel, and office building. Results show that DER with combinedheat and power equipment is a promising efficiency and carbon mitigationstrategy, but that precise system design is necessary. Furthermore, aJapan-U.S. comparison study of policy, technology, and utility tariffsrelevant to DER installation is presented.« less

Realizing Efficient Energy Harvesting from Organic Photovoltaic Cells

NASA Astrophysics Data System (ADS)

Zou, Yunlong

Organic photovoltaic cells (OPVs) are emerging field of research in renewable energy. The development of OPVs in recent years has made this technology viable for many niche applications. In order to realize widespread application however, the power conversion efficiency requires further improvement. The efficiency of an OPV depends on the short-circuit current density (JSC), open-circuit voltage (VOC) and fill factor (FF). For state-of-the-art devices, JSC is mostly optimized with the application of novel low-bandgap materials and a bulk heterojunction device architecture (internal quantum efficiency approaching 100%). The remaining limiting factors are the low VOC and FF. This work focuses on overcoming these bottlenecks for improved efficiency. Temperature dependent measurements of device performance are used to examine both charge transfer and exciton ionization process in OPVs. The results permit an improved understanding of the intrinsic limit for VOC in various device architectures and provide insight on device operation. Efforts have also been directed at engineering device architecture for optimized FF, realizing a very high efficiency of 8% for vapor deposited small molecule OPVs. With collaborators, new molecules with tailored desired energy levels are being designed for further improvements in efficiency. A new type of hybrid organic-inorganic perovskite material is also included in this study. By addressing processing issues and anomalous hysteresis effects, a very high efficiency of 19.1% is achieved. Moving forward, topics including engineering film crystallinity, exploring tandem architectures and understanding degradation mechanisms will further push OPVs toward broad commercialization.

Dynamic analysis of concentrated solar supercritical CO2-based power generation closed-loop cycle

DOE PAGES

Osorio, Julian D.; Hovsapian, Rob; Ordonez, Juan C.

2016-01-01

Here, the dynamic behavior of a concentrated solar power (CSP) supercritical CO 2 cycle is studied under different seasonal conditions. The system analyzed is composed of a central receiver, hot and cold thermal energy storage units, a heat exchanger, a recuperator, and multi-stage compression-expansion subsystems with intercoolers and reheaters between compressors and turbines respectively. Energy models for each component of the system are developed in order to optimize operating and design parameters such as mass flow rate, intermediate pressures and the effective area of the recuperator to lead to maximum efficiency. Our results show that the parametric optimization leads themore » system to a process efficiency of about 21 % and a maximum power output close to 1.5 MW. The thermal energy storage allows the system to operate for several hours after sunset. This operating time is approximately increased from 220 to 480 minutes after optimization. The hot and cold thermal energy storage also lessens the temperature fluctuations by providing smooth changes of temperatures at the turbines and compressors inlets. Our results indicate that concentrated solar systems using supercritical CO 2 could be a viable alternative to satisfying energy needs in desert areas with scarce water and fossil fuel resources.« less

Optimization of Wastewater Lift Stations for Reduction of Energy Usage and Greenhouse Gas Emissions (WERF Report INFR3R11)

EPA Science Inventory

One of the major contributions of Greenhouse Gas (GHG) emissions from water resource recovery facilities results from the energy used by the pumping regime of the lift stations. This project demonstrated an energy-efficient control method of lift station system operation that uti...

Controlling dielectric and relaxor-ferroelectric properties for energy storage by tuning Pb0.92La0.08Zr0.52Ti0.48O3 film thickness.

PubMed

Brown, Emery; Ma, Chunrui; Acharya, Jagaran; Ma, Beihai; Wu, Judy; Li, Jun

2014-12-24

The energy storage properties of Pb0.92La0.08Zr0.52Ti0.48O3 (PLZT) films grown via pulsed laser deposition were evaluated at variable film thickness of 125, 250, 500, and 1000 nm. These films show high dielectric permittivity up to ∼1200. Cyclic I-V measurements were used to evaluate the dielectric properties of these thin films, which not only provide the total electric displacement, but also separate contributions from each of the relevant components including electric conductivity (D1), dielectric capacitance (D2), and relaxor-ferroelectric domain switching polarization (P). The results show that, as the film thickness increases, the material transits from a linear dielectric to nonlinear relaxor-ferroelectric. While the energy storage per volume increases with the film thickness, the energy storage efficiency drops from ∼80% to ∼30%. The PLZT films can be optimized for different energy storage applications by tuning the film thickness to optimize between the linear and nonlinear dielectric properties and energy storage efficiency.

Controlling Dielectric and Relaxor-Ferroelectric Properties for Energy Storage by Tuning Pb 0.92La 0.08Zr 0.52Ti 0.48O 3 Film Thickness

DOE PAGES

Brown, Emery; Ma, Chunrui; Acharya, Jagaran; ...

2014-12-24

The energy storage properties of Pb 0.92La 0.08Zr 0.52Ti 0.48O 3 (PLZT) films grown via pulsed laser deposition were evaluated at variable film thickness of 125, 250, 500, and 1000 nm. These films show high dielectric permittivity up to ~1200. Cyclic I–V measurements were used to evaluate the dielectric properties of these thin films, which not only provide the total electric displacement, but also separate contributions from each of the relevant components including electric conductivity (D1), dielectric capacitance (D2), and relaxor-ferroelectric domain switching polarization (P). Our results show that, as the film thickness increases, the material transits from a linearmore » dielectric to nonlinear relaxor-ferroelectric. And while the energy storage per volume increases with the film thickness, the energy storage efficiency drops from ~80% to ~30%. The PLZT films can be optimized for different energy storage applications by tuning the film thickness to optimize between the linear and nonlinear dielectric properties and energy storage efficiency.« less

State-of-The-Art of Modeling Methodologies and Optimization Operations in Integrated Energy System

NASA Astrophysics Data System (ADS)

Zheng, Zhan; Zhang, Yongjun

2017-08-01

Rapid advances in low carbon technologies and smart energy communities are reshaping future patterns. Uncertainty in energy productions and demand sides are paving the way towards decentralization management. Current energy infrastructures could not meet with supply and consumption challenges, along with emerging environment and economic requirements. Integrated Energy System(IES) whereby electric power, natural gas, heating couples with each other demonstrates that such a significant technique would gradually become one of main comprehensive and optimal energy solutions with high flexibility, friendly renewables absorption and improving efficiency. In these global energy trends, we summarize this literature review. Firstly the accurate definition and characteristics of IES have been presented. Energy subsystem and coupling elements modeling issues are analyzed. It is pointed out that decomposed and integrated analysis methods are the key algorithms for IES optimization operations problems, followed by exploring the IES market mechanisms. Finally several future research tendencies of IES, such as dynamic modeling, peer-to-peer trading, couple market design, sare under discussion.

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

ASSESSMENT OF A WIND TURBINE INTELLIGENT CONTROLLER FOR ENHANCED ENERGY PRODUCTION AND POLLUTION REDUCTION

EPA Science Inventory

This study assessed the enhanced energy production which is possible when variable-speed wind turbines are electronically controlled by an intelligent controller for efficiency optimization and performance improvement. The control system consists of three fuzzy- logic controllers...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mittal, Sparsh; Zhang, Zhao

With each CMOS technology generation, leakage energy consumption has been dramatically increasing and hence, managing leakage power consumption of large last-level caches (LLCs) has become a critical issue in modern processor design. In this paper, we present EnCache, a novel software-based technique which uses dynamic profiling-based cache reconfiguration for saving cache leakage energy. EnCache uses a simple hardware component called profiling cache, which dynamically predicts energy efficiency of an application for 32 possible cache configurations. Using these estimates, system software reconfigures the cache to the most energy efficient configuration. EnCache uses dynamic cache reconfiguration and hence, it does not requiremore » offline profiling or tuning the parameter for each application. Furthermore, EnCache optimizes directly for the overall memory subsystem (LLC and main memory) energy efficiency instead of the LLC energy efficiency alone. The experiments performed with an x86-64 simulator and workloads from SPEC2006 suite confirm that EnCache provides larger energy saving than a conventional energy saving scheme. For single core and dual-core system configurations, the average savings in memory subsystem energy over a shared baseline configuration are 30.0% and 27.3%, respectively.« less

Surrogate-based optimization of hydraulic fracturing in pre-existing fracture networks

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Sun, Yunwei; Fu, Pengcheng; Carrigan, Charles R.; Lu, Zhiming; Tong, Charles H.; Buscheck, Thomas A.

2013-08-01

Hydraulic fracturing has been used widely to stimulate production of oil, natural gas, and geothermal energy in formations with low natural permeability. Numerical optimization of fracture stimulation often requires a large number of evaluations of objective functions and constraints from forward hydraulic fracturing models, which are computationally expensive and even prohibitive in some situations. Moreover, there are a variety of uncertainties associated with the pre-existing fracture distributions and rock mechanical properties, which affect the optimized decisions for hydraulic fracturing. In this study, a surrogate-based approach is developed for efficient optimization of hydraulic fracturing well design in the presence of natural-system uncertainties. The fractal dimension is derived from the simulated fracturing network as the objective for maximizing energy recovery sweep efficiency. The surrogate model, which is constructed using training data from high-fidelity fracturing models for mapping the relationship between uncertain input parameters and the fractal dimension, provides fast approximation of the objective functions and constraints. A suite of surrogate models constructed using different fitting methods is evaluated and validated for fast predictions. Global sensitivity analysis is conducted to gain insights into the impact of the input variables on the output of interest, and further used for parameter screening. The high efficiency of the surrogate-based approach is demonstrated for three optimization scenarios with different and uncertain ambient conditions. Our results suggest the critical importance of considering uncertain pre-existing fracture networks in optimization studies of hydraulic fracturing.

Building-to-Grid Integration through Commercial Building Portfolios Participating in Energy and Frequency Regulation Markets

NASA Astrophysics Data System (ADS)

Pavlak, Gregory S.

Building energy use is a significant contributing factor to growing worldwide energy demands. In pursuit of a sustainable energy future, commercial building operations must be intelligently integrated with the electric system to increase efficiency and enable renewable generation. Toward this end, a model-based methodology was developed to estimate the capability of commercial buildings to participate in frequency regulation ancillary service markets. This methodology was integrated into a supervisory model predictive controller to optimize building operation in consideration of energy prices, demand charges, and ancillary service revenue. The supervisory control problem was extended to building portfolios to evaluate opportunities for synergistic effect among multiple, centrally-optimized buildings. Simulation studies performed showed that the multi-market optimization was able to determine appropriate opportunities for buildings to provide frequency regulation. Total savings were increased by up to thirteen percentage points, depending on the simulation case. Furthermore, optimizing buildings as a portfolio achieved up to seven additional percentage points of savings, depending on the case. Enhanced energy and cost savings opportunities were observed by taking the novel perspective of optimizing building portfolios in multiple grid markets, motivating future pursuits of advanced control paradigms that enable a more intelligent electric grid.

BEopt-CA (Ex): A Tool for Optimal Integration of EE, DR and PV in Existing California Homes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christensen, Craig; Horowitz, Scott; Maguire, Jeff

2014-04-01

This project targeted the development of a software tool, BEopt-CA (Ex) (Building Energy Optimization Tool for California Existing Homes), that aims to facilitate balanced integration of energy efficiency (EE), demand response (DR), and photovoltaics (PV) in the residential retrofit1 market. The intent is to provide utility program managers and contractors in the EE/DR/PV marketplace with a means of balancing the integration of EE, DR, and PV

Strategies to Save 50% Site Energy in Grocery and General Merchandise Stores

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirsch, A.; Hale, E.; Leach, M.

2011-03-01

This paper summarizes the methodology and main results of two recently published Technical Support Documents. These reports explore the feasibility of designing general merchandise and grocery stores that use half the energy of a minimally code-compliant building, as measured on a whole-building basis. We used an optimization algorithm to trace out a minimum cost curve and identify designs that satisfy the 50% energy savings goal. We started from baseline building energy use and progressed to more energy-efficient designs by sequentially adding energy design measures (EDMs). Certain EDMs figured prominently in reaching the 50% energy savings goal for both building types:more » (1) reduced lighting power density; (2) optimized area fraction and construction of view glass or skylights, or both, as part of a daylighting system tuned to 46.5 fc (500 lux); (3) reduced infiltration with a main entrance vestibule or an envelope air barrier, or both; and (4) energy recovery ventilators, especially in humid and cold climates. In grocery stores, the most effective EDM, which was chosen for all climates, was replacing baseline medium-temperature refrigerated cases with high-efficiency models that have doors.« less

Electron-hole pairs generation rate estimation irradiated by isotope Nickel-63 in silicone using GEANT4

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Sidorov, V. G.; Zelenkov, P. V.; Khoroshko, A. Y.; Lelekov, A. T.

2015-10-01

To optimize parameters of beta-electrical converter of isotope Nickel-63 radiation, model of the distribution of EHP generation rate in semiconductor must be derived. By using Monte-Carlo methods in GEANT4 system with ultra-low energy electron physics models this distribution in silicon calculated and approximated with Gauss function. Maximal efficient isotope layer thickness and maximal energy efficiency of EHP generation were estimated.

Creation and Optimization of Novel Solar Cell Power via Bimaterial Piezoelectric MEMS Device

DTIC Science & Technology

2011-12-01

piezoelectric mechanical vibration energy harvesters ,” Integrated Ferroelectrics, vol. 71, pp. 121–160, 2005. [32] Y. C. Shu, I. C. Lien, “Efficiency of...energy conversion for a piezoelectric power harvesting system.” Journal of Micromechanics and Microengineering, vol. 16, pp. 2429–2438, 2006. [33] C. D...maximum efficiency for piezoelectric vibrations occurs at the natural, or resonant, frequency for the referenced material. If the alternative

Optimizing Hydropower Day-Ahead Scheduling for the Oroville-Thermalito Project

NASA Astrophysics Data System (ADS)

Veselka, T. D.; Mahalik, M.

2012-12-01

Under an award from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Water Power Program, a team of national laboratories is developing and demonstrating a suite of advanced, integrated analytical tools to assist managers and planners increase hydropower resources while enhancing the environment. As part of the project, Argonne National Laboratory is developing the Conventional Hydropower Energy and Environmental Systems (CHEERS) model to optimize day-ahead scheduling and real-time operations. We will present the application of CHEERS to the Oroville-Thermalito Project located in Northern California. CHEERS will aid California Department of Water Resources (CDWR) schedulers in making decisions about unit commitments and turbine-level operating points using a system-wide approach to increase hydropower efficiency and the value of power generation and ancillary services. The model determines schedules and operations that are constrained by physical limitations, characteristics of plant components, operational preferences, reliability, and environmental considerations. The optimization considers forebay and afterbay implications, interactions between cascaded power plants, turbine efficiency curves and rough zones, and operator preferences. CHEERS simultaneously considers over time the interactions among all CDWR power and water resources, hydropower economics, reservoir storage limitations, and a set of complex environmental constraints for the Thermalito Afterbay and Feather River habitats. Power marketers, day-ahead schedulers, and plant operators provide system configuration and detailed operational data, along with feedback on model design and performance. CHEERS is integrated with CDWR data systems to obtain historic and initial conditions of the system as the basis from which future operations are then optimized. Model results suggest alternative operational regimes that improve the value of CDWR resources to the grid while enhancing the environment and complying with water delivery obligations for non-power uses.

Optimal slew path planning for the Sino-French Space-based multiband astronomical Variable Objects Monitor mission

NASA Astrophysics Data System (ADS)

She, Yuchen; Li, Shuang

2018-01-01

The planning algorithm to calculate a satellite's optimal slew trajectory with a given keep-out constraint is proposed. An energy-optimal formulation is proposed for the Space-based multiband astronomical Variable Objects Monitor Mission Analysis and Planning (MAP) system. The innovative point of the proposed planning algorithm lies in that the satellite structure and control limitation are not considered as optimization constraints but are formulated into the cost function. This modification is able to relieve the burden of the optimizer and increases the optimization efficiency, which is the major challenge for designing the MAP system. Mathematical analysis is given to prove that there is a proportional mapping between the formulation and the satellite controller output. Simulations with different scenarios are given to demonstrate the efficiency of the developed algorithm.

Metabolic adaptation to weight loss: implications for the athlete

PubMed Central

2014-01-01

Optimized body composition provides a competitive advantage in a variety of sports. Weight reduction is common among athletes aiming to improve their strength-to-mass ratio, locomotive efficiency, or aesthetic appearance. Energy restriction is accompanied by changes in circulating hormones, mitochondrial efficiency, and energy expenditure that serve to minimize the energy deficit, attenuate weight loss, and promote weight regain. The current article reviews the metabolic adaptations observed with weight reduction and provides recommendations for successful weight reduction and long term reduced-weight maintenance in athletes. PMID:24571926

Biodiesel production from low cost and renewable feedstock

NASA Astrophysics Data System (ADS)

Gude, Veera G.; Grant, Georgene E.; Patil, Prafulla D.; Deng, Shuguang

2013-12-01

Sustainable biodiesel production should: a) utilize low cost renewable feedstock; b) utilize energy-efficient, nonconventional heating and mixing techniques; c) increase net energy benefit of the process; and d) utilize renewable feedstock/energy sources where possible. In this paper, we discuss the merits of biodiesel production following these criteria supported by the experimental results obtained from the process optimization studies. Waste cooking oil, non-edible (low-cost) oils (Jatropha curcas and Camelina Sativa) and algae were used as feedstock for biodiesel process optimization. A comparison between conventional and non-conventional methods such as microwaves and ultrasound was reported. Finally, net energy scenarios for different biodiesel feedstock options and algae are presented.

Selection of axial hydraulic turbines for low-head microhydropower plants

NASA Astrophysics Data System (ADS)

Šoukal, J.; Pochylý, F.; Varchola, M.; Parygin, A. G.; Volkov, A. V.; Khovanov, G. P.; Naumov, A. V.

2015-12-01

The creation of highly efficient hydroturbines for low-head microhydropower plants is considered. The use of uncontrolled (propeller) hydroturbines is a promising means of minimizing costs and the time for their recoupment. As an example, experimental results from Brno University of Technology are presented. The model axial hydraulic turbine produced by Czech specialists performs well. The rotor diameter of this turbine is 194 mm. In the design of the working rotor, ANSYS Fluent software is employed. Means of improving the efficiency of microhydropower plants by optimal selection of the turbine parameters in the early stages of design are outlined. The energy efficiency of the hydroturbine designed for use in a microhydropower plant may be assessed on the basis of the coefficient of energy utilization, which is a function of the total losses in all the pipeline elements and losses in the channel including the hydroturbine rotor. The limit on the coefficient of energy utilization in the pressure pipeline is the hydraulic analog of the Betz-Joukowsky limit, which is widely used in the design of wind generators. The proposed approach is experimentally verified at Moscow Power Engineering Institute. A model axial hydraulic turbine with four different rotors is designed for the research. The diameter of all four rotors is the same: 80 mm. The pipeline takes the form of a siphon. Working rotor R2, designed with parameter optimization, is characterized by the highest coefficient of energy utilization of the pressure pipeline and maximum efficiency. That confirms that the proposed approach is a promising means of maximizing the overall energy efficiency of the microhydropower plant.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

PubMed Central

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-01-01

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction. PMID:27399722

Efficient red organic electroluminescent devices by doping platinum(II) Schiff base emitter into two host materials with stepwise energy levels.

PubMed

Zhou, Liang; Kwok, Chi-Chung; Cheng, Gang; Zhang, Hongjie; Che, Chi-Ming

2013-07-15

In this work, organic electroluminescent (EL) devices with double light-emitting layers (EMLs) having stepwise energy levels were designed to improve the EL performance of a red-light-emitting platinum(II) Schiff base complex. A series of devices with single or double EML(s) were fabricated and characterized. Compared with single-EML devices, double-EML devices showed improved EL efficiency and brightness, attributed to better balance in carriers. In addition, the stepwise distribution in energy levels of host materials is instrumental in broadening the recombination zone, thus delaying the roll-off of EL efficiency. The highest EL current efficiency and power efficiency of 17.36 cd/A and 14.73 lm/W, respectively, were achieved with the optimized double-EML devices. At high brightness of 1000 cd/m², EL efficiency as high as 8.89 cd/A was retained.

mHealthMon: toward energy-efficient and distributed mobile health monitoring using parallel offloading.

PubMed

Ahnn, Jong Hoon; Potkonjak, Miodrag

2013-10-01

Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient's sensors is emerging, little effort has been investigated in an energy-efficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically designed as a global solution to optimization subproblems. This paper presents an attempt to decompose the very complex mobile health monitoring system whose layer in the system corresponds to decomposed subproblems, and interfaces between them are quantified as functions of the optimization variables in order to orchestrate the subproblems. We propose a distributed and energy-saving mobile health platform, called mHealthMon where mobile users publish/access sensor data via a cloud computing-based distributed P2P overlay network. The key objective is to satisfy the mobile health monitoring application's quality of service requirements by modeling each subsystem: mobile clients with medical sensors, wireless network medium, and distributed cloud services. By simulations based on experimental data, we present the proposed system can achieve up to 10.1 times more energy-efficient and 20.2 times faster compared to a standalone mobile health monitoring application, in various mobile health monitoring scenarios applying a realistic mobility model.

An Energy-Efficient Mobile Sink-Based Unequal Clustering Mechanism for WSNs.

PubMed

Gharaei, Niayesh; Abu Bakar, Kamalrulnizam; Mohd Hashim, Siti Zaiton; Hosseingholi Pourasl, Ali; Siraj, Mohammad; Darwish, Tasneem

2017-08-11

Network lifetime and energy efficiency are crucial performance metrics used to evaluate wireless sensor networks (WSNs). Decreasing and balancing the energy consumption of nodes can be employed to increase network lifetime. In cluster-based WSNs, one objective of applying clustering is to decrease the energy consumption of the network. In fact, the clustering technique will be considered effective if the energy consumed by sensor nodes decreases after applying clustering, however, this aim will not be achieved if the cluster size is not properly chosen. Therefore, in this paper, the energy consumption of nodes, before clustering, is considered to determine the optimal cluster size. A two-stage Genetic Algorithm (GA) is employed to determine the optimal interval of cluster size and derive the exact value from the interval. Furthermore, the energy hole is an inherent problem which leads to a remarkable decrease in the network's lifespan. This problem stems from the asynchronous energy depletion of nodes located in different layers of the network. For this reason, we propose Circular Motion of Mobile-Sink with Varied Velocity Algorithm (CM2SV2) to balance the energy consumption ratio of cluster heads (CH). According to the results, these strategies could largely increase the network's lifetime by decreasing the energy consumption of sensors and balancing the energy consumption among CHs.

Data of cost-optimal solutions and retrofit design methods for school renovation in a warm climate.

PubMed

Zacà, Ilaria; Tornese, Giuliano; Baglivo, Cristina; Congedo, Paolo Maria; D'Agostino, Delia

2016-12-01

"Efficient Solutions and Cost-Optimal Analysis for Existing School Buildings" (Paolo Maria Congedo, Delia D'Agostino, Cristina Baglivo, Giuliano Tornese, Ilaria Zacà) [1] is the paper that refers to this article. It reports the data related to the establishment of several variants of energy efficient retrofit measures selected for two existing school buildings located in the Mediterranean area. In compliance with the cost-optimal analysis described in the Energy Performance of Buildings Directive and its guidelines (EU, Directive, EU 244,) [2], [3], these data are useful for the integration of renewable energy sources and high performance technical systems for school renovation. The data of cost-efficient high performance solutions are provided in tables that are explained within the following sections. The data focus on the describe school refurbishment sector to which European policies and investments are directed. A methodological approach already used in previous studies about new buildings is followed (Baglivo Cristina, Congedo Paolo Maria, D׳Agostino Delia, Zacà Ilaria, 2015; IlariaZacà, Delia D'Agostino, Paolo Maria Congedo, Cristina Baglivo; Baglivo Cristina, Congedo Paolo Maria, D'Agostino Delia, Zacà Ilaria, 2015; Ilaria Zacà, Delia D'Agostino, Paolo Maria Congedo, Cristina Baglivo, 2015; Paolo Maria Congedo, Cristina Baglivo, IlariaZacà, Delia D'Agostino,2015) [4], [5], [6], [7], [8]. The files give the cost-optimal solutions for a kindergarten (REF1) and a nursery (REF2) school located in Sanarica and Squinzano (province of Lecce Southern Italy). The two reference buildings differ for construction period, materials and systems. The eleven tables provided contain data about the localization of the buildings, geometrical features and thermal properties of the envelope, as well as the energy efficiency measures related to walls, windows, heating, cooling, dhw and renewables. Output values of energy consumption, gas emission and costs are given for a financial and a macro-economic analysis. This data article provides 288 and 96 combinations for REF1 and REF2, respectively. The output values are obtained using the software ProCasaClima 2015v.2.0.

Dynamic Histogram Analysis To Determine Free Energies and Rates from Biased Simulations.

PubMed

Stelzl, Lukas S; Kells, Adam; Rosta, Edina; Hummer, Gerhard

2017-12-12

We present an algorithm to calculate free energies and rates from molecular simulations on biased potential energy surfaces. As input, it uses the accumulated times spent in each state or bin of a histogram and counts of transitions between them. Optimal unbiased equilibrium free energies for each of the states/bins are then obtained by maximizing the likelihood of a master equation (i.e., first-order kinetic rate model). The resulting free energies also determine the optimal rate coefficients for transitions between the states or bins on the biased potentials. Unbiased rates can be estimated, e.g., by imposing a linear free energy condition in the likelihood maximization. The resulting "dynamic histogram analysis method extended to detailed balance" (DHAMed) builds on the DHAM method. It is also closely related to the transition-based reweighting analysis method (TRAM) and the discrete TRAM (dTRAM). However, in the continuous-time formulation of DHAMed, the detailed balance constraints are more easily accounted for, resulting in compact expressions amenable to efficient numerical treatment. DHAMed produces accurate free energies in cases where the common weighted-histogram analysis method (WHAM) for umbrella sampling fails because of slow dynamics within the windows. Even in the limit of completely uncorrelated data, where WHAM is optimal in the maximum-likelihood sense, DHAMed results are nearly indistinguishable. We illustrate DHAMed with applications to ion channel conduction, RNA duplex formation, α-helix folding, and rate calculations from accelerated molecular dynamics. DHAMed can also be used to construct Markov state models from biased or replica-exchange molecular dynamics simulations. By using binless WHAM formulated as a numerical minimization problem, the bias factors for the individual states can be determined efficiently in a preprocessing step and, if needed, optimized globally afterward.

Army Net Zero: Energy Roadmap and Program Summary, Fiscal Year 2013 (Brochure)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

The U.S. Army (Army) partnered with the National Renewable Energy Laboratory (NREL) and the U.S. Army Corps of Engineers to assess opportunities for increasing energy security through improved energy efficiency and optimized renewable energy strategies at nine installations across the Army's portfolio. Referred to as Net Zero Energy Installations (NZEIs), these projects demonstrate and validate energy efficiency and renewable energy technologies with approaches that can be replicated across DOD and other Federal agencies, setting the stage for broad market adoption. This report summarizes the results of the energy project roadmaps developed by NREL, shows the progress each installation could makemore » in achieving Net Zero Energy by 2020, and presents lessons learned and unique challenges from each installation.« less

Multi-objective Optimization of a Solar Humidification Dehumidification Desalination Unit

NASA Astrophysics Data System (ADS)

Rafigh, M.; Mirzaeian, M.; Najafi, B.; Rinaldi, F.; Marchesi, R.

2017-11-01

In the present paper, a humidification-dehumidification desalination unit integrated with solar system is considered. In the first step mathematical model of the whole plant is represented. Next, taking into account the logical constraints, the performance of the system is optimized. On one hand it is desired to have higher energetic efficiency, while on the other hand, higher efficiency results in an increment in the required area for each subsystem which consequently leads to an increase in the total cost of the plant. In the present work, the optimum solution is achieved when the specific energy of the solar heater and also the areas of humidifier and dehumidifier are minimized. Due to the fact that considered objective functions are in conflict, conventional optimization methods are not applicable. Hence, multi objective optimization using genetic algorithm which is an efficient tool for dealing with problems with conflicting objectives has been utilized and a set of optimal solutions called Pareto front each of which is a tradeoff between the mentioned objectives is generated.

Energy-efficiency based classification of the manufacturing workstation

NASA Astrophysics Data System (ADS)

Frumuşanu, G.; Afteni, C.; Badea, N.; Epureanu, A.

2017-08-01

EU Directive 92/75/EC established for the first time an energy consumption labelling scheme, further implemented by several other directives. As consequence, nowadays many products (e.g. home appliances, tyres, light bulbs, houses) have an EU Energy Label when offered for sale or rent. Several energy consumption models of manufacturing equipments have been also developed. This paper proposes an energy efficiency - based classification of the manufacturing workstation, aiming to characterize its energetic behaviour. The concept of energy efficiency of the manufacturing workstation is defined. On this base, a classification methodology has been developed. It refers to specific criteria and their evaluation modalities, together to the definition & delimitation of energy efficiency classes. The energy class position is defined after the amount of energy needed by the workstation in the middle point of its operating domain, while its extension is determined by the value of the first coefficient from the Taylor series that approximates the dependence between the energy consume and the chosen parameter of the working regime. The main domain of interest for this classification looks to be the optimization of the manufacturing activities planning and programming. A case-study regarding an actual lathe classification from energy efficiency point of view, based on two different approaches (analytical and numerical) is also included.

Technical note: optimization for improved tube-loading efficiency in the dual-energy computed tomography coupled with balanced filter method.

PubMed

Saito, Masatoshi

2010-08-01

This article describes the spectral optimization of dual-energy computed tomography using balanced filters (bf-DECT) to reduce the tube loadings and dose by dedicating to the acquisition of electron density information, which is essential for treatment planning in radiotherapy. For the spectral optimization of bf-DECT, the author calculated the beam-hardening error and air kerma required to achieve a desired noise level in an electron density image of a 50-cm-diameter cylindrical water phantom. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimal combination of tube voltages was 80 kV/140 kV in conjunction with Tb/Hf and Bi/Mo filter pairs; this combination agrees with that obtained in a previous study [M. Saito, "Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method," Med. Phys. 36, 3631-3642 (2009)], although the thicknesses of the filters that yielded a minimum tube output were slightly different from those obtained in the previous study. The resultant tube loading of a low-energy scan of the present bf-DECT significantly decreased from 57.5 to 4.5 times that of a high-energy scan for conventional DECT. Furthermore, the air kerma of bf-DECT could be reduced to less than that of conventional DECT, while obtaining the same figure of merit for the measurement of electron density and effective atomic number. The tube-loading and dose efficiencies of bf-DECT were considerably improved by sacrificing the quality of the noise level in the images of effective atomic number.

IEEE 802.21 Assisted Seamless and Energy Efficient Handovers in Mixed Networks

NASA Astrophysics Data System (ADS)

Liu, Huaiyu; Maciocco, Christian; Kesavan, Vijay; Low, Andy L. Y.

Network selection is the decision process for a mobile terminal to handoff between homogeneous or heterogeneous networks. With multiple available networks, the selection process must evaluate factors like network services/conditions, monetary cost, system conditions, user preferences etc. In this paper, we investigate network selection using a cost function and information provided by IEEE 802.21. The cost function provides flexibility to balance different factors in decision making and our research is focused on improving both seamlessness and energy efficiency of handovers. Our solution is evaluated using real WiFi, WiMax, and 3G signal strength traces. The results show that appropriate networks were selected based on selection policies, handovers were triggered at optimal times to increase overall network connectivity as compared to traditional triggering schemes, while at the same time the energy consumption of multi-radio devices for both on-going operations as well as during handovers is optimized.

Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition †

PubMed Central

Janko, Vito

2017-01-01

The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy. PMID:29286301

Parametric and energy consumption optimization of Basic Red 2 removal by electrocoagulation/egg shell adsorption coupling using response surface methodology in a batch system.

PubMed

de Carvalho, Helder Pereira; Huang, Jiguo; Zhao, Meixia; Liu, Gang; Yang, Xinyu; Dong, Lili; Liu, Xingjuan

2016-01-01

In this study, response surface methodology (RSM) model was applied for optimization of Basic Red 2 (BR2) removal using electrocoagulation/eggshell (ES) coupling process in a batch system. Central composite design was used to evaluate the effects and interactions of process parameters including current density, reaction time, initial pH and ES dosage on the BR2 removal efficiency and energy consumption. The analysis of variance revealed high R(2) values (≥85%) indicating that the predictions of RSM models are adequately applicable for both responses. The optimum conditions when the dye removal efficiency of 93.18% and energy consumption of 0.840 kWh/kg were observed were 11.40 mA/cm(2) current density, 5 min and 3 s reaction time, 6.5 initial pH and 10.91 g/L ES dosage.

Energy efficiency in waste-to-energy and its relevance with regard to climate control.

PubMed

Ragossnig, Arne M; Wartha, Christian; Kirchner, Andreas

2008-02-01

This article focuses on systematically highlighting the ways to optimize waste-to-energy plants in terms of their energy efficiency as an indicator of the positive effect with regard to climate control. Potentials for increasing energy efficiency are identified and grouped into categories. The measures mentioned are illustrated by real-world examples. As an example, district cooling as a means for increasing energy efficiency in the district heating network of Vienna is described. Furthermore a scenario analysis shows the relevance of energy efficiency in waste management scenarios based on thermal treatment of waste with regard to climate control. The description is based on a model that comprises all relevant processes from the collection and transportation up to the thermal treatment of waste. The model has been applied for household-like commercial waste. The alternatives compared are a combined heat and power incinerator, which is being introduced in many places as an industrial utility boiler or in metropolitan areas where there is a demand for district heating and a classical municipal solid waste incinerator producing solely electrical power. For comparative purposes a direct landfilling scenario has been included in the scenario analysis. It is shown that the energy efficiency of thermal treatment facilities is crucial to the quantity of greenhouse gases emitted.

Recent advances in plasmonic dye-sensitized solar cells

NASA Astrophysics Data System (ADS)

Rho, Won-Yeop; Song, Da Hyun; Yang, Hwa-Young; Kim, Ho-Sub; Son, Byung Sung; Suh, Jung Sang; Jun, Bong-Hyun

2018-02-01

Dye-sensitized solar cells (DSSCs) are among the best devices in generating electrons from solar light energy due to their high efficiency, low-cost in processing and transparency in building integrated photovoltaics. There are several ways to improve their energy-conversion efficiency, such as increasing light harvesting and electron transport, of which plasmon and 3-dimensional nanostructures are greatly capable. We review recent advances in plasmonic effects which depend on optimizing sizes, shapes, alloy compositions and integration of metal nanoparticles. Different methods to integrate metal nanoparticles into 3-dimensional nanostructures are also discussed. This review presents a guideline for enhancing the energy-conversion efficiency of DSSCs by utilizing metal nanoparticles that are incorporated into 3-dimensional nanostructures.

Influence of the nozzle angle on refrigeration performance of a gas wave refrigerator

NASA Astrophysics Data System (ADS)

Liu, P.; Zhu, Y.; Wang, H.; Zhu, C.; Zou, J.; Wu, J.; Hu, D.

2017-05-01

A gas wave refrigerator (GWR) is a novel refrigerating device that refrigerates a medium by shock waves and expansion waves generated by gas pressure energy. In a typical GWR, the injection energy losses between the nozzle and the expansion tube are essential factors which influence the refrigeration efficiency. In this study, numerical simulations are used to analyze the underlying mechanism of the injection energy losses. The results of simulations show that the vortex loss, mixing energy loss, and oblique shock wave reflection loss are the main factors contributing to the injection energy losses in the expansion tube. Furthermore, the jet angle of the gas is found to dominate the injection energy losses. Therefore, the optimum jet angle is theoretically calculated based on the velocity triangle method. The value of the optimum jet angle is found to be 4^{circ }, 8^{circ }, and 12^{circ } when the refrigeration efficiency is the first-order, second-order, and third-order maximum value over all working ranges of jet frequency, respectively. Finally, a series of experiments are conducted with the jet angle ranging from -4^{circ } to 12^{circ } at a constant expansion ratio. The results indicate the optimal jet angle obtained by the experiments is in good agreement with the calculated value. The isentropic refrigeration efficiency increased by about 4 % after the jet angle was optimized.

Prediction of 4H-SiC betavoltaic microbattery characteristics based on practical Ni-63 sources.

PubMed

Gui, Gui; Zhang, Kan; Blanchard, James P; Ma, Zhenqiang

2016-01-01

We have investigated the performance of 4H-SiC betavoltaic microbatteries under exposure to the practical Ni-63 sources using the Monte Carlo method and Synopsys® Medici device simulator. A typical planar p-n junction betavoltaic device with the Ni-63 source of 20% purity on top is modeled in the simulation. The p-n junction structure includes a p+ layer, a p- layer, an n+ layer, and an n- layer. In order to obtain an accurate and valid predication, our simulations consider several practical factors, including isotope impurities, self-absorption, and full beta energy spectra. By simulating the effects of both the p-n junction configuration and the isotope source thickness on the battery output performance, we have achieved the optimal design of the device and maximum energy conversion efficiency. Our simulation results show that the energy conversion efficiency increases as the doping concentration and thickness of the p- layer increase, whereas it is independent of the total depth of the p-n junction. Furthermore, the energy conversion efficiency decreases as the thickness of the practical Ni-63 source increases, because of self-absorption in the isotope source. Therefore, we propose that a p-n junction betavoltaic cell with a thicker and heavily doped p- layer under exposure to a practical Ni-63 source with an appreciable thickness could produce the optimal energy conversion efficiency. Copyright © 2015 Elsevier Ltd. All rights reserved.

Up-conversion in rare-earth doped micro-particles applied to new emissive two-dimensional displays

NASA Astrophysics Data System (ADS)

Milliez, Anne Janet

Up-conversion (UC) in rare-earth co-doped fluorides to convert diode laser light in the near infrared to red, green and blue visible light is applied to make possible high performance emissive displays. The infrared-to-visible UC in the materials we study is a sequential form of non-linear two photon absorption in which a strong absorbing constituent absorbs two low energy photons and transfers this energy to another constituent which emits visible light. Some of the UC emitters' most appealing characteristics for displays are: a wide color gamut with very saturated colors, very high brightness operation without damage to the emitters, long lifetimes and efficiencies comparable to those of existing technologies. Other advantages include simplicity of fabrication, versatility of operating modes, and the potential for greatly reduced display weight and depth. Thanks to recent advances in material science and diode laser technology at the excitation wavelength, UC selected materials can be very efficient visible emitters. However, optimal UC efficiencies strongly depend on chosing proper operating conditions. In this thesis, we studied the conditions required for optimization. We demonstrated that high efficiency UC depends on high pump irradiance, low temperature and low scattering. With this understanding we can predict how to optimally use UC emitters in a wide range of applications. In particular, we showed how our very efficient UC emitters can be applied to make full color displays and very efficient white light sources.

Accelerated Enveloping Distribution Sampling: Enabling Sampling of Multiple End States while Preserving Local Energy Minima.

PubMed

Perthold, Jan Walther; Oostenbrink, Chris

2018-05-17

Enveloping distribution sampling (EDS) is an efficient approach to calculate multiple free-energy differences from a single molecular dynamics (MD) simulation. However, the construction of an appropriate reference-state Hamiltonian that samples all states efficiently is not straightforward. We propose a novel approach for the construction of the EDS reference-state Hamiltonian, related to a previously described procedure to smoothen energy landscapes. In contrast to previously suggested EDS approaches, our reference-state Hamiltonian preserves local energy minima of the combined end-states. Moreover, we propose an intuitive, robust and efficient parameter optimization scheme to tune EDS Hamiltonian parameters. We demonstrate the proposed method with established and novel test systems and conclude that our approach allows for the automated calculation of multiple free-energy differences from a single simulation. Accelerated EDS promises to be a robust and user-friendly method to compute free-energy differences based on solid statistical mechanics.

Energy latency tradeoffs for medium access and sleep scheduling in wireless sensor networks

NASA Astrophysics Data System (ADS)

Gang, Lu

Wireless sensor networks are expected to be used in a wide range of applications from environment monitoring to event detection. The key challenge is to provide energy efficient communication; however, latency remains an important concern for many applications that require fast response. The central thesis of this work is that energy efficient medium access and sleep scheduling mechanisms can be designed without necessarily sacrificing application-specific latency performance. We validate this thesis through results from four case studies that cover various aspects of medium access and sleep scheduling design in wireless sensor networks. Our first effort, DMAC, is to design an adaptive low latency and energy efficient MAC for data gathering to reduce the sleep latency. We propose staggered schedule, duty cycle adaptation, data prediction and the use of more-to-send packets to enable seamless packet forwarding under varying traffic load and channel contentions. Simulation and experimental results show significant energy savings and latency reduction while ensuring high data reliability. The second research effort, DESS, investigates the problem of designing sleep schedules in arbitrary network communication topologies to minimize the worst case end-to-end latency (referred to as delay diameter). We develop a novel graph-theoretical formulation, derive and analyze optimal solutions for the tree and ring topologies and heuristics for arbitrary topologies. The third study addresses the problem of minimum latency joint scheduling and routing (MLSR). By constructing a novel delay graph, the optimal joint scheduling and routing can be solved by M node-disjoint paths algorithm under multiple channel model. We further extended the algorithm to handle dynamic traffic changes and topology changes. A heuristic solution is proposed for MLSR under single channel interference. In the fourth study, EEJSPC, we first formulate a fundamental optimization problem that provides tunable energy-latency-throughput tradeoffs with joint scheduling and power control and present both exponential and polynomial complexity solutions. Then we investigate the problem of minimizing total transmission energy while satisfying transmission requests within a latency bound, and present an iterative approach which converges rapidly to the optimal parameter settings.

Feedback control of a Darrieus wind turbine and optimization of the produced energy

NASA Astrophysics Data System (ADS)

Maurin, T.; Henry, B.; Devos, F.; de Saint Louvent, B.; Gosselin, J.

1984-03-01

A microprocessor-driven control system, applied to the feedback control of a Darrieus wind turbine is presented. The use of a dc machine as a generator to recover the energy and as a motor to start the engine, allows simplified power electronics. The architecture of the control unit is built to ensure four different functions: starting, optimization of the recoverable energy, regulation of the speed, and braking. An experimental study of the system in a wind tunnel allowed optimization of the coefficients of the proportional and integral (pi) control algorithm. The electrical energy recovery was found to be much more efficient using the feedback system than without the control unit. This system allows a better characterization of the wind turbine and a regulation adapted to the wind statistics observed in one given geographical location.

Integrating prediction, provenance, and optimization into high energy workflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schram, M.; Bansal, V.; Friese, R. D.

We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

Optimal Power and Efficiency of Quantum Thermoacoustic Micro-cycle Working in 1D Harmonic Trap

NASA Astrophysics Data System (ADS)

E, Qing; Wu, Feng; Yin, Yong; Liu, XiaoWei

2017-10-01

Thermoacoustic engines (including heat engines and refrigerators) are energy conversion devices without moving part. They have great potential in aviation, new energy utilization, power technology, refrigerating and cryogenics. The thermoacoustic parcels, which compose the working fluid of a thermoacoustic engine, oscillate within the sound channel with a temperature gradient. The thermodynamic foundation of a thermoacoustic engine is the thermoacoustic micro-cycle (TAMC). In this paper, the theory of quantum mechanics is applied to the study of the actual thermoacoustic micro-cycle for the first time. A quantum mechanics model of the TAMC working in a 1D harmonic trap, which is named as a quantum thermoacoustic micro-cycle (QTAMC), is established. The QTAMC is composed of two constant force processes connected by two straight line processes. Analytic expressions of the power output and the efficiency for QTAMC have been derived. The effects of the trap width and the temperature amplitude on the power output and the thermal efficiency have been discussed. Some optimal characteristic curves of power output versus efficiency are plotted, and then the optimization region of QTAMC is given in this paper. The results obtained here not only enrich the thermoacoustic theory but also expand the application of quantum thermodynamics.

Neural network based optimal control of HVAC&R systems

NASA Astrophysics Data System (ADS)

Ning, Min

Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the supervisory controller, a set of five adaptive PI (proportional-integral) controllers are designed for each of the five local control loops of the HVAC&R system. The five controllers are used to track optimal set points and zone air temperature set points. Parameters of these PI controllers are tuned online to reduce tracking errors. The updating rules are derived from Lyapunov stability analysis. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.

Spectrum splitting using multi-layer dielectric meta-surfaces for efficient solar energy harvesting

NASA Astrophysics Data System (ADS)

Yao, Yuhan; Liu, He; Wu, Wei

2014-06-01

We designed a high-efficiency dispersive mirror based on multi-layer dielectric meta-surfaces. By replacing the secondary mirror of a dome solar concentrator with this dispersive mirror, the solar concentrator can be converted into a spectrum-splitting photovoltaic system with higher energy harvesting efficiency and potentially lower cost. The meta-surfaces are consisted of high-index contrast gratings (HCG). The structures and parameters of the dispersive mirror (i.e. stacked HCG) are optimized based on finite-difference time-domain and rigorous coupled-wave analysis method. Our numerical study shows that the dispersive mirror can direct light with different wavelengths into different angles in the entire solar spectrum, maintaining very low energy loss. Our approach will not only improve the energy harvesting efficiency, but also lower the cost by using single junction cells instead of multi-layer tandem solar cells. Moreover, this approach has the minimal disruption to the existing solar concentrator infrastructures.

A Biomimetic-Computational Approach to Optimizing the Quantum Efficiency of Photovoltaics

NASA Astrophysics Data System (ADS)

Perez, Lisa M.; Holzenburg, Andreas

The most advanced low-cost organic photovoltaic cells have a quantum efficiency of 10%. This is in stark contrast to plant/bacterial light-harvesting systems which offer quantum efficiencies close to unity. Of particular interest is the highly effective quantum coherence-enabled energy transfer (Fig. 1). Noting that quantum coherence is promoted by charged residues and local dielectrics, classical atomistic simulations and time-dependent density functional theory (DFT) are used to identify charge/dielectric patterns and electronic coupling at exactly defined energy transfer interfaces. The calculations make use of structural information obtained on photosynthetic protein-pigment complexes while still in the native membrane making it possible to establish a link between supramolecular organization and quantum coherence in terms of what length scales enable fast energy transport and prevent quenching. Calculating energy transfer efficiencies between components based on different proximities will permit the search for patterns that enable defining material properties suitable for advanced photovoltaics.

Regional energy planning: Some suggestions to public administration

NASA Astrophysics Data System (ADS)

Sozzi, R.

A methodology is proposed to estimate the relevant data and to improve the energy efficiency in regional energy planning. The quantification of the regional energy system is subdivided in three independent parameters which are separetely estimated: energy demand, energy consumption, and transformation capacity. Definitions and estimating procedures are given. The optimization of the regional planning includes the application, wherever possible, of the technologies which centralize the space-heating energy production or combine the production of electric energy with space-heating energy distribution.

Current and efficiency optimization under oscillating forces in entropic barriers

NASA Astrophysics Data System (ADS)

Nutku, Ferhat; Aydıner, Ekrem

2016-09-01

The transport of externally overdriven particles confined in entropic barriers is investigated under various types of oscillating and temporal forces. Temperature, load, and amplitude dependence of the particle current and energy conversion efficiency are investigated in three dimensions. For oscillating forces, the optimized temperature-load, amplitude-temperature, and amplitude-load intervals are determined when fixing the amplitude, load, and temperature, respectively. By using three-dimensional plots rather than two-dimensional ones, it is clearly shown that oscillating forces provide more efficiency compared with a temporal one in specified optimized parameter regions. Furthermore, the dependency of efficiency to the angle between the unbiased driving force and a constant force is investigated and an asymmetric angular dependence is found for all types of forces. Finally, it is shown that oscillating forces with a high amplitude and under a moderate load lead to higher efficiencies than a temporal force at both low and high temperatures for the entire range of contact angle. Project supported by the Istanbul University, Turkey (Grant No. 55383).

Optimization of the Efficiency of a Neutron Detector to Measure (α, n) Reaction Cross-Section

NASA Astrophysics Data System (ADS)

Perello, Jesus; Montes, Fernando; Ahn, Tony; Meisel, Zach; Joint InstituteNuclear Astrophysics Team

2015-04-01

Nucleosynthesis, the origin of elements, is one of the greatest mysteries in physics. A recent particular nucleosynthesis process of interest is the charge-particle process (cpp). In the cpp, elements form by nuclear fusion reactions during supernovae. This process of nuclear fusion, (α,n), will be studied by colliding beam elements produced and accelerated at the National Superconducting Cyclotron Laboratory (NSCL) to a helium-filled cell target. The elements will fuse with α (helium nuclei) and emit neutrons during the reaction. The neutrons will be detected for a count of fused-elements, thus providing us the probability of such reactions. The neutrons will be detected using the Neutron Emission Ratio Observer (NERO). Currently, NERO's efficiency varies for neutrons at the expected energy range (0-12 MeV). To study (α,n), NERO's efficiency must be near-constant at these energies. Monte-Carlo N-Particle Transport Code (MCNP6), a software package that simulates nuclear processes, was used to optimize NERO configuration for the experiment. MCNP6 was used to simulate neutron interaction with different NERO configurations at the expected neutron energies. By adding additional 3He detectors and polyethylene, a near-constant efficiency at these energies was obtained in the simulations. With the new NERO configuration, study of the (α,n) reactions can begin, which may explain how elements are formed in the cpp. SROP MSU, NSF, JINA, McNair Society.

An Optimization Framework for Dynamic Hybrid Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis

A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problemmore » takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.« less

Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E²)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hou, Yunfei; Seliman, Salaheldeen M. S.; Wang, Enshu

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly consideringmore » the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.« less

Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E²)

DOE PAGES

Hou, Yunfei; Seliman, Salaheldeen M. S.; Wang, Enshu; ...

2018-02-15

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly consideringmore » the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.« less

Power optimization of ultrasonic friction-modulation tactile interfaces.

PubMed

Wiertlewski, Michael; Colgate, J Edward

2015-01-01

Ultrasonic friction-modulation devices provide rich tactile sensation on flat surfaces and have the potential to restore tangibility to touchscreens. To date, their adoption into consumer electronics has been in part limited by relatively high power consumption, incompatible with the requirements of battery-powered devices. This paper introduces a method that optimizes the energy efficiency and performance of this class of devices. It considers optimal energy transfer to the impedance provided by the finger interacting with the surface. Constitutive equations are determined from the mode shape of the interface and the piezoelectric coupling of the actuator. The optimization procedure employs a lumped parameter model to simplify the treatment of the problem. Examples and an experimental study show the evolution of the optimal design as a function of the impedance of the finger.

Optimized nonorthogonal transforms for image compression.

PubMed

Guleryuz, O G; Orchard, M T

1997-01-01

The transform coding of images is analyzed from a common standpoint in order to generate a framework for the design of optimal transforms. It is argued that all transform coders are alike in the way they manipulate the data structure formed by transform coefficients. A general energy compaction measure is proposed to generate optimized transforms with desirable characteristics particularly suited to the simple transform coding operation of scalar quantization and entropy coding. It is shown that the optimal linear decoder (inverse transform) must be an optimal linear estimator, independent of the structure of the transform generating the coefficients. A formulation that sequentially optimizes the transforms is presented, and design equations and algorithms for its computation provided. The properties of the resulting transform systems are investigated. In particular, it is shown that the resulting basis are nonorthogonal and complete, producing energy compaction optimized, decorrelated transform coefficients. Quantization issues related to nonorthogonal expansion coefficients are addressed with a simple, efficient algorithm. Two implementations are discussed, and image coding examples are given. It is shown that the proposed design framework results in systems with superior energy compaction properties and excellent coding results.

Ship Trim Optimization: Assessment of Influence of Trim on Resistance of MOERI Container Ship

PubMed Central

Duan, Wenyang

2014-01-01

Environmental issues and rising fuel prices necessitate better energy efficiency in all sectors. Shipping industry is a stakeholder in environmental issues. Shipping industry is responsible for approximately 3% of global CO2 emissions, 14-15% of global NOX emissions, and 16% of global SOX emissions. Ship trim optimization has gained enormous momentum in recent years being an effective operational measure for better energy efficiency to reduce emissions. Ship trim optimization analysis has traditionally been done through tow-tank testing for a specific hullform. Computational techniques are increasingly popular in ship hydrodynamics applications. The purpose of this study is to present MOERI container ship (KCS) hull trim optimization by employing computational methods. KCS hull total resistances and trim and sinkage computed values, in even keel condition, are compared with experimental values and found in reasonable agreement. The agreement validates that mesh, boundary conditions, and solution techniques are correct. The same mesh, boundary conditions, and solution techniques are used to obtain resistance values in different trim conditions at Fn = 0.2274. Based on attained results, optimum trim is suggested. This research serves as foundation for employing computational techniques for ship trim optimization. PMID:24578649

Synchronous Firefly Algorithm for Cluster Head Selection in WSN

PubMed Central

Baskaran, Madhusudhanan; Sadagopan, Chitra

2015-01-01

Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH) offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC. PMID:26495431

Performance analysis of CO(2) emissions and energy efficiency of metal industries in China.

PubMed

Shao, Chaofeng; Guan, Yang; Wan, Zheng; Chu, Chunli; Ju, Meiting

2014-02-15

Nonferrous metal industries play an important role in China's national economy and are some of the country's largest energy consumers. To better understand the nature of CO(2) emissions from these industries and to further move towards low-carbon development in this industry sector, this study investigates the CO(2) emissions of 12 nonferrous metal industries from 2003 to 2010 based on their life-cycle assessments. It then classifies these industries into four "emission-efficiency" types through cluster analysis. The results show that (1) the industrial economy and energy consumption of China's nonferrous metal industries have grown rapidly, although their recent energy consumption rate shows a declining trend. (2) The copper, aluminum, zinc, lead, and magnesium industries, classified as high-emission industries, are the main contributors of CO(2) emissions. The results have implications for policy decisions that aim to enhance energy efficiency, particularly for promoting the transformation of low-efficiency industries to high-efficiency ones. The study also highlights the important role of policy development in technological innovations, optimization, and upgrades, the reduction of coal proportion in energy consumption, and the advancement of new energy sources. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessment of Distributed Generation Potential in JapaneseBuildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2005-05-25

To meet growing energy demands, energy efficiency, renewable energy, and on-site generation coupled with effective utilization of exhaust heat will all be required. Additional benefit can be achieved by integrating these distributed technologies into distributed energy resource (DER) systems (or microgrids). This research investigates a method of choosing economically optimal DER, expanding on prior studies at the Berkeley Lab using the DER design optimization program, the Distributed Energy Resources Customer Adoption Model (DER-CAM). DER-CAM finds the optimal combination of installed equipment from available DER technologies, given prevailing utility tariffs, site electrical and thermal loads, and a menu of available equipment.more » It provides a global optimization, albeit idealized, that shows how the site energy loads can be served at minimum cost by selection and operation of on-site generation, heat recovery, and cooling. Five prototype Japanese commercial buildings are examined and DER-CAM applied to select the economically optimal DER system for each. The five building types are office, hospital, hotel, retail, and sports facility. Based on the optimization results, energy and emission reductions are evaluated. Furthermore, a Japan-U.S. comparison study of policy, technology, and utility tariffs relevant to DER installation is presented. Significant decreases in fuel consumption, carbon emissions, and energy costs were seen in the DER-CAM results. Savings were most noticeable in the sports facility (a very favourable CHP site), followed by the hospital, hotel, and office building.« less

Efficient Transition State Optimization of Periodic Structures through Automated Relaxed Potential Energy Surface Scans.

PubMed

Plessow, Philipp N

2018-02-13

This work explores how constrained linear combinations of bond lengths can be used to optimize transition states in periodic structures. Scanning of constrained coordinates is a standard approach for molecular codes with localized basis functions, where a full set of internal coordinates is used for optimization. Common plane wave-codes for periodic boundary conditions almost exlusively rely on Cartesian coordinates. An implementation of constrained linear combinations of bond lengths with Cartesian coordinates is described. Along with an optimization of the value of the constrained coordinate toward the transition states, this allows transition optimization within a single calculation. The approach is suitable for transition states that can be well described in terms of broken and formed bonds. In particular, the implementation is shown to be effective and efficient in the optimization of transition states in zeolite-catalyzed reactions, which have high relevance in industrial processes.

Optimization for energy efficiency of underground building envelope thermal performance in different climate zones of China

NASA Astrophysics Data System (ADS)

Shi, Luyang; Liu, Jing; Zhang, Huibo

2017-11-01

The object of this article is to investigate the influence of thermal performance of envelopes in shallow-buried buildings on energy consumption for different climate zones of China. For the purpose of this study, an effective building energy simulation tool (DeST) developed by Tsinghua University was chosen to model the heat transfer in underground buildings. Based on the simulative results, energy consumption for heating and cooling for the whole year was obtained. The results showed that the relationship between energy consumption and U-value of envelopes for underground buildings is different compared with above-ground buildings: improving thermal performance of exterior walls cannot reduce energy consumption, on the contrary, may result in more energy cost. Besides, it is can be derived that optimized U-values of underground building envelopes vary with climate zones of China in this study. For severe cold climate zone, the optimized U-value of underground building envelopes is 0.8W/(m2·K); for cold climate zone, the optimized U-value is 1.5W/(m2·K); for warm climate zone, the U-value is 2.0W/(m2·K).

Design optimization of the S-frame to improve crashworthiness

NASA Astrophysics Data System (ADS)

Liu, Shu-Tian; Tong, Ze-Qi; Tang, Zhi-Liang; Zhang, Zong-Hua

2014-08-01

In this paper, the S-frames, the front side rail structures of automobile, were investigated for crashworthiness. Various cross-sections including regular polygon, non-convex polygon and multi-cell with inner stiffener sections were investigated in terms of energy absorption of S-frames. It was determined through extensive numerical simulation that a multi-cell S-frame with double vertical internal stiffeners can absorb more energy than the other configurations. Shape optimization was also carried out to improve energy absorption of the S-frame with a rectangular section. The center composite design of experiment and the sequential response surface method (SRSM) were adopted to construct the approximate design sub-problem, which was then solved by the feasible direction method. An innovative double S-frame was obtained from the optimal result. The optimum configuration of the S-frame was crushed numerically and more plastic hinges as well as shear zones were observed during the crush process. The energy absorption efficiency of the structure with the optimal configuration was improved compared to the initial configuration.

Power allocation strategies to minimize energy consumption in wireless body area networks.

PubMed

Kailas, Aravind

2011-01-01

The wide scale deployment of wireless body area networks (WBANs) hinges on designing energy efficient communication protocols to support the reliable communication as well as to prolong the network lifetime. Cooperative communications, a relatively new idea in wireless communications, offers the benefits of multi-antenna systems, thereby improving the link reliability and boosting energy efficiency. In this short paper, the advantages of resorting to cooperative communications for WBANs in terms of minimized energy consumption are investigated. Adopting an energy model that encompasses energy consumptions in the transmitter and receiver circuits, and transmitting energy per bit, it is seen that cooperative transmission can improve energy efficiency of the wireless network. In particular, the problem of optimal power allocation is studied with the constraint of targeted outage probability. Two strategies of power allocation are considered: power allocation with and without posture state information. Using analysis and simulation-based results, two key points are demonstrated: (i) allocating power to the on-body sensors making use of the posture information can reduce the total energy consumption of the WBAN; and (ii) when the channel condition is good, it is better to recruit less relays for cooperation to enhance energy efficiency.

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors.

PubMed

Dasgupta, Rumpa; Yoon, Seokhoon

2017-04-01

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs' traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs' paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay.

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors

PubMed Central

Dasgupta, Rumpa; Yoon, Seokhoon

2017-01-01

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs’ traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs’ paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay. PMID:28368300

Information efficiency in visual communication

NASA Astrophysics Data System (ADS)

Alter-Gartenberg, Rachel; Rahman, Zia-ur

1993-08-01

This paper evaluates the quantization process in the context of the end-to-end performance of the visual-communication channel. Results show that the trade-off between data transmission and visual quality revolves around the information in the acquired signal, not around its energy. Improved information efficiency is gained by frequency dependent quantization that maintains the information capacity of the channel and reduces the entropy of the encoded signal. Restorations with energy bit-allocation lose both in sharpness and clarity relative to restorations with information bit-allocation. Thus, quantization with information bit-allocation is preferred for high information efficiency and visual quality in optimized visual communication.

OppoRTUnities Abound

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deru, Michael

According to the U.S. Energy Information Administration, HVAC accounts for approximately 38 percent of U.S. commercial buildings' primary energy consumption and a slightly higher percentage of their greenhouse-gas emissions. We have seen incredible gains made with lighting, going from incandescent and T12 fluorescent bulbs to high-efficiency LEDS, but there are even greater advances to be made with HVAC. Gains of 20 percent to 30 percent easily can be made by replacing older degraded equipment with new high-efficiency equipment. Even more savings are possible with an integrated engineering approach yielding optimized system designs combined with highly efficient controls.

Information efficiency in visual communication

NASA Technical Reports Server (NTRS)

Alter-Gartenberg, Rachel; Rahman, Zia-Ur

1993-01-01

This paper evaluates the quantization process in the context of the end-to-end performance of the visual-communication channel. Results show that the trade-off between data transmission and visual quality revolves around the information in the acquired signal, not around its energy. Improved information efficiency is gained by frequency dependent quantization that maintains the information capacity of the channel and reduces the entropy of the encoded signal. Restorations with energy bit-allocation lose both in sharpness and clarity relative to restorations with information bit-allocation. Thus, quantization with information bit-allocation is preferred for high information efficiency and visual quality in optimized visual communication.

Progress Towards Highly Efficient Windows for Zero—Energy Buildings

NASA Astrophysics Data System (ADS)

Selkowitz, Stephen

2008-09-01

Energy efficient windows could save 4 quads/year, with an additional 1 quad/year gain from daylighting in commercial buildings. This corresponds to 13% of energy used by US buildings and 5% of all energy used by the US. The technical potential is thus very large and the economic potential is slowly becoming a reality. This paper describes the progress in energy efficient windows that employ low-emissivity glazing, electrochromic switchable coatings and other novel materials. Dynamic systems are being developed that use sensors and controls to modulate daylighting and shading contributions in response to occupancy, comfort and energy needs. Improving the energy performance of windows involves physics in a variety of application: optics, heat transfer, materials science and applied engineering. Technical solutions must also be compatible with national policy, codes and standards, economics, business practice and investment, real and perceived risks, comfort, health, safety, productivity, amenities, and occupant preference and values. The challenge is to optimize energy performance by understanding and reinforcing the synergetic coupling between these many issues.

An energy analysis of torrefaction for upgrading microalga residue as a solid fuel.

PubMed

Chen, Wei-Hsin; Huang, Ming-Yueh; Chang, Jo-Shu; Chen, Chun-Yen; Lee, Wen-Jhy

2015-06-01

The torrefaction characteristics and energy utilization of microalga Chlamydomonas sp. JSC4 (C. sp. JSC4) residue under the combination of temperature and duration are studied by examining contour maps. The torrefaction temperature on the contour line of solid yield has a trend to linearly decrease with increasing duration. An index of relative energy efficiency (REE) is introduced to identify the performance of energy utilization for upgrading biomass. For a fixed energy yield, the optimal operation can be found to maximize the heating value of the biomass and minimize the solid yield. The energy utilization under the combination of a high temperature and a short duration is more efficient than that of a low temperature and a long duration. The maximum REE along the contour line of energy yield is always exhibited at the highest temperature (300°C) where the energy efficiency can be enlarged by a factor of at least 2.36. Copyright © 2015 Elsevier Ltd. All rights reserved.

Energy Efficiency Challenges of 5G Small Cell Networks.

PubMed

Ge, Xiaohu; Yang, Jing; Gharavi, Hamid; Sun, Yang

2017-05-01

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this paper is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell base stations (BSs). Moreover, the computation power of 5G small cell BS can approach 800 watt when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks.

Energy Efficiency Challenges of 5G Small Cell Networks

PubMed Central

Ge, Xiaohu; Yang, Jing; Gharavi, Hamid; Sun, Yang

2017-01-01

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this paper is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell base stations (BSs). Moreover, the computation power of 5G small cell BS can approach 800 watt when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks. PMID:28757670

Development of a Prototype Low-Voltage Electron Beam Freeform Fabrication System

NASA Technical Reports Server (NTRS)

Watson, J. K.; Taminger, K. M.; Hafley, R. A.; Petersen, D. D.

2002-01-01

NASA's Langley Research Center and Johnson Space Center are developing a solid freeform fabrication system utilizing an electron beam energy source and wire feedstock. This system will serve as a testbed for exploring the influence of gravitational acceleration on the deposition process and will be a simplified prototype for future systems that may be deployed during long-duration space missions for assembly, fabrication, and production of structural and mechanical replacement components. Critical attributes for this system are compactness, minimal mass, efficiency in use of feedstock material, energy use efficiency, and safety. The use of a low-voltage (less than 15kV) electron beam energy source will reduce radiation so that massive shielding is not required to protect adjacent personnel. Feedstock efficiency will be optimized by use of wire, and energy use efficiency will be achieved by use of the electron beam energy source. This system will be evaluated in a microgravity environment using the NASA KC-135A aircraft.

Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine

NASA Astrophysics Data System (ADS)

Zhang, L.; Zhuge, W. L.; Peng, J.; Liu, S. J.; Zhang, Y. J.

2013-12-01

In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (WR and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β6, the exit tip radius R6t and hub radius R6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency ηts, and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency ηts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the value of τ is at 0.5 to 0.6.

Optimal Energy Management for Microgrids

NASA Astrophysics Data System (ADS)

Zhao, Zheng

Microgrid is a recent novel concept in part of the development of smart grid. A microgrid is a low voltage and small scale network containing both distributed energy resources (DERs) and load demands. Clean energy is encouraged to be used in a microgrid for economic and sustainable reasons. A microgrid can have two operational modes, the stand-alone mode and grid-connected mode. In this research, a day-ahead optimal energy management for a microgrid under both operational modes is studied. The objective of the optimization model is to minimize fuel cost, improve energy utilization efficiency and reduce gas emissions by scheduling generations of DERs in each hour on the next day. Considering the dynamic performance of battery as Energy Storage System (ESS), the model is featured as a multi-objectives and multi-parametric programming constrained by dynamic programming, which is proposed to be solved by using the Advanced Dynamic Programming (ADP) method. Then, factors influencing the battery life are studied and included in the model in order to obtain an optimal usage pattern of battery and reduce the correlated cost. Moreover, since wind and solar generation is a stochastic process affected by weather changes, the proposed optimization model is performed hourly to track the weather changes. Simulation results are compared with the day-ahead energy management model. At last, conclusions are presented and future research in microgrid energy management is discussed.

A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints

DOE PAGES

Wu, Fei; Sioshansi, Ramteen

2017-05-25

Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival timesmore » and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. Here, we demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. Lastly, we also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.« less

Integrating a dual-silicon photoelectrochemical cell into a redox flow battery for unassisted photocharging.

PubMed

Liao, Shichao; Zong, Xu; Seger, Brian; Pedersen, Thomas; Yao, Tingting; Ding, Chunmei; Shi, Jingying; Chen, Jian; Li, Can

2016-05-04

Solar rechargeable flow cells (SRFCs) provide an attractive approach for in situ capture and storage of intermittent solar energy via photoelectrochemical regeneration of discharged redox species for electricity generation. However, overall SFRC performance is restricted by inefficient photoelectrochemical reactions. Here we report an efficient SRFC based on a dual-silicon photoelectrochemical cell and a quinone/bromine redox flow battery for in situ solar energy conversion and storage. Using narrow bandgap silicon for efficient photon collection and fast redox couples for rapid interface charge injection, our device shows an optimal solar-to-chemical conversion efficiency of ∼5.9% and an overall photon-chemical-electricity energy conversion efficiency of ∼3.2%, which, to our knowledge, outperforms previously reported SRFCs. The proposed SRFC can be self-photocharged to 0.8 V and delivers a discharge capacity of 730 mAh l(-1). Our work may guide future designs for highly efficient solar rechargeable devices.

Optimization design of hydroturbine rotors according to the efficiency-strength criteria

NASA Astrophysics Data System (ADS)

Bannikov, D. V.; Yesipov, D. V.; Cherny, S. G.; Chirkov, D. V.

2010-12-01

The hydroturbine runner designing [1] is optimized by efficient methods for calculation of head loss in entire flow-through part of the turbine and deformation state of the blade. Energy losses are found at modelling of the spatial turbulent flow and engineering semi-empirical formulae. State of deformation is determined from the solution of the linear problem of elasticity for the isolated blade at hydrodynamic pressure with the method of boundary elements. With the use of the proposed system, the problem of the turbine runner design with the capacity of 640 MW providing the preset dependence of efficiency on the turbine work mode (efficiency criterion) is solved. The arising stresses do not exceed the critical value (strength criterion).

Cost-efficiency trade-off and the design of thermoelectric power generators.

PubMed

Yazawa, Kazuaki; Shakouri, Ali

2011-09-01

The energy conversion efficiency of today's thermoelectric generators is significantly lower than that of conventional mechanical engines. Almost all of the existing research is focused on materials to improve the conversion efficiency. Here we propose a general framework to study the cost-efficiency trade-off for thermoelectric power generation. A key factor is the optimization of thermoelectric modules together with their heat source and heat sinks. Full electrical and thermal co-optimization yield a simple analytical expression for optimum design. Based on this model, power output per unit mass can be maximized. We show that the fractional area coverage of thermoelectric elements in a module could play a significant role in reducing the cost of power generation systems.

Optimized Ion Energy Profiles for Heavy Ion Direct Drive Targets

NASA Astrophysics Data System (ADS)

Hay, Michael J.; Barnard, John J.; Perkins, L. John; Logan, B. Grant

2009-11-01

Recent 1-D implosion calculations [1] have characterized pure-DT targets delivering gains of 50-90 with less than 0.5 MJ of heavy ion direct drive. With a payload fraction of 1/3, these low-aspect ratio targets operate near the peak of rocket efficiency and achieve ˜10% overall coupling efficiencies (vs. the 15-20% efficiencies analytically predicted for less stable, higher-aspect ratio targets). In Ref. 1, the ion energy is ramped directly from a 50 MeV foot pulse to a 500 MeV main pulse. In this paper, we instead tune the ion energy throughout the drive to closely match the beam deposition with the inward progress of the ablation front. We will present the ion energy and intensity time histories that maximize drive efficiency and gain for a single target at constant integrated drive energy. [1] L. J. Perkins, B. G. Logan, J. J. Barnard, and M. J. Hay. ``High Efficiency High Gain Heavy Ion Direct Drive Targets,'' Bulletin of the American Physical Society, vol. 54: DPP, Nov. 2009.

Hybrid-drive implosion system for ICF targets

DOEpatents

Mark, James W.

1988-08-02

Hybrid-drive implosion systems (20,40) for ICF targets (10,22,42) are described which permit a significant increase in target gain at fixed total driver energy. The ICF target is compressed in two phases, an initial compression phase and a final peak power phase, with each phase driven by a separate, optimized driver. The targets comprise a hollow spherical ablator (12) surroundingly disposed around fusion fuel (14). The ablator is first compressed to higher density by a laser system (24), or by an ion beam system (44), that in each case is optimized for this initial phase of compression of the target. Then, following compression of the ablator, energy is directly delivered into the compressed ablator by an ion beam driver system (30,48) that is optimized for this second phase of operation of the target. The fusion fuel (14) is driven, at high gain, to conditions wherein fusion reactions occur. This phase separation allows hydrodynamic efficiency and energy deposition uniformity to be individually optimized, thereby securing significant advantages in energy gain. In additional embodiments, the same or separate drivers supply energy for ICF target implosion.

Hybrid-drive implosion system for ICF targets

DOEpatents

Mark, James W.

1988-01-01

Hybrid-drive implosion systems (20,40) for ICF targets (10,22,42) are described which permit a significant increase in target gain at fixed total driver energy. The ICF target is compressed in two phases, an initial compression phase and a final peak power phase, with each phase driven by a separate, optimized driver. The targets comprise a hollow spherical ablator (12) surroundingly disposed around fusion fuel (14). The ablator is first compressed to higher density by a laser system (24), or by an ion beam system (44), that in each case is optimized for this initial phase of compression of the target. Then, following compression of the ablator, energy is directly delivered into the compressed ablator by an ion beam driver system (30,48) that is optimized for this second phase of operation of the target. The fusion fuel (14) is driven, at high gain, to conditions wherein fusion reactions occur. This phase separation allows hydrodynamic efficiency and energy deposition uniformity to be individually optimized, thereby securing significant advantages in energy gain. In additional embodiments, the same or separate drivers supply energy for ICF target implosion.

Hybrid-drive implosion system for ICF targets

DOEpatents

Mark, J.W.K.

1987-10-14

Hybrid-drive implosion systems for ICF targets are described which permit a significant increase in target gain at fixed total driver energy. The ICF target is compressed in two phases, an initial compression phase and a final peak power phase, with each phase driven by a separate, optimized driver. The targets comprise a hollow spherical ablator surroundingly disposed around fusion fuel. The ablator is first compressed to higher density by a laser system, or by an ion beam system, that in each case is optimized for this initial phase of compression of the target. Then, following compression of the ablator, energy is directly delivered into the compressed ablator by an ion beam driver system that is optimized for this second phase of operation of the target. The fusion fuel is driven, at high gain, to conditions wherein fusion reactions occur. This phase separation allows hydrodynamic efficiency and energy deposition uniformity to be individually optimized, thereby securing significant advantages in energy gain. In additional embodiments, the same or separate drivers supply energy for ICF target implosion. 3 figs.

The effects of particle swarm optimization algorithm on volume ignition gain of Proton-Lithium (7) pellets

NASA Astrophysics Data System (ADS)

Livari, As. Ali; Malekynia, B.; Livari, Ak. A.; Khoda-Bakhsh, R.

2017-11-01

When it was found out that the ignition of nuclear fusion hinges upon input energy laser, the efforts in order to make giant lasers began, and energy gains of DT fuel were obtained. But due to the neutrons generation and emitted radioactivity from DT reaction, gains of fuels like Proton-Lithium (7) were also adverted. Therefore, making larger and powerful lasers was followed. Here, using new versions of particle swarm optimization algorithm, it will be shown that available maximum gain of Proton-Lithium (7) is reached only at energies about 1014 J, and not only the highest input energy is not helpful but the efficiency is also decreased.

Atmospheric Renewable Energy Research, Volume 4: Atmospheric Renewable Energy Field Study Number 2 (ARE2)

DTIC Science & Technology

2017-10-30

these renewable energy commodities. For this report, we focus on solar power, gleaned from photovoltaic ( PV ) technology, as the renewable energy...optimized efficiency and effectiveness for the hybrid microgrid. Presuming solar energy is being extracted using photovoltaic ( PV ) panels (versus solar ...inhibitors of solar radiation traversing from space to the PV panels on or near the earth’s surface were categorized as hard and soft shadows. The

Harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency.

PubMed

VandeHaar, M J; Armentano, L E; Weigel, K; Spurlock, D M; Tempelman, R J; Veerkamp, R

2016-06-01

Feed efficiency, as defined by the fraction of feed energy or dry matter captured in products, has more than doubled for the US dairy industry in the past 100 yr. This increased feed efficiency was the result of increased milk production per cow achieved through genetic selection, nutrition, and management with the desired goal being greater profitability. With increased milk production per cow, more feed is consumed per cow, but a greater portion of the feed is partitioned toward milk instead of maintenance and body growth. This dilution of maintenance has been the overwhelming driver of enhanced feed efficiency in the past, but its effect diminishes with each successive increment in production relative to body size and therefore will be less important in the future. Instead, we must also focus on new ways to enhance digestive and metabolic efficiency. One way to examine variation in efficiency among animals is residual feed intake (RFI), a measure of efficiency that is independent of the dilution of maintenance. Cows that convert feed gross energy to net energy more efficiently or have lower maintenance requirements than expected based on body weight use less feed than expected and thus have negative RFI. Cows with low RFI likely digest and metabolize nutrients more efficiently and should have overall greater efficiency and profitability if they are also healthy, fertile, and produce at a high multiple of maintenance. Genomic technologies will help to identify these animals for selection programs. Nutrition and management also will continue to play a major role in farm-level feed efficiency. Management practices such as grouping and total mixed ration feeding have improved rumen function and therefore efficiency, but they have also decreased our attention on individual cow needs. Nutritional grouping is key to helping each cow reach its genetic potential. Perhaps new computer-driven technologies, combined with genomics, will enable us to optimize management for each individual cow within a herd, or to optimize animal selection to match management environments. In the future, availability of feed resources may shift as competition for land increases. New approaches combining genetic, nutrition, and other management practices will help optimize feed efficiency, profitability, and environmental sustainability. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Improvement of the energy resolution of pixelated CdTe detectors for applications in 0νββ searches

NASA Astrophysics Data System (ADS)

Gleixner, T.; Anton, G.; Filipenko, M.; Seller, P.; Veale, M. C.; Wilson, M. D.; Zang, A.; Michel, T.

2015-07-01

Experiments trying to detect 0νββ are very challenging. Their requirements include a good energy resolution and a good detection efficiency. With current fine pixelated CdTe detectors there is a trade off between the energy resolution and the detection efficiency, which limits their performance. It will be shown with simulations that this problem can be mostly negated by analysing the cathode signal which increases the optimal sensor thickness. We will compare different types of fine pixelated CdTe detectors (Timepix, Dosepix, HEXITEC) from this point of view.

Transaction-Based Building Controls Framework, Volume 1: Reference Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Somasundaram, Sriram; Pratt, Robert G.; Akyol, Bora A.

This document proposes a framework concept to achieve the objectives of raising buildings’ efficiency and energy savings potential benefitting building owners and operators. We call it a transaction-based framework, wherein mutually-beneficial and cost-effective market-based transactions can be enabled between multiple players across different domains. Transaction-based building controls are one part of the transactional energy framework. While these controls realize benefits by enabling automatic, market-based intra-building efficiency optimizations, the transactional energy framework provides similar benefits using the same market -based structure, yet on a larger scale and beyond just buildings, to the society at large.

Optimization of Light-Harvesting Pigment Improves Photosynthetic Efficiency.

PubMed

Jin, Honglei; Li, Mengshu; Duan, Sujuan; Fu, Mei; Dong, Xiaoxiao; Liu, Bing; Feng, Dongru; Wang, Jinfa; Wang, Hong-Bin

2016-11-01

Maximizing light capture by light-harvesting pigment optimization represents an attractive but challenging strategy to improve photosynthetic efficiency. Here, we report that loss of a previously uncharacterized gene, HIGH PHOTOSYNTHETIC EFFICIENCY1 (HPE1), optimizes light-harvesting pigments, leading to improved photosynthetic efficiency and biomass production. Arabidopsis (Arabidopsis thaliana) hpe1 mutants show faster electron transport and increased contents of carbohydrates. HPE1 encodes a chloroplast protein containing an RNA recognition motif that directly associates with and regulates the splicing of target RNAs of plastid genes. HPE1 also interacts with other plastid RNA-splicing factors, including CAF1 and OTP51, which share common targets with HPE1. Deficiency of HPE1 alters the expression of nucleus-encoded chlorophyll-related genes, probably through plastid-to-nucleus signaling, causing decreased total content of chlorophyll (a+b) in a limited range but increased chlorophyll a/b ratio. Interestingly, this adjustment of light-harvesting pigment reduces antenna size, improves light capture, decreases energy loss, mitigates photodamage, and enhances photosynthetic quantum yield during photosynthesis. Our findings suggest a novel strategy to optimize light-harvesting pigments that improves photosynthetic efficiency and biomass production in higher plants. © 2016 American Society of Plant Biologists. All Rights Reserved.

Optimization of Light-Harvesting Pigment Improves Photosynthetic Efficiency1[OPEN

PubMed Central

Jin, Honglei; Li, Mengshu; Duan, Sujuan; Fu, Mei; Dong, Xiaoxiao; Feng, Dongru; Wang, Jinfa

2016-01-01

Maximizing light capture by light-harvesting pigment optimization represents an attractive but challenging strategy to improve photosynthetic efficiency. Here, we report that loss of a previously uncharacterized gene, HIGH PHOTOSYNTHETIC EFFICIENCY1 (HPE1), optimizes light-harvesting pigments, leading to improved photosynthetic efficiency and biomass production. Arabidopsis (Arabidopsis thaliana) hpe1 mutants show faster electron transport and increased contents of carbohydrates. HPE1 encodes a chloroplast protein containing an RNA recognition motif that directly associates with and regulates the splicing of target RNAs of plastid genes. HPE1 also interacts with other plastid RNA-splicing factors, including CAF1 and OTP51, which share common targets with HPE1. Deficiency of HPE1 alters the expression of nucleus-encoded chlorophyll-related genes, probably through plastid-to-nucleus signaling, causing decreased total content of chlorophyll (a+b) in a limited range but increased chlorophyll a/b ratio. Interestingly, this adjustment of light-harvesting pigment reduces antenna size, improves light capture, decreases energy loss, mitigates photodamage, and enhances photosynthetic quantum yield during photosynthesis. Our findings suggest a novel strategy to optimize light-harvesting pigments that improves photosynthetic efficiency and biomass production in higher plants. PMID:27609860

Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox

NASA Astrophysics Data System (ADS)

Li, R. N.; Liu, X.; Liu, S. J.

2013-12-01

In order to ensure the high efficiency of the whole flexible drive train of the front-end speed adjusting wind turbine, the working principle of the main part of the drive train is analyzed. As critical parameters, rotating speed ratios of three planetary gear trains are selected as the research subject. The mathematical model of the torque converter speed ratio is established based on these three critical variable quantity, and the effect of key parameters on the efficiency of hydraulic mechanical transmission is analyzed. Based on the torque balance and the energy balance, refer to hydraulic mechanical transmission characteristics, the transmission efficiency expression of the whole drive train is established. The fitness function and constraint functions are established respectively based on the drive train transmission efficiency and the torque converter rotating speed ratio range. And the optimization calculation is carried out by using MATLAB genetic algorithm toolbox. The optimization method and results provide an optimization program for exact match of wind turbine rotor, gearbox, hydraulic mechanical transmission, hydraulic torque converter and synchronous generator, ensure that the drive train work with a high efficiency, and give a reference for the selection of the torque converter and hydraulic mechanical transmission.

Weather Driven Renewable Energy Analysis, Modeling New Technologies

NASA Astrophysics Data System (ADS)

Paine, J.; Clack, C.; Picciano, P.; Terry, L.

2015-12-01

Carbon emission reduction is essential to hampering anthropogenic climate change. While there are several methods to broach carbon reductions, the National Energy with Weather System (NEWS) model focuses on limiting electrical generation emissions by way of a national high-voltage direct-current transmission that takes advantage of the strengths of different regions in terms of variable sources of energy. Specifically, we focus upon modeling concentrating solar power (CSP) as another source to contribute to the electric grid. Power tower solar fields are optimized taking into account high spatial and temporal resolution, 13km and hourly, numerical weather prediction model data gathered by NOAA from the years of 2006-2008. Importantly, the optimization of these CSP power plants takes into consideration factors that decrease the optical efficiency of the heliostats reflecting solar irradiance. For example, cosine efficiency, atmospheric attenuation, and shadowing are shown here; however, it should be noted that they are not the only limiting factors. While solar photovoltaic plants can be combined for similar efficiency to the power tower and currently at a lower cost, they do not have a cost-effective capability to provide electricity when there are interruptions in solar irradiance. Power towers rely on a heat transfer fluid, which can be used for thermal storage changing the cost efficiency of this energy source. Thermal storage increases the electric stability that many other renewable energy sources lack, and thus, the ability to choose between direct electric conversion and thermal storage is discussed. The figure shown is a test model of a CSP plant made up of heliostats. The colors show the optical efficiency of each heliostat at a single time of the day.

Magnetic materials and devices for the 21st century: stronger, lighter, and more energy efficient.

PubMed

Gutfleisch, Oliver; Willard, Matthew A; Brück, Ekkes; Chen, Christina H; Sankar, S G; Liu, J Ping

2011-02-15

A new energy paradigm, consisting of greater reliance on renewable energy sources and increased concern for energy efficiency in the total energy lifecycle, has accelerated research into energy-related technologies. Due to their ubiquity, magnetic materials play an important role in improving the efficiency and performance of devices in electric power generation, conditioning, conversion, transportation, and other energy-use sectors of the economy. This review focuses on the state-of-the-art hard and soft magnets and magnetocaloric materials, with an emphasis on their optimization for energy applications. Specifically, the impact of hard magnets on electric motor and transportation technologies, of soft magnetic materials on electricity generation and conversion technologies, and of magnetocaloric materials for refrigeration technologies, are discussed. The synthesis, characterization, and property evaluation of the materials, with an emphasis on structure-property relationships, are discussed in the context of their respective markets, as well as their potential impact on energy efficiency. Finally, considering future bottlenecks in raw materials, options for the recycling of rare-earth intermetallics for hard magnets will be discussed. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SU-F-T-193: Evaluation of a GPU-Based Fast Monte Carlo Code for Proton Therapy Biological Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taleei, R; Qin, N; Jiang, S

2016-06-15

Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency. Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relativemore » Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS). Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ∼ 600 times faster. Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.« less

Optimization of plasma amplifiers

DOE PAGES

Sadler, James D.; Trines, Raoul M. G. M.; Tabak, Max; ...

2017-05-24

Here, plasma amplifiers offer a route to side-step limitations on chirped pulse amplification and generate laser pulses at the power frontier. They compress long pulses by transferring energy to a shorter pulse via the Raman or Brillouin instabilities. We present an extensive kinetic numerical study of the three-dimensional parameter space for the Raman case. Further particle-in-cell simulations find the optimal seed pulse parameters for experimentally relevant constraints. The high-efficiency self-similar behavior is observed only for seeds shorter than the linear Raman growth time. A test case similar to an upcoming experiment at the Laboratory for Laser Energetics is found tomore » maintain good transverse coherence and high-energy efficiency. Effective compression of a 10kJ, nanosecond-long driver pulse is also demonstrated in a 15-cm-long amplifier.« less

Optimization of plasma amplifiers

NASA Astrophysics Data System (ADS)

Sadler, James D.; Trines, Raoul M. Â. G. Â. M.; Tabak, Max; Haberberger, Dan; Froula, Dustin H.; Davies, Andrew S.; Bucht, Sara; Silva, Luís O.; Alves, E. Paulo; Fiúza, Frederico; Ceurvorst, Luke; Ratan, Naren; Kasim, Muhammad F.; Bingham, Robert; Norreys, Peter A.

2017-05-01

Plasma amplifiers offer a route to side-step limitations on chirped pulse amplification and generate laser pulses at the power frontier. They compress long pulses by transferring energy to a shorter pulse via the Raman or Brillouin instabilities. We present an extensive kinetic numerical study of the three-dimensional parameter space for the Raman case. Further particle-in-cell simulations find the optimal seed pulse parameters for experimentally relevant constraints. The high-efficiency self-similar behavior is observed only for seeds shorter than the linear Raman growth time. A test case similar to an upcoming experiment at the Laboratory for Laser Energetics is found to maintain good transverse coherence and high-energy efficiency. Effective compression of a 10 kJ , nanosecond-long driver pulse is also demonstrated in a 15-cm-long amplifier.

Formulation strategies for optimizing the morphology of polymeric bulk heterojunction organic solar cells: a brief review

NASA Astrophysics Data System (ADS)

Vongsaysy, Uyxing; Bassani, Dario M.; Servant, Laurent; Pavageau, Bertrand; Wantz, Guillaume; Aziz, Hany

2014-01-01

Polymeric bulk heterojunction (BHJ) organic solar cells represent one of the most promising technologies for renewable energy with a low fabrication cost. Control over BHJ morphology is one of the key factors in obtaining high-efficiency devices. This review focuses on formulation strategies for optimizing the BHJ morphology. We address how solvent choice and the introduction of processing additives affect the morphology. We also review a number of recent studies concerning prediction methods that utilize the Hansen solubility parameters to develop efficient solvent systems.

Optimal translational swimming of a sphere at low Reynolds number.

PubMed

Felderhof, B U; Jones, R B

2014-08-01

Swimming velocity and rate of dissipation of a sphere with surface distortions are discussed on the basis of the Stokes equations of low-Reynolds-number hydrodynamics. At first the surface distortions are assumed to cause an irrotational axisymmetric flow pattern. The efficiency of swimming is optimized within this class of flows. Subsequently, more general axisymmetric polar flows with vorticity are considered. This leads to a considerably higher maximum efficiency. An additional measure of swimming performance is proposed based on the energy consumption for given amplitude of stroke.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks.

PubMed

Zhang, Guomei; Sun, Hao

2016-12-16

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor's reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks

PubMed Central

Zhang, Guomei; Sun, Hao

2016-01-01

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor’s reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured. PMID:27999282

Energy comparison between solar thermal power plant and photovoltaic power plant

NASA Astrophysics Data System (ADS)

Novosel, Urška; Avsec, Jurij

2017-07-01

The combined use of renewable energy and alternative energy systems and better efficiency of energy devices is a promising approach to reduce effects due to global warming in the world. On the basis of first and second law of thermodynamics we could optimize the processes in the energy sector. The presented paper shows the comparison between solar thermal power plant and photovoltaic power plant in terms of energy, exergy and life cycle analysis. Solar thermal power plant produces electricity with basic Rankine cycle, using solar tower and solar mirrors to produce high fluid temperature. Heat from the solar system is transferred by using a heat exchanger to Rankine cycle. Both power plants produce hydrogen via electrolysis. The paper shows the global efficiency of the system, regarding production of the energy system.

[Optimization of Energy Saving Measures with ABR-MBR Integrated Process].

PubMed

Wu, Peng; Lu, Shuang-jun; Xu, Yue-zhong; Liu, Jie; Shen, Yao-liang

2015-08-01

High energy consumption and membrane fouling are important factors that limit the wide use of membrane bioreactor (MBR). In order to reduce energy consumption and delay the process of membrane fouling, the process of anaerobic baffled reactor (ABR)-MBR was used to treat domestic sewage. The structure of the process and conditions of nitrogen and phosphorus removal were optimized in this study. The results showed that energy consumption was reduced by 43% through optimizing the structure of ABR-MBR process. Meanwhile, the process achieved a high level of COD, NH: -N, TN and TP removal, with the average removal efficiencies of 91%, 85%, 76% and 86%, respectively. In addition, the added particulate media could effectively delay membrane fouling, while the formation process of membrane fouling was changed. The extracted amount of carbohydrates increased while the amount of proteins decreased. Finally, the potential was enhanced for the practical application of MBR.

First Steps in the Smart Grid Framework: An Optimal and Feasible Pathway Toward Power System Reform in Mexico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bracho, Riccardo; Linvill, Carl; Sedano, Richard

With the vision to transform the power sector, Mexico included in the new laws and regulations deployment of smart grid technologies and provided various attributes to the Ministry of Energy and the Energy Regulatory Commission to enact public policies and regulation. The use of smart grid technologies can have a significant impact on the integration of variable renewable energy resources while maintaining reliability and stability of the system, significantly reducing technical and non-technical electricity losses in the grid, improving cyber security, and allowing consumers to make distributed generation and demand response decisions. This report describes for Mexico's Ministry of Energymore » (SENER) an overall approach (Optimal Feasible Pathway) for moving forward with smart grid policy development in Mexico to enable increasing electric generation from renewable energy in a way that optimizes system stability and reliability in an efficient and cost-effective manner.« less

Detonation Energies of Explosives by Optimized JCZ3 Procedures

NASA Astrophysics Data System (ADS)

Stiel, Leonard; Baker, Ernest

1997-07-01

Procedures for the detonation properties of explosives have been extended for the calculation of detonation energies at adiabatic expansion conditions. Advanced variable metric optimization routines developed by ARDEC are utilized to establish chemical reaction equilibrium by the minimization of the Helmholtz free energy of the system. The use of the JCZ3 equation of state with optimized Exp-6 potential parameters leads to lower errors in JWL detonation energies than the TIGER JCZ3 procedure and other methods tested for relative volumes to 7.0. For the principal isentrope with C-J parameters and freeze conditions established at elevated pressures with the JCZ3 equation of state, best results are obtained if an alternate volumetric relationship is utilized at the highest expansions. Efficient subroutines (designated JAGUAR) have been developed which incorporate the ability to automatically generate JWL and JWLB equation of state parameters. abstract.

Random benzotrithiophene-based donor-acceptor copolymers for efficient organic photovoltaic devices.

PubMed

Nielsen, Christian B; Ashraf, Raja Shahid; Schroeder, Bob C; D'Angelo, Pasquale; Watkins, Scott E; Song, Kigook; Anthopoulos, Thomas D; McCulloch, Iain

2012-06-14

A series of benzotrithiophene-containing random terpolymers for polymer solar cells is reported. Through variations of the two other components in the terpolymers, the absorption profile and the frontier energy levels are optimized and maximum power conversion efficiencies are nearly doubled (5.14%) relative to the parent alternating copolymer.

Bioelectrochemical systems-driven directional ion transport enables low-energy water desalination, pollutant removal, and resource recovery.

PubMed

Chen, Xi; Liang, Peng; Zhang, Xiaoyuan; Huang, Xia

2016-09-01

Bioelectrochemical systems (BESs) are integrated water treatment technologies that generate electricity using organic matter in wastewater. In situ use of bioelectricity can direct the migration of ionic substances in a BES, thereby enabling water desalination, resource recovery, and valuable substance production. Recently, much attention has been placed on the microbial desalination cells in BESs to drive water desalination, and various configurations have optimized electricity generation and desalination performance and also coupled hydrogen production, heavy metal reduction, and other reactions. In addition, directional transport of other types of charged ions can remediate polluted groundwater, recover nutrient, and produce valuable substances. To better promote the practical application, the use of BESs as directional drivers of ionic substances requires further optimization to improve energy use efficiency and treatment efficacy. This article reviews existing researches on BES-driven directional ion transport to treat wastewater and identifies a few key factors involved in efficiency optimization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Intelligent sensor in control systems for objects with changing thermophysical properties

NASA Astrophysics Data System (ADS)

Belousov, O. A.; Muromtsev, D. Yu; Belyaev, M. P.

2018-04-01

The control of heat devices in a wide temperature range given thermophysical properties of an object is a topical issue. Optimal control systems of electric furnaces have to meet strict requirements in terms of accuracy of production procedures and efficiency of energy consumption. The fulfillment of these requirements is possible only if the dynamics model describing adequately the processes occurring in the furnaces is used to calculate the optimal control actions. One of the types of electric furnaces is the electric chamber furnace intended for heat treatment of various materials at temperatures from thousands of degrees Celsius and above. To solve the above-mentioned problem and to determine its place in the system of energy-efficient control of dynamic modes in the electric furnace, we propose the concept of an intelligent sensor and a method of synthesizing variables on sets of functioning states. The use of synthesis algorithms for optimal control in real time ensures the required accuracy when operating under different conditions and operating modes of the electric chamber furnace.

An improved reaction path optimization method using a chain of conformations

NASA Astrophysics Data System (ADS)

Asada, Toshio; Sawada, Nozomi; Nishikawa, Takuya; Koseki, Shiro

2018-05-01

The efficient fast path optimization (FPO) method is proposed to optimize the reaction paths on energy surfaces by using chains of conformations. No artificial spring force is used in the FPO method to ensure the equal spacing of adjacent conformations. The FPO method is applied to optimize the reaction path on two model potential surfaces. The use of this method enabled the optimization of the reaction paths with a drastically reduced number of optimization cycles for both potentials. It was also successfully utilized to define the MEP of the isomerization of the glycine molecule in water by FPO method.

Fast exploration of an optimal path on the multidimensional free energy surface

PubMed Central

Chen, Changjun

2017-01-01

In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules. PMID:28542475

Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks.

PubMed

Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

2016-01-04

Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks' activities in an uninterrupted and efficient manner.

Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks

PubMed Central

Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

2016-01-01

Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks’ activities in an uninterrupted and efficient manner. PMID:26742042

Microgrid Analysis Tools Summary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jimenez, Antonio; Haase, Scott G; Mathur, Shivani

2018-03-05

The over-arching goal of the Alaska Microgrid Partnership is to reduce the use of total imported fuel into communities to secure all energy services by at least 50% in Alaska's remote microgrids without increasing system life cycle costs while also improving overall system reliability, security, and resilience. One goal of the Alaska Microgrid Partnership is to investigate whether a combination of energy efficiency and high-contribution (from renewable energy) power systems can reduce total imported energy usage by 50% while reducing life cycle costs and improving reliability and resiliency. This presentation provides an overview of the following four renewable energy optimizationmore » tools. Information is from respective tool websites, tool developers, and author experience. Distributed Energy Resources Customer Adoption Model (DER-CAM) Microgrid Design Toolkit (MDT) Renewable Energy Optimization (REopt) Tool Hybrid Optimization Model for Electric Renewables (HOMER).« less

Optimized design of total energy systems: The RETE project

NASA Astrophysics Data System (ADS)

Alia, P.; Dallavalle, F.; Denard, C.; Sanson, F.; Veneziani, S.; Spagni, G.

1980-05-01

The RETE (Reggio Emilia Total Energy) project is discussed. The total energy system (TES) was developed to achieve the maximum quality matching on the thermal energy side between plant and user and perform an open scheme on the electrical energy side by connection with the Italian electrical network. The most significant qualitative considerations at the basis of the plant economic energy optimization and the selection of the operating criterion most fitting the user consumption characteristics and the external system constraints are reported. The design methodology described results in a TES that: in energy terms achieves a total efficiency evaluated on a yearly basis to be equal to about 78 percent and a fuel saving of about 28 percent and in economic terms allows a recovery of the investment required as to conventional solutions, in about seven years.

The latest developments and outlook for hydrogen liquefaction technology

NASA Astrophysics Data System (ADS)

Ohlig, K.; Decker, L.

2014-01-01

Liquefied hydrogen is presently mainly used for space applications and the semiconductor industry. While clean energy applications, for e.g. the automotive sector, currently contribute to this demand with a small share only, their demand may see a significant boost in the next years with the need for large scale liquefaction plants exceeding the current plant sizes by far. Hydrogen liquefaction for small scale plants with a maximum capacity of 3 tons per day (tpd) is accomplished with a Brayton refrigeration cycle using helium as refrigerant. This technology is characterized by low investment costs but lower process efficiency and hence higher operating costs. For larger plants, a hydrogen Claude cycle is used, characterized by higher investment but lower operating costs. However, liquefaction plants meeting the potentially high demand in the clean energy sector will need further optimization with regard to energy efficiency and hence operating costs. The present paper gives an overview of the currently applied technologies, including their thermodynamic and technical background. Areas of improvement are identified to derive process concepts for future large scale hydrogen liquefaction plants meeting the needs of clean energy applications with optimized energy efficiency and hence minimized operating costs. Compared to studies in this field, this paper focuses on application of new technology and innovative concepts which are either readily available or will require short qualification procedures. They will hence allow implementation in plants in the close future.

The potential of value management (VM) to improve the consideration of energy efficiency within pre-construction

NASA Astrophysics Data System (ADS)

Tahir, Mohamad Zamhari; Nawi, Mohd Nasrun Mohd; Rajemi, Mohamad Farizal

2016-08-01

Energy demand and consumption in buildings will rise rapidly in the near future because of several social economics factors and this situation occurs not only in developed countries but also in developing countries such as Malaysia. There is demand towards building with energy efficiency features at this time, however most of the current buildings types are still being constructed with conventional designs, thus contribute to inefficient of energy consumption during the operation stage of the building. This paper presents the concept and the application of Value Management (VM) approach and its potential to improve consideration of energy efficiency within pre-construction process. Based on the relevant literatures, VM has provides an efficient and effective delivery system to fulfill the objectives and client's requirements. Generally in this paper, VM is discussed and scrutinized with reference to previous studies to see how these concepts contribute to better optimize the energy consumption in a building by seeking the best value energy efficiency through the design and construction process. This paper will not draw any conclusion but rather a preliminary research to propose the most energy efficiency measures to reliably accomplish a function that will meet the client's needs, desires and expectations. For further research in future, simple quantitative industry survey and VM workshops will be conducted to validate and further improve the research.

Resource optimized TTSH-URA for multimedia stream authentication in swallowable-capsule-based wireless body sensor networks.

PubMed

Wang, Wei; Wang, Chunqiu; Zhao, Min

2014-03-01

To ease the burdens on the hospitalization capacity, an emerging swallowable-capsule technology has evolved to serve as a remote gastrointestinal (GI) disease examination technique with the aid of the wireless body sensor network (WBSN). Secure multimedia transmission in such a swallowable-capsule-based WBSN faces critical challenges including energy efficiency and content quality guarantee. In this paper, we propose a joint resource allocation and stream authentication scheme to maintain the best possible video quality while ensuring security and energy efficiency in GI-WBSNs. The contribution of this research is twofold. First, we establish a unique signature-hash (S-H) diversity approach in the authentication domain to optimize video authentication robustness and the authentication bit rate overhead over a wireless channel. Based on the full exploration of S-H authentication diversity, we propose a new two-tier signature-hash (TTSH) stream authentication scheme to improve the video quality by reducing authentication dependence overhead while protecting its integrity. Second, we propose to combine this authentication scheme with a unique S-H oriented unequal resource allocation (URA) scheme to improve the energy-distortion-authentication performance of wireless video delivery in GI-WBSN. Our analysis and simulation results demonstrate that the proposed TTSH with URA scheme achieves considerable gain in both authenticated video quality and energy efficiency.

A thermodynamic approach for selecting operating conditions in the design of reversible solid oxide cell energy systems

NASA Astrophysics Data System (ADS)

Wendel, Christopher H.; Kazempoor, Pejman; Braun, Robert J.

2016-01-01

Reversible solid oxide cell (ReSOC) systems are being increasingly considered for electrical energy storage, although much work remains before they can be realized, including cell materials development and system design optimization. These systems store electricity by generating a synthetic fuel in electrolysis mode and subsequently recover electricity by electrochemically oxidizing the stored fuel in fuel cell mode. System thermal management is improved by promoting methane synthesis internal to the ReSOC stack. Within this strategy, the cell-stack operating conditions are highly impactful on system performance and optimizing these parameters to suit both operating modes is critical to achieving high roundtrip efficiency. Preliminary analysis shows the thermoneutral voltage to be a useful parameter for analyzing ReSOC systems and the focus of this study is to quantitatively examine how it is affected by ReSOC operating conditions. The results reveal that the thermoneutral voltage is generally reduced by increased pressure, and reductions in temperature, fuel utilization, and hydrogen-to-carbon ratio. Based on the thermodynamic analysis, many different combinations of these operating conditions are expected to promote efficient energy storage. Pressurized systems can achieve high efficiency at higher temperature and fuel utilization, while non-pressurized systems may require lower stack temperature and suffer from reduced energy density.

Using qualitative methods to understand non-technological aspects of domestic energy efficiency

NASA Astrophysics Data System (ADS)

Ambrose, Aimee Rebecca

The overall aim of the collected published works is to investigate how different policy interventions in the field of energy efficiency (including zero carbon homes, low carbon heat networks, and domestic energy efficiency schemes) are experienced and made sense of by a range of key actors. A further aim is to understand these interventions in the context of existing theories within the field of domestic energy efficiency including socio-technical theory and Actor Network Theory. More specifically, this research advances existing knowledge in the following areas: The nature of the socio-technical challenges encountered in the introduction of more energy efficient buildings, and the importance of achieving a balance between socially acceptable and technically optimal environments. (Papers 2, 3, 4, 6 and 8). The value of qualitative research in gaining a more nuanced understanding of our relationship with the home and the implications of this for domestic energy efficiency interventions and the design of low energy buildings (all papers). The influence of tenure as determinant of access to a more energy efficient home and in particular, the stubborn and complex barriers to achieving higher standards of energy performance within the private rented sector. (Papers 1, 2, 3 and 4). The significance of identity, setting and notions of home in the context of domestic energy efficiency interventions. (Papers 1 and 4). As these themes suggest, this PhD is not just concerned with carbon reduction and energy saving as technical objects, but as a way of life. More specifically, it considers the interactions between the two and contends that technical or policy instruments, no matter how sophisticated, cannot succeed if they are not compatible with our ways of life (and ways of doing businesss) or if our ways of life cannot be reasonably adapted to acoomodate them.

Co-Optimization of Fuels and Engines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrell, John

2016-03-24

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a new DOE initiative focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) are designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, ten national laboratories, and numerous industry and academic partners to simultaneously tackle fuel and engine research and development (R&D) to maximize energymore » savings and on-road vehicle performance while dramatically reducing transportation-related petroleum consumption and greenhouse gas (GHG) emissions. This multi-year project will provide industry with the scientific underpinnings required to move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions. This presentation provides an overview of the project.« less

Improving Energy Efficiency in CNC Machining

NASA Astrophysics Data System (ADS)

Pavanaskar, Sushrut S.

We present our work on analyzing and improving the energy efficiency of multi-axis CNC milling process. Due to the differences in energy consumption behavior, we treat 3- and 5-axis CNC machines separately in our work. For 3-axis CNC machines, we first propose an energy model that estimates the energy requirement for machining a component on a specified 3-axis CNC milling machine. Our model makes machine-specific predictions of energy requirements while also considering the geometric aspects of the machining toolpath. Our model - and the associated software tool - facilitate direct comparison of various alternative toolpath strategies based on their energy-consumption performance. Further, we identify key factors in toolpath planning that affect energy consumption in CNC machining. We then use this knowledge to propose and demonstrate a novel toolpath planning strategy that may be used to generate new toolpaths that are inherently energy-efficient, inspired by research on digital micrography -- a form of computational art. For 5-axis CNC machines, the process planning problem consists of several sub-problems that researchers have traditionally solved separately to obtain an approximate solution. After illustrating the need to solve all sub-problems simultaneously for a truly optimal solution, we propose a unified formulation based on configuration space theory. We apply our formulation to solve a problem variant that retains key characteristics of the full problem but has lower dimensionality, allowing visualization in 2D. Given the complexity of the full 5-axis toolpath planning problem, our unified formulation represents an important step towards obtaining a truly optimal solution. With this work on the two types of CNC machines, we demonstrate that without changing the current infrastructure or business practices, machine-specific, geometry-based, customized toolpath planning can save energy in CNC machining.

Compact 200 kHz HHG source driven by a few-cycle OPCPA

NASA Astrophysics Data System (ADS)

Harth, Anne; Guo, Chen; Cheng, Yu-Chen; Losquin, Arthur; Miranda, Miguel; Mikaelsson, Sara; Heyl, Christoph M.; Prochnow, Oliver; Ahrens, Jan; Morgner, Uwe; L'Huillier, Anne; Arnold, Cord L.

2018-01-01

We present efficient high-order harmonic generation (HHG) based on a high-repetition rate, few-cycle, near infrared (NIR), carrier-envelope phase stable, optical parametric chirped pulse amplifier (OPCPA), emitting 6 fs pulses with 9 μJ pulse energy. In krypton, we reach conversion efficiencies from the NIR to the extreme ultraviolet (XUV) radiation pulse energy on the order of ˜10-6 with less than 3 μJ driving pulse energy. This is achieved by optimizing the OPCPA for a spatially and temporally clean pulse and by a specially designed high-pressure gas target. In the future, the high efficiency of the HHG source will be beneficial for high-repetition rate two-colour (NIR-XUV) pump-probe experiments, where the available pulse energy from the laser has to be distributed economically between pump and probe pulses.

Design of a portable artificial heart drive system based on efficiency analysis.

PubMed

Kitamura, T

1986-11-01

This paper discusses a computer simulation of a pneumatic portable piston-type artificial heart drive system with a linear d-c-motor. The purpose of the design is to obtain an artificial heart drive system with high efficiency and small dimensions to enhance portability. The design employs two factors contributing the total efficiency of the drive system. First, the dimensions of the pneumatic actuator were optimized under a cost function of the total efficiency. Second, the motor performance was studied in terms of efficiency. More than 50 percent of the input energy of the actuator with practical loads is consumed in the armature circuit in all linear d-c-motors with brushes. An optimal design is: the piston cross-sectional area of 10.5 cm2 cylinder longitudinal length of 10 cm. The total efficiency could be up to 25 percent by improving the gasket to reduce the frictional force.

How to harvest efficient laser from solar light

NASA Astrophysics Data System (ADS)

Zhao, Changming; Guan, Zhe; Zhang, Haiyang

2018-02-01

Solar Pumped Solid State Lasers (SPSSL) is a kind of solid state lasers that can transform solar light into laser directly, with the advantages of least energy transform procedure, higher energy transform efficiency, simpler structure, higher reliability, and longer lifetime, which is suitable for use in unmanned space system, for solar light is the only form of energy source in space. In order to increase the output power and improve the efficiency of SPSSL, we conducted intensive studies on the suitable laser material selection for solar pump, high efficiency/large aperture focusing optical system, the optimization of concave cavity as the second focusing system, laser material bonding and surface processing. Using bonded and grooved Nd:YAG rod as laser material, large aperture Fresnel lens as the first stage focusing element, concave cavity as the second stage focusing element, we finally got 32.1W/m2 collection efficiency, which is the highest collection efficiency in the world up to now.

Dense Array Optimization of Cross-Flow Turbines

NASA Astrophysics Data System (ADS)

Scherl, Isabel; Strom, Benjamin; Brunton, Steven; Polagye, Brian

2017-11-01

Cross-flow turbines, where the axis of rotation is perpendicular to the freestream flow, can be used to convert the kinetic energy in wind or water currents to electrical power. By taking advantage of mean and time-resolved wake structures, the optimal density of an array of cross-flow turbines has the potential for higher power output per unit area of land or sea-floor than an equivalent array of axial-flow turbines. In addition, dense arrays in tidal or river channels may be able to further elevate efficiency by exploiting flow confinement and surface proximity. In this work, a two-turbine array is optimized experimentally in a recirculating water channel. The spacing between turbines, as well as individual and coordinated turbine control strategies are optimized. Array efficiency is found to exceed the maximum efficiency for a sparse array (i.e., no interaction between turbines) for stream-wise rotor spacing of less than two diameters. Results are discussed in the context of wake measurements made behind a single rotor.

Upper Limits for Power Yield in Thermal, Chemical, and Electrochemical Systems

NASA Astrophysics Data System (ADS)

Sieniutycz, Stanislaw

2010-03-01

We consider modeling and power optimization of energy converters, such as thermal, solar and chemical engines and fuel cells. Thermodynamic principles lead to expressions for converter's efficiency and generated power. Efficiency equations serve to solve the problems of upgrading or downgrading a resource. Power yield is a cumulative effect in a system consisting of a resource, engines, and an infinite bath. While optimization of steady state systems requires using the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. The primary result of static optimization is the upper limit of power, whereas that of dynamic optimization is a finite-rate counterpart of classical reversible work (exergy). The latter quantity depends on the end state coordinates and a dissipation index, h, which is the Hamiltonian of the problem of minimum entropy production. In reacting systems, an active part of chemical affinity constitutes a major component of the overall efficiency. The theory is also applied to fuel cells regarded as electrochemical flow engines. Enhanced bounds on power yield follow, which are stronger than those predicted by the reversible work potential.

Improving the Performance of PbS Quantum Dot Solar Cells by Optimizing ZnO Window Layer

NASA Astrophysics Data System (ADS)

Yang, Xiaokun; Hu, Long; Deng, Hui; Qiao, Keke; Hu, Chao; Liu, Zhiyong; Yuan, Shengjie; Khan, Jahangeer; Li, Dengbing; Tang, Jiang; Song, Haisheng; Cheng, Chun

2017-04-01

Comparing with hot researches in absorber layer, window layer has attracted less attention in PbS quantum dot solar cells (QD SCs). Actually, the window layer plays a key role in exciton separation, charge drifting, and so on. Herein, ZnO window layer was systematically investigated for its roles in QD SCs performance. The physical mechanism of improved performance was also explored. It was found that the optimized ZnO films with appropriate thickness and doping concentration can balance the optical and electrical properties, and its energy band align well with the absorber layer for efficient charge extraction. Further characterizations demonstrated that the window layer optimization can help to reduce the surface defects, improve the heterojunction quality, as well as extend the depletion width. Compared with the control devices, the optimized devices have obtained an efficiency of 6.7% with an enhanced V oc of 18%, J sc of 21%, FF of 10%, and power conversion efficiency of 58%. The present work suggests a useful strategy to improve the device performance by optimizing the window layer besides the absorber layer.

The improvement of thermal characteristics of autoclave aerated concrete for energy efficient high-rise buildings application

NASA Astrophysics Data System (ADS)

Khavanov, Pavel; Fomina, Ekaterina; Kozhukhova, Natalia

2018-03-01

Nowadays, the problem of energy saving is very relevant. One of the ways to reduction energy consumption in construction materials production and construction of civil and industrial high-rise buildings is the application of claddings with heat-insulating performance. The concept of energy efficiency of high-rise buildings is closely related to environmental aspect and sustainability of applied construction materials; reducing service costs; energy saving and microclimate comfortability. A complexity of architectural and structural design as well as aesthetic characteristics of construction materials are also should be considered. The high interest focused on materials with combined properties. This work is oriented on the study of energy efficiency of buildings by improving heat-insulation and strength performance of autoclave aerated concrete. The applied method of sulfate activation of lime allows monitoring phase and structure formation in aerated concrete. The optimal mix design of aerated concrete with the compressive strength up to 8.5 MPa and decreased density up to 760 kg/m3 was proposed. Analysis of structure at macro-and microscale was performed as well as the criteria of an optimal porosity formation was considered a number, size, shape of pore and density of interior partition. SEM analysis and BET method were performed in this research work. The research results demonstrated the correlation between structure and vapor permeability resistance, also it was found that the increase of strength can lead to reduction of thermal conductivity.

Energy conservation in housing design using solar energy, mechanical system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bakir, N.M.W.

1985-01-01

This paper presents the first experimental full-scale house built by the Solar Energy Research Center of Baghdad to be heated and cooled by solar energy. The various architectural and environmental considerations which entered into the design process are discussed, as well as the range of passive techniques examined for their compatibility with the local climate and their ability to optimize the energy efficiency of the house. The mechanical systems which were ultimately implemented are described.

Optimization of Wireless Transceivers under Processing Energy Constraints

NASA Astrophysics Data System (ADS)

Wang, Gaojian; Ascheid, Gerd; Wang, Yanlu; Hanay, Oner; Negra, Renato; Herrmann, Matthias; Wehn, Norbert

2017-09-01

Focus of the article is on achieving maximum data rates under a processing energy constraint. For a given amount of processing energy per information bit, the overall power consumption increases with the data rate. When targeting data rates beyond 100 Gb/s, the system's overall power consumption soon exceeds the power which can be dissipated without forced cooling. To achieve a maximum data rate under this power constraint, the processing energy per information bit must be minimized. Therefore, in this article, suitable processing efficient transmission schemes together with energy efficient architectures and their implementations are investigated in a true cross-layer approach. Target use cases are short range wireless transmitters working at carrier frequencies around 60 GHz and bandwidths between 1 GHz and 10 GHz.

Distributed Coordination of Energy Storage with Distributed Generators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Tao; Wu, Di; Stoorvogel, Antonie A.

2016-07-18

With a growing emphasis on energy efficiency and system flexibility, a great effort has been made recently in developing distributed energy resources (DER), including distributed generators and energy storage systems. This paper first formulates an optimal coordination problem considering constraints at both system and device levels, including power balance constraint, generator output limits, storage energy and power capacity and charging/discharging efficiencies. An algorithm is then proposed to dynamically and automatically coordinate DERs in a distributed manner. With the proposed algorithm, the agent at each DER only maintains a local incremental cost and updates it through information exchange with a fewmore » neighbors, without relying on any central decision maker. Simulation results are used to illustrate and validate the proposed algorithm.« less

Self-Powered WSN for Distributed Data Center Monitoring

PubMed Central

Brunelli, Davide; Passerone, Roberto; Rizzon, Luca; Rossi, Maurizio; Sartori, Davide

2016-01-01

Monitoring environmental parameters in data centers is gathering nowadays increasing attention from industry, due to the need of high energy efficiency of cloud services. We present the design and the characterization of an energy neutral embedded wireless system, prototyped to monitor perpetually environmental parameters in servers and racks. It is powered by an energy harvesting module based on Thermoelectric Generators, which converts the heat dissipation from the servers. Starting from the empirical characterization of the energy harvester, we present a power conditioning circuit optimized for the specific application. The whole system has been enhanced with several sensors. An ultra-low-power micro-controller stacked over the energy harvesting provides an efficient power management. Performance have been assessed and compared with the analytical model for validation. PMID:26729135

Self-Powered WSN for Distributed Data Center Monitoring.

PubMed

Brunelli, Davide; Passerone, Roberto; Rizzon, Luca; Rossi, Maurizio; Sartori, Davide

2016-01-02

Monitoring environmental parameters in data centers is gathering nowadays increasing attention from industry, due to the need of high energy efficiency of cloud services. We present the design and the characterization of an energy neutral embedded wireless system, prototyped to monitor perpetually environmental parameters in servers and racks. It is powered by an energy harvesting module based on Thermoelectric Generators, which converts the heat dissipation from the servers. Starting from the empirical characterization of the energy harvester, we present a power conditioning circuit optimized for the specific application. The whole system has been enhanced with several sensors. An ultra-low-power micro-controller stacked over the energy harvesting provides an efficient power management. Performance have been assessed and compared with the analytical model for validation.

Efficient approach to obtain free energy gradient using QM/MM MD simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asada, Toshio; Koseki, Shiro; The Research Institute for Molecular Electronic Devices

2015-12-31

The efficient computational approach denoted as charge and atom dipole response kernel (CDRK) model to consider polarization effects of the quantum mechanical (QM) region is described using the charge response and the atom dipole response kernels for free energy gradient (FEG) calculations in the quantum mechanical/molecular mechanical (QM/MM) method. CDRK model can reasonably reproduce energies and also energy gradients of QM and MM atoms obtained by expensive QM/MM calculations in a drastically reduced computational time. This model is applied on the acylation reaction in hydrated trypsin-BPTI complex to optimize the reaction path on the free energy surface by means ofmore » FEG and the nudged elastic band (NEB) method.« less

Design and Control of Integrated Systems for Hydrogen Production and Power Generation

NASA Astrophysics Data System (ADS)

Georgis, Dimitrios

Growing concerns on CO2 emissions have led to the development of highly efficient power plants. Options for increased energy efficiencies include alternative energy conversion pathways, energy integration and process intensification. Solid oxide fuel cells (SOFC) constitute a promising alternative for power generation since they convert the chemical energy electrochemically directly to electricity. Their high operating temperature shows potential for energy integration with energy intensive units (e.g. steam reforming reactors). Although energy integration is an essential tool for increased efficiencies, it leads to highly complex process schemes with rich dynamic behavior, which are challenging to control. Furthermore, the use of process intensification for increased energy efficiency imposes an additional control challenge. This dissertation identifies and proposes solutions on design, operational and control challenges of integrated systems for hydrogen production and power generation. Initially, a study on energy integrated SOFC systems is presented. Design alternatives are identified, control strategies are proposed for each alternative and their validity is evaluated under different operational scenarios. The operational range of the proposed control strategies is also analyzed. Next, thermal management of water gas shift membrane reactors, which are a typical application of process intensification, is considered. Design and operational objectives are identified and a control strategy is proposed employing advanced control algorithms. The performance of the proposed control strategy is evaluated and compared with classical control strategies. Finally SOFC systems for combined heat and power applications are considered. Multiple recycle loops are placed to increase design flexibility. Different operational objectives are identified and a nonlinear optimization problem is formulated. Optimal designs are obtained and their features are discussed and compared. The results of the dissertation provide a deeper understanding on the design, operational and control challenges of the above systems and can potentially guide further commercialization efforts. In addition to this, the results can be generalized and used for applications from the transportation and residential sector to large--scale power plants.

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

PubMed

Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yazawa, Kazuaki; Shakouri, Ali

The energy conversion efficiency of today’s thermoelectric generators is significantly lower than that of conventional mechanical engines. Almost all of the existing research is focused on materials to improve the conversion efficiency. Here we propose a general framework to study the cost-efficiency trade-off for thermoelectric power generation. A key factor is the optimization of thermoelectric modules together with their heat source and heat sinks. Full electrical and thermal co-optimization yield a simple analytical expression for optimum design. Based on this model, power output per unit mass can be maximized. We show that the fractional area coverage of thermoelectric elements inmore » a module could play a significant role in reducing the cost of power generation systems.« less

Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem

NASA Astrophysics Data System (ADS)

Tang, Dunbing; Dai, Min

2015-09-01

The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.

The Power of Flexibility: Autonomous Agents That Conserve Energy in Commercial Buildings

NASA Astrophysics Data System (ADS)

Kwak, Jun-young

Agent-based systems for energy conservation are now a growing area of research in multiagent systems, with applications ranging from energy management and control on the smart grid, to energy conservation in residential buildings, to energy generation and dynamic negotiations in distributed rural communities. Contributing to this area, my thesis presents new agent-based models and algorithms aiming to conserve energy in commercial buildings. More specifically, my thesis provides three sets of algorithmic contributions. First, I provide online predictive scheduling algorithms to handle massive numbers of meeting/event scheduling requests considering flexibility , which is a novel concept for capturing generic user constraints while optimizing the desired objective. Second, I present a novel BM-MDP ( Bounded-parameter Multi-objective Markov Decision Problem) model and robust algorithms for multi-objective optimization under uncertainty both at the planning and execution time. The BM-MDP model and its robust algorithms are useful in (re)scheduling events to achieve energy efficiency in the presence of uncertainty over user's preferences. Third, when multiple users contribute to energy savings, fair division of credit for such savings to incentivize users for their energy saving activities arises as an important question. I appeal to cooperative game theory and specifically to the concept of Shapley value for this fair division. Unfortunately, scaling up this Shapley value computation is a major hindrance in practice. Therefore, I present novel approximation algorithms to efficiently compute the Shapley value based on sampling and partitions and to speed up the characteristic function computation. These new models have not only advanced the state of the art in multiagent algorithms, but have actually been successfully integrated within agents dedicated to energy efficiency: SAVES, TESLA and THINC. SAVES focuses on the day-to-day energy consumption of individuals and groups in commercial buildings by reactively suggesting energy conserving alternatives. TESLA takes a long-range planning perspective and optimizes overall energy consumption of a large number of group events or meetings together. THINC provides an end-to-end integration within a single agent of energy efficient scheduling, rescheduling and credit allocation. While SAVES, TESLA and THINC thus differ in their scope and applicability, they demonstrate the utility of agent-based systems in actually reducing energy consumption in commercial buildings. I evaluate my algorithms and agents using extensive analysis on data from over 110,000 real meetings/events at multiple educational buildings including the main libraries at the University of Southern California. I also provide results on simulations and real-world experiments, clearly demonstrating the power of agent technology to assist human users in saving energy in commercial buildings.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

Energy Saving Melting and Revert Reduction Technology: Melting Efficiency in Die Casting Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

David Schwam

2012-12-15

This project addressed multiple aspects of the aluminum melting and handling in die casting operations, with the objective of increasing the energy efficiency while improving the quality of the molten metal. The efficiency of melting has always played an important role in the profitability of aluminum die casting operations. Consequently, die casters need to make careful choices in selecting and operating melting equipment and procedures. The capital cost of new melting equipment with higher efficiency can sometimes be recovered relatively fast when it replaces old melting equipment with lower efficiency. Upgrades designed to improve energy efficiency of existing equipment maymore » be well justified. Energy efficiency is however not the only factor in optimizing melting operations. Melt losses and metal quality are also very important. Selection of melting equipment has to take into consideration the specific conditions at the die casting shop such as availability of floor space, average quantity of metal used as well as the ability to supply more metal during peaks in demand. In all these cases, it is essential to make informed decisions based on the best available data.« less

Optimization and economic evaluation of industrial gas production and combined heat and power generation from gasification of corn stover and distillers grains.

PubMed

Kumar, Ajay; Demirel, Yasar; Jones, David D; Hanna, Milford A

2010-05-01

Thermochemical gasification is one of the most promising technologies for converting biomass into power, fuels and chemicals. The objectives of this study were to maximize the net energy efficiency for biomass gasification, and to estimate the cost of producing industrial gas and combined heat and power (CHP) at a feedrate of 2000kg/h. Aspen Plus-based model for gasification was combined with a CHP generation model, and optimized using corn stover and dried distillers grains with solubles (DDGS) as the biomass feedstocks. The cold gas efficiencies for gas production were 57% and 52%, respectively, for corn stover and DDGS. The selling price of gas was estimated to be $11.49 and $13.08/GJ, respectively, for corn stover and DDGS. For CHP generation, the electrical and net efficiencies were as high as 37% and 88%, respectively, for corn stover and 34% and 78%, respectively, for DDGS. The selling price of electricity was estimated to be $0.1351 and $0.1287/kWh for corn stover and DDGS, respectively. Overall, high net energy efficiencies for gas and CHP production from biomass gasification can be achieved with optimized processing conditions. However, the economical feasibility of these conversion processes will depend on the relative local prices of fossil fuels. Copyright 2009 Elsevier Ltd. All rights reserved.

A highly efficient and compact long pulse Nd:YAG rod laser with 540 J of pulse energy for welding application.

PubMed

Choubey, Ambar; Vishwakarma, S C; Misra, Pushkar; Jain, R K; Agrawal, D K; Arya, R; Upadhyaya, B N; Oak, S M

2013-07-01

We have developed an efficient and high average power flash lamp pumped long pulse Nd:YAG laser capable of generating 1 kW of average output power with maximum 540 J of single pulse energy and 20 kW of peak power. The laser pulse duration can be varied from 1 to 40 ms and repetition rate from 1 to 100 Hz. A compact and robust laser pump chamber and resonator was designed to achieve this high average and peak power. It was found that this laser system provides highest single pulse energy as compared to other long pulsed Nd:YAG laser systems of similar rating. A slope efficiency of 5.4% has been achieved, which is on higher side for typical lamp pumped solid-state lasers. This system will be highly useful in laser welding of materials such as aluminium and titanium. We have achieved 4 mm deep penetration welding of these metals under optimized conditions of output power, pulse energy, and pulse duration. The laser resonator was optimized to provide stable operation from single shot to 100 Hz of repetition rate. The beam quality factor was measured to be M(2) ~ 91 and pulse-to-pulse stability of ±3% for the multimode operation. The laser beam was efficiently coupled through an optical fiber of 600 μm core diameter and 0.22 numerical aperture with power transmission of 90%.

Energy-cascade organic photovoltaic devices incorporating a host-guest architecture.

PubMed

Menke, S Matthew; Holmes, Russell J

2015-02-04

In planar heterojunction organic photovoltaic devices (OPVs), broad spectral coverage can be realized by incorporating multiple molecular absorbers in an energy-cascade architecture. Here, this approach is combined with a host-guest donor layer architecture previously shown to optimize exciton transport for the fluorescent organic semiconductor boron subphthalocyanine chloride (SubPc) when diluted in an optically transparent host. In order to maximize the absorption efficiency, energy-cascade OPVs that utilize both photoactive host and guest donor materials are examined using the pairing of SubPc and boron subnaphthalocyanine chloride (SubNc), respectively. In a planar heterojunction architecture, excitons generated on the SubPc host rapidly energy transfer to the SubNc guest, where they may migrate toward the dissociating, donor-acceptor interface. Overall, the incorporation of a photoactive host leads to a 13% enhancement in the short-circuit current density and a 20% enhancement in the power conversion efficiency relative to an optimized host-guest OPV combining SubNc with a nonabsorbing host. This work underscores the potential for further design refinements in planar heterojunction OPVs and demonstrates progress toward the effective separation of functionality between constituent OPV materials.

Energy Performance Monitoring and Optimization System for DoD Campuses

DTIC Science & Technology

2014-02-01

EPMO system exceeded the energy consumption reduction target of 20% and improved occupant thermal comfort by reducing the number of instances outside... thermal comfort constraints, and plant efficiency EW2011-42 Final Report 8 February 2014 in the same framework [30-33]. In this framework, 4-hour...conjunction with information such as: thermal comfort constraints, equipment constraints, energy performance objectives. All the information is

Monte Carlo treatment of resonance-radiation imprisonment in fluorescent lamps—revisited

NASA Astrophysics Data System (ADS)

Anderson, James B.

2016-12-01

We reported in 1985 a Monte Carlo treatment of the imprisonment of the 253.7 nm resonance radiation from mercury in the mercury-argon discharge of fluorescent lamps. The calculated spectra of the emitted radiation were found in good agreement with measured spectra. The addition of the isotope mercury-196 to natural mercury was found, also in agreement with experiments, to increase lamp efficiency. In this paper we report the extension of the earlier work with increased accuracy, analysis of photon exit-time distributions, recycling of energy released in quenching, analysis of dynamic similarity for different lamp sizes, variation of Mrozowski transfer rates, prediction and analysis of the hyperfine ultra-violet spectra, and optimization of tailored mercury isotope mixtures for increased lamp efficiency. The spectra were found insensitive to the extent of quenching and recycling. The optimized mixtures were found to increase efficiencies by as much as 5% for several lamp configurations. Optimization without increasing the mercury-196 fraction was found to increase efficiencies by nearly 1% for several configurations.

Optimal design and operation of solid oxide fuel cell systems for small-scale stationary applications

NASA Astrophysics Data System (ADS)

Braun, Robert Joseph

The advent of maturing fuel cell technologies presents an opportunity to achieve significant improvements in energy conversion efficiencies at many scales; thereby, simultaneously extending our finite resources and reducing "harmful" energy-related emissions to levels well below that of near-future regulatory standards. However, before realization of the advantages of fuel cells can take place, systems-level design issues regarding their application must be addressed. Using modeling and simulation, the present work offers optimal system design and operation strategies for stationary solid oxide fuel cell systems applied to single-family detached dwellings. A one-dimensional, steady-state finite-difference model of a solid oxide fuel cell (SOFC) is generated and verified against other mathematical SOFC models in the literature. Fuel cell system balance-of-plant components and costs are also modeled and used to provide an estimate of system capital and life cycle costs. The models are used to evaluate optimal cell-stack power output, the impact of cell operating and design parameters, fuel type, thermal energy recovery, system process design, and operating strategy on overall system energetic and economic performance. Optimal cell design voltage, fuel utilization, and operating temperature parameters are found using minimization of the life cycle costs. System design evaluations reveal that hydrogen-fueled SOFC systems demonstrate lower system efficiencies than methane-fueled systems. The use of recycled cell exhaust gases in process design in the stack periphery are found to produce the highest system electric and cogeneration efficiencies while achieving the lowest capital costs. Annual simulations reveal that efficiencies of 45% electric (LHV basis), 85% cogenerative, and simple economic paybacks of 5--8 years are feasible for 1--2 kW SOFC systems in residential-scale applications. Design guidelines that offer additional suggestions related to fuel cell-stack sizing and operating strategy (base-load or load-following and cogeneration or electric-only) are also presented.

Electromechanical conversion efficiency for dielectric elastomer generator in different energy harvesting cycles

NASA Astrophysics Data System (ADS)

Cao, Jian-Bo; E, Shi-Ju; Guo, Zhuang; Gao, Zhao; Luo, Han-Pin

2017-11-01

In order to improve electromechanical conversion efficiency for dielectric elastomer generators (DEG), on the base of studying DEG energy harvesting cycles of constant voltage, constant charge and constant electric field intensity, a new combined cycle mode and optimization theory in terms of the generating mechanism and electromechanical coupling process have been built. By controlling the switching point to achieve the best energy conversion cycle, the energy loss in the energy conversion process is reduced. DEG generating test bench which was used to carry out comparative experiments has been established. Experimental results show that the collected energy in constant voltage cycle, constant charge cycle and constant electric field intensity energy harvesting cycle decreases in turn. Due to the factors such as internal resistance losses, electrical losses and so on, actual energy values are less than the theoretical values. The electric energy conversion efficiency by combining constant electric field intensity cycle with constant charge cycle is larger than that of constant electric field intensity cycle. The relevant conclusions provide a basis for the further applications of DEG.

Collaboration Mechanism for Equipment Instruction of Multiple Energy Systems

NASA Astrophysics Data System (ADS)

Wang, Dong; Wang, Tuo; Wang, Qi; Zhang, Zhao; Zhao, Mingyu; Wang, Yinghui

2018-01-01

When multiple energy systems execute optimization instructions simultaneously, and the same equipment is Shared, the instruction conflict may occur. Aiming at the above problems, taking into account the control objectives of each system, the characteristics of different systems, such as comprehensive clean energy, energy efficiency, and peak filling, etc., designed the instruction coordination mechanism for the daemon. This mechanism mainly acts on the main station of the system, and form a final optimization instruction. For some specific scenarios, the collaboration mechanism of unlocking the terminal is supplemented. The mechanism determines the specific execution instructions based on the arrival time of the instruction. Finally, the experiment in Tianjin eco-city shows that this algorithm can meet the instruction and collaboration requirements of multi-energy systems, and ensure the safe operation of the equipment.

Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

PubMed

Bellucci, Michael A; Coker, David F

2011-07-28

We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

Experimental study of a fuel cell power train for road transport application

NASA Astrophysics Data System (ADS)

Corbo, P.; Corcione, F. E.; Migliardini, F.; Veneri, O.

The development of fuel cell electric vehicles requires the on-board integration of fuel cell systems and electric energy storage devices, with an appropriate energy management system. The optimization of performance and efficiency needs an experimental analysis of the power train, which has to be effected in both stationary and transient conditions (including standard driving cycles). In this paper experimental results concerning the performance of a fuel cell power train are reported and discussed. In particular characterization results for a small sized fuel cell system (FCS), based on a 2.5 kW PEM stack, alone and coupled to an electric propulsion chain of 3.7 kW are presented and discussed. The control unit of the FCS allowed the main stack operative parameters (stoichiometric ratio, hydrogen and air pressure, temperature) to be varied and regulated in order to obtain optimized polarization and efficiency curves. Experimental runs effected on the power train during standard driving cycles have allowed the performance and efficiency of the individual components (fuel cell stack and auxiliaries, dc-dc converter, traction batteries, electric engine) to be evaluated, evidencing the role of output current and voltage of the dc-dc converter in directing the energy flows within the propulsion system.

Efficiency transfer using the GEANT4 code of CERN for HPGe gamma spectrometry.

PubMed

Chagren, S; Tekaya, M Ben; Reguigui, N; Gharbi, F

2016-01-01

In this work we apply the GEANT4 code of CERN to calculate the peak efficiency in High Pure Germanium (HPGe) gamma spectrometry using three different procedures. The first is a direct calculation. The second corresponds to the usual case of efficiency transfer between two different configurations at constant emission energy assuming a reference point detection configuration and the third, a new procedure, consists on the transfer of the peak efficiency between two detection configurations emitting the gamma ray in different energies assuming a "virtual" reference point detection configuration. No pre-optimization of the detector geometrical characteristics was performed before the transfer to test the ability of the efficiency transfer to reduce the effect of the ignorance on their real magnitude on the quality of the transferred efficiency. The obtained and measured efficiencies were found in good agreement for the two investigated methods of efficiency transfer. The obtained agreement proves that Monte Carlo method and especially the GEANT4 code constitute an efficient tool to obtain accurate detection efficiency values. The second investigated efficiency transfer procedure is useful to calibrate the HPGe gamma detector for any emission energy value for a voluminous source using one point source detection efficiency emitting in a different energy as a reference efficiency. The calculations preformed in this work were applied to the measurement exercise of the EUROMET428 project. A measurement exercise where an evaluation of the full energy peak efficiencies in the energy range 60-2000 keV for a typical coaxial p-type HpGe detector and several types of source configuration: point sources located at various distances from the detector and a cylindrical box containing three matrices was performed. Copyright © 2015 Elsevier Ltd. All rights reserved.

An optimization-based approach for facility energy management with uncertainties, and, Power portfolio optimization in deregulated electricity markets with risk management

NASA Astrophysics Data System (ADS)

Xu, Jun

Topic 1. An Optimization-Based Approach for Facility Energy Management with Uncertainties. Effective energy management for facilities is becoming increasingly important in view of the rising energy costs, the government mandate on the reduction of energy consumption, and the human comfort requirements. This part of dissertation presents a daily energy management formulation and the corresponding solution methodology for HVAC systems. The problem is to minimize the energy and demand costs through the control of HVAC units while satisfying human comfort, system dynamics, load limit constraints, and other requirements. The problem is difficult in view of the fact that the system is nonlinear, time-varying, building-dependent, and uncertain; and that the direct control of a large number of HVAC components is difficult. In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system. A method that combines Lagrangian relaxation, neural networks, stochastic dynamic programming, and heuristics is developed to predict the system dynamics and uncontrollable load, and to optimize the setpoints. Numerical testing and prototype implementation results show that our method can effectively reduce total costs, manage uncertainties, and shed the load, is computationally efficient. Furthermore, it is significantly better than existing methods. Topic 2. Power Portfolio Optimization in Deregulated Electricity Markets with Risk Management. In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, risks in such volatile markets, stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance but difficulty for an LSE to serve the load, maximize its profit, and manage risks. In this topic, a mid-term power portfolio optimization problem with risk management is presented. Key instruments are considered, risk terms based on semi-variances of spot market transactions are introduced, and penalties on load obligation violations are added to the objective function to improve algorithm convergence and constraint satisfaction. To overcome the inseparability of the resulting problem, a surrogate optimization framework is developed enabling a decomposition and coordination approach. Numerical testing results show that our method effectively provides decisions for various instruments to maximize profit, manage risks, and is computationally efficient.

Deployment-based lifetime optimization for linear wireless sensor networks considering both retransmission and discrete power control.

PubMed

Li, Ruiying; Ma, Wenting; Huang, Ning; Kang, Rui

2017-01-01

A sophisticated method for node deployment can efficiently reduce the energy consumption of a Wireless Sensor Network (WSN) and prolong the corresponding network lifetime. Pioneers have proposed many node deployment based lifetime optimization methods for WSNs, however, the retransmission mechanism and the discrete power control strategy, which are widely used in practice and have large effect on the network energy consumption, are often neglected and assumed as a continuous one, respectively, in the previous studies. In this paper, both retransmission and discrete power control are considered together, and a more realistic energy-consumption-based network lifetime model for linear WSNs is provided. Using this model, we then propose a generic deployment-based optimization model that maximizes network lifetime under coverage, connectivity and transmission rate success constraints. The more accurate lifetime evaluation conduces to a longer optimal network lifetime in the realistic situation. To illustrate the effectiveness of our method, both one-tiered and two-tiered uniformly and non-uniformly distributed linear WSNs are optimized in our case studies, and the comparisons between our optimal results and those based on relatively inaccurate lifetime evaluation show the advantage of our method when investigating WSN lifetime optimization problems.

A power management circuit with 50% efficiency and large load capacity for triboelectric nanogenerator

NASA Astrophysics Data System (ADS)

Bao, Dechun; Luo, Lichuan; Zhang, Zhaohua; Ren, Tianling

2017-09-01

Recently, triboelectric nanogenerators (TENGs), as a collection technology with characteristics of high reliability, high energy density and low cost, has attracted more and more attention. However, the energy coming from TENGs needs to be stored in a storage unit effectively due to its unstable ac output. The traditional energy storage circuit has an extremely low energy storage efficiency for TENGs because of their high internal impedance. This paper presents a new power management circuit used to optimize the energy using efficiency of TENGs, and realize large load capacity. The power management circuit mainly includes rectification storage circuit and DC-DC management circuit. A rotating TENG with maximal energy output of 106 mW at 170 rpm based on PCB is used for the experimental verification. Experimental results show that the power energy transforming to the storage capacitor reach up to 53 mW and the energy using efficiency is calculated as 50%. When different loading resistances range from 0.82 to 34.5 k {{Ω }} are connected to the storage capacitor in parallel, the power energy stored in the storage capacitor is all about 52.5 mW. Getting through the circuit, the power energy coming from the TENGs can be used to drive numerous conventional electronics, such as wearable watches.

Practical Study on HVAC Control Technology Based on the Learning Function and Optimum Multiple Objective Processes

NASA Astrophysics Data System (ADS)

Ueda, Haruka; Dazai, Ryota; Kaseda, Chosei; Ikaga, Toshiharu; Kato, Akihiro

Demand among large office buildings for the energy-saving benefits of the HVAC (Heating, Ventilating and Air-Conditioning) System are increasing as more and more people become concerned with global environmental issues. However, immoderate measures taken in the interest of energy conservation may encroach on the thermal comfort and productivity level of office workers. Building management should satisfy both indoor thermal comfort and energy conservation while adapting to the many regulatory, social, climate, and other changes that occur during the lifespan of the building. This paper demonstrates how optimal control of the HVAC system, based on data modeling and the multi-objective optimal method, achieves an efficient equilibrium between thermal comfort and energy conservation.

Vibration energy harvesting with polyphase AC transducers

NASA Astrophysics Data System (ADS)

McCullagh, James J.; Scruggs, Jeffrey T.; Asai, Takehiko

2016-04-01

Three-phase transduction affords certain advantages in the efficient electromechanical conversion of energy, especially at higher power scales. This paper considers the use of a three-phase electric machine for harvesting energy from vibrations. We consider the use of vector control techniques, which are common in the area of industrial electronics, for optimizing the feedback loops in a stochastically-excited energy harvesting system. To do this, we decompose the problem into two separate feedback loops for direct and quadrature current components, and illustrate how each might be separately optimized to maximize power output. In a simple analytical example, we illustrate how these techniques might be used to gain insight into the tradeoffs in the design of the electronic hardware and the choice of bus voltage.

Multistage Stochastic Programming and its Applications in Energy Systems Modeling and Optimization

NASA Astrophysics Data System (ADS)

Golari, Mehdi

Electric energy constitutes one of the most crucial elements to almost every aspect of life of people. The modern electric power systems face several challenges such as efficiency, economics, sustainability, and reliability. Increase in electrical energy demand, distributed generations, integration of uncertain renewable energy resources, and demand side management are among the main underlying reasons of such growing complexity. Additionally, the elements of power systems are often vulnerable to failures because of many reasons, such as system limits, weak conditions, unexpected events, hidden failures, human errors, terrorist attacks, and natural disasters. One common factor complicating the operation of electrical power systems is the underlying uncertainties from the demands, supplies and failures of system components. Stochastic programming provides a mathematical framework for decision making under uncertainty. It enables a decision maker to incorporate some knowledge of the intrinsic uncertainty into the decision making process. In this dissertation, we focus on application of two-stage and multistage stochastic programming approaches to electric energy systems modeling and optimization. Particularly, we develop models and algorithms addressing the sustainability and reliability issues in power systems. First, we consider how to improve the reliability of power systems under severe failures or contingencies prone to cascading blackouts by so called islanding operations. We present a two-stage stochastic mixed-integer model to find optimal islanding operations as a powerful preventive action against cascading failures in case of extreme contingencies. Further, we study the properties of this problem and propose efficient solution methods to solve this problem for large-scale power systems. We present the numerical results showing the effectiveness of the model and investigate the performance of the solution methods. Next, we address the sustainability issue considering the integration of renewable energy resources into production planning of energy-intensive manufacturing industries. Recently, a growing number of manufacturing companies are considering renewable energies to meet their energy requirements to move towards green manufacturing as well as decreasing their energy costs. However, the intermittent nature of renewable energies imposes several difficulties in long term planning of how to efficiently exploit renewables. In this study, we propose a scheme for manufacturing companies to use onsite and grid renewable energies provided by their own investments and energy utilities as well as conventional grid energy to satisfy their energy requirements. We propose a multistage stochastic programming model and study an efficient solution method to solve this problem. We examine the proposed framework on a test case simulated based on a real-world semiconductor company. Moreover, we evaluate long-term profitability of such scheme via so called value of multistage stochastic programming.

Climate impact analysis of waste treatment scenarios--thermal treatment of commercial and pretreated waste versus landfilling in Austria.

PubMed

Ragossnig, A M; Wartha, C; Pomberger, R

2009-11-01

A major challenge for modern waste management lies in a smart integration of waste-to-energy installations in local energy systems in such a way that the energy efficiency of the waste-to-energy plant is optimized and that the energy contained in the waste is, therefore, optimally utilized. The extent of integration of thermal waste treatment processes into regular energy supply systems plays a major role with regard to climate control. In this research, the specific waste management situation looked at scenarios aiming at maximizing the energy recovery from waste (i.e. actual scenario and waste-to-energy process with 75% energy efficiency [22.5% electricity, 52.5% heat]) yield greenhouse gas emission savings due to the fact that more greenhouse gas emissions are avoided in the energy sector than caused by the various waste treatment processes. Comparing dedicated waste-to-energy-systems based on the combined heat and power (CHP) process with concepts based on sole electricity production, the energy efficiency proves to be crucial with regard to climate control. This underlines the importance of choosing appropriate sites for waste-to-energy-plants. This research was looking at the effect with regard to the climate impact of various waste management scenarios that could be applied alternatively by a private waste management company in Austria. The research is, therefore, based on a specific set of data for the waste streams looked at (waste characteristics, logistics needed, etc.). Furthermore, the investigated scenarios have been defined based on the actual available alternatives with regard to the usage of treatment plants for this specific company. The standard scenarios for identifying climate impact implications due to energy recovery from waste are based on the respective marginal energy data for the power and heat generation facilities/industrial processes in Austria.

Spot-Scanning Proton Arc (SPArc) Therapy: The First Robust and Delivery-Efficient Spot-Scanning Proton Arc Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Xuanfeng, E-mail: Xuanfeng.ding@beaumont.org; Li, Xiaoqiang; Zhang, J. Michele

Purpose: To present a novel robust and delivery-efficient spot-scanning proton arc (SPArc) therapy technique. Methods and Materials: A SPArc optimization algorithm was developed that integrates control point resampling, energy layer redistribution, energy layer filtration, and energy layer resampling. The feasibility of such a technique was evaluated using sample patients: 1 patient with locally advanced head and neck oropharyngeal cancer with bilateral lymph node coverage, and 1 with a nonmobile lung cancer. Plan quality, robustness, and total estimated delivery time were compared with the robust optimized multifield step-and-shoot arc plan without SPArc optimization (Arc{sub multi-field}) and the standard robust optimized intensity modulatedmore » proton therapy (IMPT) plan. Dose-volume histograms of target and organs at risk were analyzed, taking into account the setup and range uncertainties. Total delivery time was calculated on the basis of a 360° gantry room with 1 revolutions per minute gantry rotation speed, 2-millisecond spot switching time, 1-nA beam current, 0.01 minimum spot monitor unit, and energy layer switching time of 0.5 to 4 seconds. Results: The SPArc plan showed potential dosimetric advantages for both clinical sample cases. Compared with IMPT, SPArc delivered 8% and 14% less integral dose for oropharyngeal and lung cancer cases, respectively. Furthermore, evaluating the lung cancer plan compared with IMPT, it was evident that the maximum skin dose, the mean lung dose, and the maximum dose to ribs were reduced by 60%, 15%, and 35%, respectively, whereas the conformity index was improved from 7.6 (IMPT) to 4.0 (SPArc). The total treatment delivery time for lung and oropharyngeal cancer patients was reduced by 55% to 60% and 56% to 67%, respectively, when compared with Arc{sub multi-field} plans. Conclusion: The SPArc plan is the first robust and delivery-efficient proton spot-scanning arc therapy technique, which could potentially be implemented into routine clinical practice.« less

A new wind energy conversion system

NASA Technical Reports Server (NTRS)

Smetana, F. O.

1975-01-01

It is presupposed that vertical axis wind energy machines will be superior to horizontal axis machines on a power output/cost basis and the design of a new wind energy machine is presented. The design employs conical cones with sharp lips and smooth surfaces to promote maximum drag and minimize skin friction. The cones are mounted on a vertical axis in such a way as to assist torque development. Storing wind energy as compressed air is thought to be optimal and reasons are: (1) the efficiency of compression is fairly high compared to the conversion of mechanical energy to electrical energy in storage batteries; (2) the release of stored energy through an air motor has high efficiency; and (3) design, construction, and maintenance of an all-mechanical system is usually simpler than for a mechanical to electrical conversion system.

Economic challenges of hybrid microgrid: An analysis and approaches for rural electrification

NASA Astrophysics Data System (ADS)

Habibullah, Mohammad; Mahmud, Khizir; Koçar, Günnur; Islam, A. K. M. Sadrul; Salehin, Sayedus

2017-06-01

This paper focuses on the integration of three renewable resources: biogas, wind energy and solar energy, utilizing solar PV panels, a biogas generator, and a wind turbine, respectively, to analyze the technical and economic challenges of a hybrid micro-gird. The integration of these sources has been analyzed and optimized based on realistic data for a real location. Different combinations of these sources have been analyzed to find out the optimized combination based on the efficiency and the minimum cost of electricity (COE). Wind and solar energy are considered as the primary sources of power generation during off-peak hours, and any excess power is used to charge a battery bank. During peak hours, biogas generators produce power to support the additional demand. A business strategy to implement the integrated optimized system in rural areas is discussed.

A global optimization method synthesizing heat transfer and thermodynamics for the power generation system with Brayton cycle

NASA Astrophysics Data System (ADS)

Fu, Rong-Huan; Zhang, Xing

2016-09-01

Supercritical carbon dioxide operated in a Brayton cycle offers a numerous of potential advantages for a power generation system, and a lot of thermodynamics analyses have been conducted to increase its efficiency. Because there are a lot of heat-absorbing and heat-lossing subprocesses in a practical thermodynamic cycle and they are implemented by heat exchangers, it will increase the gross efficiency of the whole power generation system to optimize the system combining thermodynamics and heat transfer theory. This paper analyzes the influence of the performance of heat exchangers on the actual efficiency of an ideal Brayton cycle with a simple configuration, and proposes a new method to optimize the power generation system, which aims at the minimum energy consumption. Although the method is operated only for the ideal working fluid in this paper, its merits compared to that only with thermodynamic analysis are fully shown.

Optimal control for the sun-powered airplane with taking into account efficiency of onboard accumulator charging-discharging and charge limits

NASA Astrophysics Data System (ADS)

Serokhvostov, S. V.; Churkina, T. E.

2018-06-01

The problem of optimal control for the aircraft with the electric powerplant and solar cells for the multiday flight is investigated using the more precise equation of motion comparing to the previous investigations. The cases of some restrictions on aircraft energy storage and peculiarities of its charge and discharge are also analyzed. Pontryagin's maximum principle is utilized. Optimal trajectories were obtained for the cases considered.

Porphyrin-sensitized solar cells: systematic molecular optimization, coadsorption and cosensitization.

PubMed

Song, Heli; Liu, Qingyun; Xie, Yongshu

2018-02-15

As a promising low-cost solar energy conversion technique, dye-sensitized solar cells have undergone spectacular development since 1991. For practical applications, improvement of power conversion efficiency has always been one of the major research topics. Porphyrins are outstanding sensitizers endowed with strong sunlight harvesting ability in the visible region and multiple reaction sites available for functionalization. However, judicious molecular design in consideration of light-harvest, energy levels, operational dynamics, adsorption geometry and suppression of back reactions is specifically required for achieving excellent photovoltaic performance. This feature article highlights some of the recently developed porphyrin sensitizers, especially focusing on the systematic dye structure optimization approach in combination with coadsorption and cosensitization methods in pursuing higher efficiencies. Herein, we expect to provide more insights into the structure-performance correlation and molecular engineering strategies in a stepwise manner.

NREL Evaluates Performance of Fast-Charge Electric Buses

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-09-16

This real-world performance evaluation is designed to enhance understanding of the overall usage and effectiveness of electric buses in transit operation and to provide unbiased technical information to other agencies interested in adding such vehicles to their fleets. Initial results indicate that the electric buses under study offer significant fuel and emissions savings. The final results will help Foothill Transit optimize the energy-saving potential of its transit fleet. NREL's performance evaluations help vehicle manufacturers fine-tune their designs and help fleet managers select fuel-efficient, low-emission vehicles that meet their bottom line and operational goals. help Foothill Transit optimize the energy-saving potentialmore » of its transit fleet. NREL's performance evaluations help vehicle manufacturers fine-tune their designs and help fleet managers select fuel-efficient, low-emission vehicles that meet their bottom line and operational goals.« less

Geometric integration in Born-Oppenheimer molecular dynamics.

PubMed

Odell, Anders; Delin, Anna; Johansson, Börje; Cawkwell, Marc J; Niklasson, Anders M N

2011-12-14

Geometric integration schemes for extended Lagrangian self-consistent Born-Oppenheimer molecular dynamics, including a weak dissipation to remove numerical noise, are developed and analyzed. The extended Lagrangian framework enables the geometric integration of both the nuclear and electronic degrees of freedom. This provides highly efficient simulations that are stable and energy conserving even under incomplete and approximate self-consistent field (SCF) convergence. We investigate three different geometric integration schemes: (1) regular time reversible Verlet, (2) second order optimal symplectic, and (3) third order optimal symplectic. We look at energy conservation, accuracy, and stability as a function of dissipation, integration time step, and SCF convergence. We find that the inclusion of dissipation in the symplectic integration methods gives an efficient damping of numerical noise or perturbations that otherwise may accumulate from finite arithmetics in a perfect reversible dynamics. © 2011 American Institute of Physics

Fine-Tuning the Energy Levels of a Nonfullerene Small-Molecule Acceptor to Achieve a High Short-Circuit Current and a Power Conversion Efficiency over 12% in Organic Solar Cells.

PubMed

Kan, Bin; Zhang, Jiangbin; Liu, Feng; Wan, Xiangjian; Li, Chenxi; Ke, Xin; Wang, Yunchuang; Feng, Huanran; Zhang, Yamin; Long, Guankui; Friend, Richard H; Bakulin, Artem A; Chen, Yongsheng

2018-01-01

Organic solar cell optimization requires careful balancing of current-voltage output of the materials system. Here, such optimization using ultrafast spectroscopy as a tool to optimize the material bandgap without altering ultrafast photophysics is reported. A new acceptor-donor-acceptor (A-D-A)-type small-molecule acceptor NCBDT is designed by modification of the D and A units of NFBDT. Compared to NFBDT, NCBDT exhibits upshifted highest occupied molecular orbital (HOMO) energy level mainly due to the additional octyl on the D unit and downshifted lowest unoccupied molecular orbital (LUMO) energy level due to the fluorination of A units. NCBDT has a low optical bandgap of 1.45 eV which extends the absorption range toward near-IR region, down to ≈860 nm. However, the 60 meV lowered LUMO level of NCBDT hardly changes the V oc level, and the elevation of the NCBDT HOMO does not have a substantial influence on the photophysics of the materials. Thus, for both NCBDT- and NFBDT-based systems, an unusually slow (≈400 ps) but ultimately efficient charge generation mediated by interfacial charge-pair states is observed, followed by effective charge extraction. As a result, the PBDB-T:NCBDT devices demonstrate an impressive power conversion efficiency over 12%-among the best for solution-processed organic solar cells. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The effects of relative food item size on optimal tooth cusp sharpness during brittle food item processing

PubMed Central

Berthaume, Michael A.; Dumont, Elizabeth R.; Godfrey, Laurie R.; Grosse, Ian R.

2014-01-01

Teeth are often assumed to be optimal for their function, which allows researchers to derive dietary signatures from tooth shape. Most tooth shape analyses normalize for tooth size, potentially masking the relationship between relative food item size and tooth shape. Here, we model how relative food item size may affect optimal tooth cusp radius of curvature (RoC) during the fracture of brittle food items using a parametric finite-element (FE) model of a four-cusped molar. Morphospaces were created for four different food item sizes by altering cusp RoCs to determine whether optimal tooth shape changed as food item size changed. The morphospaces were also used to investigate whether variation in efficiency metrics (i.e. stresses, energy and optimality) changed as food item size changed. We found that optimal tooth shape changed as food item size changed, but that all optimal morphologies were similar, with one dull cusp that promoted high stresses in the food item and three cusps that acted to stabilize the food item. There were also positive relationships between food item size and the coefficients of variation for stresses in food item and optimality, and negative relationships between food item size and the coefficients of variation for stresses in the enamel and strain energy absorbed by the food item. These results suggest that relative food item size may play a role in selecting for optimal tooth shape, and the magnitude of these selective forces may change depending on food item size and which efficiency metric is being selected. PMID:25320068

Hovering efficiency comparison of rotary and flapping flight for rigid rectangular wings via dimensionless multi-objective optimization.

PubMed

Bayiz, Yagiz; Ghanaatpishe, Mohammad; Fathy, Hosam; Cheng, Bo

2018-05-08

In this work, a multi-objective optimization framework is developed for optimizing low Reynolds number ([Formula: see text]) hovering flight. This framework is then applied to compare the efficiency of rigid revolving and flapping wings with rectangular shape under varying [Formula: see text] and Rossby number ([Formula: see text], or aspect ratio). The proposed framework is capable of generating sets of optimal solutions and Pareto fronts for maximizing the lift coefficient and minimizing the power coefficient in dimensionless space, explicitly revealing the trade-off between lift generation and power consumption. The results indicate that revolving wings are more efficient when the required average lift coefficient [Formula: see text] is low (<1 for [Formula: see text] and  <1.6 for [Formula: see text]), while flapping wings are more efficient in achieving higher [Formula: see text]. With the dimensionless power loading as the single-objective performance measure to be maximized, rotary flight is more efficient than flapping wings for [Formula: see text] regardless of the amount of energy storage assumed in the flapping wing actuation mechanism, while flapping flight is more efficient for [Formula: see text]. It is observed that wings with low [Formula: see text] perform better when higher [Formula: see text] is needed, whereas higher [Formula: see text] cases are more efficient at [Formula: see text] regions. However, for the selected geometry and [Formula: see text], the efficiency is weakly dependent on [Formula: see text] when the dimensionless power loading is maximized.

Connectivity-enhanced route selection and adaptive control for the Chevrolet Volt

DOE PAGES

Gonder, Jeffrey; Wood, Eric; Rajagopalan, Sai

2016-01-01

The National Renewable Energy Laboratory and General Motors evaluated connectivity-enabled efficiency enhancements for the Chevrolet Volt. A high-level model was developed to predict vehicle fuel and electricity consumption based on driving characteristics and vehicle state inputs. These techniques were leveraged to optimize energy efficiency via green routing and intelligent control mode scheduling, which were evaluated using prospective driving routes between tens of thousands of real-world origin/destination pairs. The overall energy savings potential of green routing and intelligent mode scheduling was estimated at 5% and 3%, respectively. Furthermore, these represent substantial opportunities considering that they only require software adjustments to implement.

Simulation of a Novel Single-column Cryogenic Air Separation Process Using LNG Cold Energy

NASA Astrophysics Data System (ADS)

Jieyu, Zheng; Yanzhong, Li; Guangpeng, Li; Biao, Si

In this paper, a novel single-column air separation process is proposed with the implementation of heat pump technique and introduction of LNG coldenergy. The proposed process is verifiedand optimized through simulation on the Aspen Hysys® platform. Simulation results reveal that thepower consumption per unit mass of liquid productis around 0.218 kWh/kg, and the total exergy efficiency of the systemis 0.575. According to the latest literatures, an energy saving of 39.1% is achieved compared with those using conventional double-column air separation units.The introduction of LNG cold energy is an effective way to increase the system efficiency.

Optimization of porous microchannel heat exchanger

NASA Astrophysics Data System (ADS)

Kozhukhov, N. N.; Konovalov, D. A.

2017-11-01

The technical progress in information and communication sphere leads to a sharp increase in the use of radio electronic devices. Functioning of radio electronics is accompanied by release of thermal energy, which must be diverted from the heat-stressed element. Moreover, using of electronics at negative temperatures, on the contrary, requires supply of a certain amount of heat to start the system. There arises the task of creating a system that allows both to supply and to divert the necessary amount of thermal energy. The development of complex thermostabilization systems for radio electronic equipment is due to increasing the efficiency of each of its elements separately. For more efficient operation of a heat exchanger, which directly affects the temperature of the heat-stressed element, it is necessary to calculate the mode characteristics and to take into account the effect of its design parameters. The results of optimizing the microchannel heat exchanger are presented in the article. The target optimization functions are the mass, pressure drop and temperature. The parameters of optimization are the layout of porous fins, their geometric dimensions and coolant flow. For the given conditions, the optimum variant of porous microchannel heat exchanger is selected.

OLTARIS: An Efficient Web-Based Tool for Analyzing Materials Exposed to Space Radiation

NASA Technical Reports Server (NTRS)

Slaba, Tony; McMullen, Amelia M.; Thibeault, Sheila A.; Sandridge, Chris A.; Clowdsley, Martha S.; Blatting, Steve R.

2011-01-01

The near-Earth space radiation environment includes energetic galactic cosmic rays (GCR), high intensity proton and electron belts, and the potential for solar particle events (SPE). These sources may penetrate shielding materials and deposit significant energy in sensitive electronic devices on board spacecraft and satellites. Material and design optimization methods may be used to reduce the exposure and extend the operational lifetime of individual components and systems. Since laboratory experiments are expensive and may not cover the range of particles and energies relevant for space applications, such optimization may be done computationally with efficient algorithms that include the various constraints placed on the component, system, or mission. In the present work, the web-based tool OLTARIS (On-Line Tool for the Assessment of Radiation in Space) is presented, and the applicability of the tool for rapidly analyzing exposure levels within either complicated shielding geometries or user-defined material slabs exposed to space radiation is demonstrated. An example approach for material optimization is also presented. Slabs of various advanced multifunctional materials are defined and exposed to several space radiation environments. The materials and thicknesses defining each layer in the slab are then systematically adjusted to arrive at an optimal slab configuration.

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2011-01-01

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

Optimizing the Energy and Throughput of a Water-Quality Monitoring System.

PubMed

Olatinwo, Segun O; Joubert, Trudi-H

2018-04-13

This work presents a new approach to the maximization of energy and throughput in a wireless sensor network (WSN), with the intention of applying the approach to water-quality monitoring. Water-quality monitoring using WSN technology has become an interesting research area. Energy scarcity is a critical issue that plagues the widespread deployment of WSN systems. Different power supplies, harvesting energy from sustainable sources, have been explored. However, when energy-efficient models are not put in place, energy harvesting based WSN systems may experience an unstable energy supply, resulting in an interruption in communication, and low system throughput. To alleviate these problems, this paper presents the joint maximization of the energy harvested by sensor nodes and their information-transmission rate using a sum-throughput technique. A wireless information and power transfer (WIPT) method is considered by harvesting energy from dedicated radio frequency sources. Due to the doubly near-far condition that confronts WIPT systems, a new WIPT system is proposed to improve the fairness of resource utilization in the network. Numerical simulation results are presented to validate the mathematical formulations for the optimization problem, which maximize the energy harvested and the overall throughput rate. Defining the performance metrics of achievable throughput and fairness in resource sharing, the proposed WIPT system outperforms an existing state-of-the-art WIPT system, with the comparison based on numerical simulations of both systems. The improved energy efficiency of the proposed WIPT system contributes to addressing the problem of energy scarcity.

Optimizing the Energy and Throughput of a Water-Quality Monitoring System

PubMed Central

Olatinwo, Segun O.

2018-01-01

This work presents a new approach to the maximization of energy and throughput in a wireless sensor network (WSN), with the intention of applying the approach to water-quality monitoring. Water-quality monitoring using WSN technology has become an interesting research area. Energy scarcity is a critical issue that plagues the widespread deployment of WSN systems. Different power supplies, harvesting energy from sustainable sources, have been explored. However, when energy-efficient models are not put in place, energy harvesting based WSN systems may experience an unstable energy supply, resulting in an interruption in communication, and low system throughput. To alleviate these problems, this paper presents the joint maximization of the energy harvested by sensor nodes and their information-transmission rate using a sum-throughput technique. A wireless information and power transfer (WIPT) method is considered by harvesting energy from dedicated radio frequency sources. Due to the doubly near–far condition that confronts WIPT systems, a new WIPT system is proposed to improve the fairness of resource utilization in the network. Numerical simulation results are presented to validate the mathematical formulations for the optimization problem, which maximize the energy harvested and the overall throughput rate. Defining the performance metrics of achievable throughput and fairness in resource sharing, the proposed WIPT system outperforms an existing state-of-the-art WIPT system, with the comparison based on numerical simulations of both systems. The improved energy efficiency of the proposed WIPT system contributes to addressing the problem of energy scarcity. PMID:29652866

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

PubMed

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

TH-CD-209-10: Scanning Proton Arc Therapy (SPArc) - The First Robust and Delivery-Efficient Spot Scanning Proton Arc Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, X; Li, X; Zhang, J

Purpose: To develop a delivery-efficient proton spot-scanning arc therapy technique with robust plan quality. Methods: We developed a Scanning Proton Arc(SPArc) optimization algorithm integrated with (1)Control point re-sampling by splitting control point into adjacent sub-control points; (2)Energy layer re-distribution by assigning the original energy layers to the new sub-control points; (3)Energy layer filtration by deleting low MU weighting energy layers; (4)Energy layer re-sampling by sampling additional layers to ensure the optimal solution. A bilateral head and neck oropharynx case and a non-mobile lung target case were tested. Plan quality and total estimated delivery time were compared to original robust optimizedmore » multi-field step-and-shoot arc plan without SPArc optimization (Arcmulti-field) and standard robust optimized Intensity Modulated Proton Therapy(IMPT) plans. Dose-Volume-Histograms (DVH) of target and Organ-at-Risks (OARs) were analyzed along with all worst case scenarios. Total delivery time was calculated based on the assumption of a 360 degree gantry room with 1 RPM rotation speed, 2ms spot switching time, beam current 1nA, minimum spot weighting 0.01 MU, energy-layer-switching-time (ELST) from 0.5 to 4s. Results: Compared to IMPT, SPArc delivered less integral dose(−14% lung and −8% oropharynx). For lung case, SPArc reduced 60% of skin max dose, 35% of rib max dose and 15% of lung mean dose. Conformity Index is improved from 7.6(IMPT) to 4.0(SPArc). Compared to Arcmulti-field, SPArc reduced number of energy layers by 61%(276 layers in lung) and 80%(1008 layers in oropharynx) while kept the same robust plan quality. With ELST from 0.5s to 4s, it reduced 55%–60% of Arcmulti-field delivery time for the lung case and 56%–67% for the oropharynx case. Conclusion: SPArc is the first robust and delivery-efficient proton spot-scanning arc therapy technique which could be implemented in routine clinic. For modern proton machine with ELST close to 0.5s, SPArc would be a popular treatment option for both single and multi-room center.« less

Optimized operation of dielectric laser accelerators: Multibunch

NASA Astrophysics Data System (ADS)

Hanuka, Adi; Schächter, Levi

2018-06-01

We present a self-consistent analysis to determine the optimal charge, gradient, and efficiency for laser driven accelerators operating with a train of microbunches. Specifically, we account for the beam loading reduction on the material occurring at the dielectric-vacuum interface. In the case of a train of microbunches, such beam loading effect could be detrimental due to energy spread, however this may be compensated by a tapered laser pulse. We ultimately propose an optimization procedure with an analytical solution for group velocity which equals to half the speed of light. This optimization results in a maximum efficiency 20% lower than the single bunch case, and a total accelerated charge of 1 06 electrons in the train. The approach holds promise for improving operations of dielectric laser accelerators and may have an impact on emerging laser accelerators driven by high-power optical lasers.

Energy efficient engine: Low-pressure turbine subsonic cascade component development and integration program

NASA Technical Reports Server (NTRS)

Sharma, O. P.; Kopper, F. C.; Knudsen, L. K.; Yustinich, J. B.

1982-01-01

A subsonic cascade test program was conducted to provide technical data for optimizing the blade and vane airfoil designs for the Energy Efficient Engine Low-Pressure Turbine component. The program consisted of three parts. The first involved an evaluation of the low-chamber inlet guide vane. The second, was an evaluation of two candidate aerodynamic loading philosophies for the fourth blade root section. The third part consisted of an evaluation of three candidate airfoil geometries for the fourth blade mean section. The performance of each candidate airfoil was evaluated in a linear cascade configuration. The overall results of this study indicate that the aft-loaded airfoil designs resulted in lower losses which substantiated Pratt & Whitney Aircraft's design philosophy for the Energy Efficient Engine low-pressure turbine component.

Design and optimization of resonance-based efficient wireless power delivery systems for biomedical implants.

PubMed

Ramrakhyani, A K; Mirabbasi, S; Mu Chiao

2011-02-01

Resonance-based wireless power delivery is an efficient technique to transfer power over a relatively long distance. This technique typically uses four coils as opposed to two coils used in conventional inductive links. In the four-coil system, the adverse effects of a low coupling coefficient between primary and secondary coils are compensated by using high-quality (Q) factor coils, and the efficiency of the system is improved. Unlike its two-coil counterpart, the efficiency profile of the power transfer is not a monotonically decreasing function of the operating distance and is less sensitive to changes in the distance between the primary and secondary coils. A four-coil energy transfer system can be optimized to provide maximum efficiency at a given operating distance. We have analyzed the four-coil energy transfer systems and outlined the effect of design parameters on power-transfer efficiency. Design steps to obtain the efficient power-transfer system are presented and a design example is provided. A proof-of-concept prototype system is implemented and confirms the validity of the proposed analysis and design techniques. In the prototype system, for a power-link frequency of 700 kHz and a coil distance range of 10 to 20 mm, using a 22-mm diameter implantable coil resonance-based system shows a power-transfer efficiency of more than 80% with an enhanced operating range compared to ~40% efficiency achieved by a conventional two-coil system.

Minimizing energy dissipation of matrix multiplication kernel on Virtex-II

NASA Astrophysics Data System (ADS)

Choi, Seonil; Prasanna, Viktor K.; Jang, Ju-wook

2002-07-01

In this paper, we develop energy-efficient designs for matrix multiplication on FPGAs. To analyze the energy dissipation, we develop a high-level model using domain-specific modeling techniques. In this model, we identify architecture parameters that significantly affect the total energy (system-wide energy) dissipation. Then, we explore design trade-offs by varying these parameters to minimize the system-wide energy. For matrix multiplication, we consider a uniprocessor architecture and a linear array architecture to develop energy-efficient designs. For the uniprocessor architecture, the cache size is a parameter that affects the I/O complexity and the system-wide energy. For the linear array architecture, the amount of storage per processing element is a parameter affecting the system-wide energy. By using maximum amount of storage per processing element and minimum number of multipliers, we obtain a design that minimizes the system-wide energy. We develop several energy-efficient designs for matrix multiplication. For example, for 6×6 matrix multiplication, energy savings of upto 52% for the uniprocessor architecture and 36% for the linear arrary architecture is achieved over an optimized library for Virtex-II FPGA from Xilinx.

Enhancing low-grade thermal energy recovery in a thermally regenerative ammonia battery using elevated temperatures.

PubMed

Zhang, Fang; LaBarge, Nicole; Yang, Wulin; Liu, Jia; Logan, Bruce E

2015-03-01

A thermally regenerative ammonia battery (TRAB) is a new approach for converting low-grade thermal energy into electricity by using an ammonia electrolyte and copper electrodes. TRAB operation at 72 °C produced a power density of 236 ± 8 Wm(-2), with a linear decrease in power to 95 ± 5 Wm(-2) at 23 °C. The improved power at higher temperatures was due to reduced electrode overpotentials and more favorable thermodynamics for the anode reaction (copper oxidation). The energy density varied with temperature and discharge rates, with a maximum of 650 Wh m(-3) at a discharge energy efficiency of 54% and a temperature of 37 °C. The energy efficiency calculated with chemical process simulation software indicated a Carnot-based efficiency of up to 13% and an overall thermal energy recovery of 0.5%. It should be possible to substantially improve these energy recoveries through optimization of electrolyte concentrations and by using improved ion-selective membranes and energy recovery systems such as heat exchangers. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Energy Efficiency Under Alternative Carbon Policies. Incentives, Measurement, and Interregional Effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steinberg, Daniel C.; Boyd, Erin

2015-08-28

In this report, we examine and compare how tradable mass-based polices and tradable rate-based policies create different incentives for energy efficiency investments. Through a generalized demonstration and set of examples, we show that as a result of the output subsidy they create, traditional rate-based policies, those that do not credit energy savings from efficiency measures, reduce the incentive for investment in energy efficiency measures relative to an optimally designed mass-based policy or equivalent carbon tax. We then show that this reduced incentive can be partially addressed by modifying the rate-based policy such that electricity savings from energy efficiency measures aremore » treated as a source of zero-carbon generation within the framework of the standard, or equivalently, by assigning avoided emissions credit to the electricity savings at the rate of the intensity target. These approaches result in an extension of the output subsidy to efficiency measures and eliminate the distortion between supply-side and demand-side options for GHG emissions reduction. However, these approaches do not address electricity price distortions resulting from the output subsidy that also impact the value of efficiency measures. Next, we assess alternative approaches for crediting energy efficiency savings within the framework of a rate-based policy. Finally, we identify a number of challenges that arise in implementing a rate-based policy with efficiency crediting, including the requirement to develop robust estimates of electricity savings in order to assess compliance, and the requirement to track the regionality of the generation impacts of efficiency measures to account for their interstate effects.« less

Investigation of the Energy Balance in the Spark Discharge Generator for Nanoparticles Synthesis

NASA Astrophysics Data System (ADS)

Mylnikov, D. A.; Efimov, A. A.; Ivanov, V. V.

2017-07-01

In this paper we investigate the balance of energy in the discharge circuit of a spark discharge generator (SDG) for nanoparticles synthesis. The released energy consists of several parts: the energy in a discharge gap and the energy dissipated in the other elements of the circuit. In turn, in the gap a one part of the energy releases in preanode and precathode regions and the other part in an arc between electrodes. We measured these parts and proposed ways to optimize energy efficiency of the nanoparticles production.

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

PubMed Central

Kim, Youngmin; Lee, Chan-Gun

2017-01-01

In wireless sensor networks (WSNs), sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods. PMID:29240695

Improving the energy efficiency of telecommunication networks

NASA Astrophysics Data System (ADS)

Lange, Christoph; Gladisch, Andreas

2011-05-01

The energy consumption of telecommunication networks has gained increasing interest throughout the recent past: Besides its environmental implications it has been identified to be a major contributor to operational expenditures of network operators. Targeting at sustainable telecommunication networks, thus, it is important to find appropriate strategies for improving their energy efficiency before the background of rapidly increasing traffic volumes. Besides the obvious benefits of increasing energy efficiency of network elements by leveraging technology progress, load-adaptive network operation is a very promising option, i.e. using network resources only to an extent and for the time they are actually needed. In contrast, current network operation takes almost no advantage of the strongly time-variant behaviour of the network traffic load. Mechanisms for energy-aware load-adaptive network operation can be subdivided in techniques based on local autonomous or per-link decisions and in techniques relying on coordinated decisions incorporating information from several links. For the transformation from current network structures and operation paradigms towards energy-efficient and sustainable networks it will be essential to use energy-optimized network elements as well as including the overall energy consumption in network design and planning phases together with the energy-aware load-adaptive operation. In load-adaptive operation it will be important to establish the optimum balance between local and overarching power management concepts in telecommunication networks.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform.

PubMed

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon; Cho, Sungrae

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform

PubMed Central

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively. PMID:28796804

A new optimal seam method for seamless image stitching

NASA Astrophysics Data System (ADS)

Xue, Jiale; Chen, Shengyong; Cheng, Xu; Han, Ying; Zhao, Meng

2017-07-01

A novel optimal seam method which aims to stitch those images with overlapping area more seamlessly has been propos ed. Considering the traditional gradient domain optimal seam method and fusion algorithm result in bad color difference measurement and taking a long time respectively, the input images would be converted to HSV space and a new energy function is designed to seek optimal stitching path. To smooth the optimal stitching path, a simplified pixel correction and weighted average method are utilized individually. The proposed methods exhibit performance in eliminating the stitching seam compared with the traditional gradient optimal seam and high efficiency with multi-band blending algorithm.

Conformal growth of Mo/Si multilayers on grating substrates using collimated ion beam sputtering

NASA Astrophysics Data System (ADS)

Voronov, D. L.; Gawlitza, P.; Cambie, R.; Dhuey, S.; Gullikson, E. M.; Warwick, T.; Braun, S.; Yashchuk, V. V.; Padmore, H. A.

2012-05-01

Deposition of multilayers on saw-tooth substrates is a key step in the fabrication of multilayer blazed gratings (MBG) for extreme ultraviolet and soft x-rays. Growth of the multilayers can be perturbed by shadowing effects caused by the highly corrugated surface of the substrates, which results in distortion of the multilayer stack structure and degradation of performance of MBGs. To minimize the shadowing effects, we used an ion-beam sputtering machine with a highly collimated atomic flux to deposit Mo/Si multilayers on saw-tooth substrates. The sputtering conditions were optimized by finding a balance between smoothening and roughening processes in order to minimize degradation of the groove profile in the course of deposition and at the same time to keep the interfaces of a multilayer stack smooth enough for high efficiency. An optimal value of energy of 200 eV for sputtering Kr+ ions was found by deposition of test multilayers on flat substrates at a range of ion energies. Two saw-tooth substrates were deposited at energies of 200 eV and 700 eV for the sputtering ions. It was found that reduction of the ion energy improved the blazing performance of the MBG and resulted in a 40% gain in the diffraction efficiency due to better replication of the groove profile by the multilayer. As a result of the optimization performed, an absolute diffraction efficiency of 28.8% was achieved for the 2nd blaze order of the MBG with a groove density of 7350 lines/mm at a wavelength of 13.5 nm. Details of the growth behavior of the multilayers on flat and saw-tooth substrates are discussed in terms of the linear continuous model of film growth.

Conformal growth of Mo/Si multilayers on grating substrates using collimated ion beam sputtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voronov, D. L.; Cambie, R.; Dhuey, S.

2012-05-01

Deposition of multilayers on saw-tooth substrates is a key step in the fabrication of multilayer blazed gratings (MBG) for extreme ultraviolet and soft x-rays. Growth of the multilayers can be perturbed by shadowing effects caused by the highly corrugated surface of the substrates, which results in distortion of the multilayer stack structure and degradation of performance of MBGs. To minimize the shadowing effects, we used an ion-beam sputtering machine with a highly collimated atomic flux to deposit Mo/Si multilayers on saw-tooth substrates. The sputtering conditions were optimized by finding a balance between smoothening and roughening processes in order to minimizemore » degradation of the groove profile in the course of deposition and at the same time to keep the interfaces of a multilayer stack smooth enough for high efficiency. An optimal value of energy of 200 eV for sputtering Kr{sup +} ions was found by deposition of test multilayers on flat substrates at a range of ion energies. Two saw-tooth substrates were deposited at energies of 200 eV and 700 eV for the sputtering ions. It was found that reduction of the ion energy improved the blazing performance of the MBG and resulted in a 40% gain in the diffraction efficiency due to better replication of the groove profile by the multilayer. As a result of the optimization performed, an absolute diffraction efficiency of 28.8% was achieved for the 2nd blaze order of the MBG with a groove density of 7350 lines/mm at a wavelength of 13.5 nm. Details of the growth behavior of the multilayers on flat and saw-tooth substrates are discussed in terms of the linear continuous model of film growth.« less

Conformal growth of Mo/Si multilayers on grating substrates using collimated ion beam sputtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voronov, D. L.; Gawlitza, Peter; Cambie, Rossana

2012-05-07

Deposition of multilayers on saw-tooth substrates is a key step in the fabrication of multilayer blazed gratings (MBG) for extreme ultraviolet and soft x-rays. Growth of the multilayers can be perturbed by shadowing effects caused by the highly corrugated surface of the substrates, which results in distortion of the multilayer stack structure and degradation of performance of MBGs. In this study, to minimize the shadowing effects, we used an ion-beamsputtering machine with a highly collimated atomic flux to deposit Mo/Si multilayers on saw-tooth substrates. The sputtering conditions were optimized by finding a balance between smoothening and roughening processes in ordermore » to minimize degradation of the groove profile in the course of deposition and at the same time to keep the interfaces of a multilayer stack smooth enough for high efficiency. An optimal value of energy of 200 eV for sputtering Kr + ions was found by deposition of test multilayers on flat substrates at a range of ion energies. Two saw-tooth substrates were deposited at energies of 200 eV and 700 eV for the sputtering ions. It was found that reduction of the ion energy improved the blazing performance of the MBG and resulted in a 40% gain in the diffraction efficiency due to better replication of the groove profile by the multilayer. As a result of the optimization performed, an absolute diffraction efficiency of 28.8% was achieved for the 2nd blaze order of the MBG with a groove density of 7350 lines/mm at a wavelength of 13.5 nm. Lastly, details of the growth behavior of the multilayers on flat and saw-tooth substrates are discussed in terms of the linear continuous model of film growth.« less

Optimization of constrained density functional theory

NASA Astrophysics Data System (ADS)

O'Regan, David D.; Teobaldi, Gilberto

2016-07-01

Constrained density functional theory (cDFT) is a versatile electronic structure method that enables ground-state calculations to be performed subject to physical constraints. It thereby broadens their applicability and utility. Automated Lagrange multiplier optimization is necessary for multiple constraints to be applied efficiently in cDFT, for it to be used in tandem with geometry optimization, or with molecular dynamics. In order to facilitate this, we comprehensively develop the connection between cDFT energy derivatives and response functions, providing a rigorous assessment of the uniqueness and character of cDFT stationary points while accounting for electronic interactions and screening. In particular, we provide a nonperturbative proof that stable stationary points of linear density constraints occur only at energy maxima with respect to their Lagrange multipliers. We show that multiple solutions, hysteresis, and energy discontinuities may occur in cDFT. Expressions are derived, in terms of convenient by-products of cDFT optimization, for quantities such as the dielectric function and a condition number quantifying ill definition in multiple constraint cDFT.

Analysis of power management and system latency in wireless sensor networks

NASA Astrophysics Data System (ADS)

Oswald, Matthew T.; Rohwer, Judd A.; Forman, Michael A.

2004-08-01

Successful power management in a wireless sensor network requires optimization of the protocols which affect energy-consumption on each node and the aggregate effects across the larger network. System optimization for a given deployment scenario requires an analysis and trade off of desired node and network features with their associated costs. The sleep protocol for an energy-efficient wireless sensor network for event detection, target classification, and target tracking developed at Sandia National Laboratories is presented. The dynamic source routing (DSR) algorithm is chosen to reduce network maintenance overhead, while providing a self-configuring and self-healing network architecture. A method for determining the optimal sleep time is developed and presented, providing reference data which spans several orders of magnitude. Message timing diagrams show, that a node in a five-node cluster, employing an optimal cyclic single-radio sleep protocol, consumes 3% more energy and incurs a 16-s increase latency than nodes employing the more complex dual-radio STEM protocol.

Integrating a dual-silicon photoelectrochemical cell into a redox flow battery for unassisted photocharging

PubMed Central

Liao, Shichao; Zong, Xu; Seger, Brian; Pedersen, Thomas; Yao, Tingting; Ding, Chunmei; Shi, Jingying; Chen, Jian; Li, Can

2016-01-01

Solar rechargeable flow cells (SRFCs) provide an attractive approach for in situ capture and storage of intermittent solar energy via photoelectrochemical regeneration of discharged redox species for electricity generation. However, overall SFRC performance is restricted by inefficient photoelectrochemical reactions. Here we report an efficient SRFC based on a dual-silicon photoelectrochemical cell and a quinone/bromine redox flow battery for in situ solar energy conversion and storage. Using narrow bandgap silicon for efficient photon collection and fast redox couples for rapid interface charge injection, our device shows an optimal solar-to-chemical conversion efficiency of ∼5.9% and an overall photon–chemical–electricity energy conversion efficiency of ∼3.2%, which, to our knowledge, outperforms previously reported SRFCs. The proposed SRFC can be self-photocharged to 0.8 V and delivers a discharge capacity of 730 mAh l−1. Our work may guide future designs for highly efficient solar rechargeable devices. PMID:27142885

Solar water splitting by photovoltaic-electrolysis with a solar-to-hydrogen efficiency over 30%

PubMed Central

Jia, Jieyang; Seitz, Linsey C.; Benck, Jesse D.; Huo, Yijie; Chen, Yusi; Ng, Jia Wei Desmond; Bilir, Taner; Harris, James S.; Jaramillo, Thomas F.

2016-01-01

Hydrogen production via electrochemical water splitting is a promising approach for storing solar energy. For this technology to be economically competitive, it is critical to develop water splitting systems with high solar-to-hydrogen (STH) efficiencies. Here we report a photovoltaic-electrolysis system with the highest STH efficiency for any water splitting technology to date, to the best of our knowledge. Our system consists of two polymer electrolyte membrane electrolysers in series with one InGaP/GaAs/GaInNAsSb triple-junction solar cell, which produces a large-enough voltage to drive both electrolysers with no additional energy input. The solar concentration is adjusted such that the maximum power point of the photovoltaic is well matched to the operating capacity of the electrolysers to optimize the system efficiency. The system achieves a 48-h average STH efficiency of 30%. These results demonstrate the potential of photovoltaic-electrolysis systems for cost-effective solar energy storage. PMID:27796309

Solar water splitting by photovoltaic-electrolysis with a solar-to-hydrogen efficiency over 30.

PubMed

Jia, Jieyang; Seitz, Linsey C; Benck, Jesse D; Huo, Yijie; Chen, Yusi; Ng, Jia Wei Desmond; Bilir, Taner; Harris, James S; Jaramillo, Thomas F

2016-10-31

Hydrogen production via electrochemical water splitting is a promising approach for storing solar energy. For this technology to be economically competitive, it is critical to develop water splitting systems with high solar-to-hydrogen (STH) efficiencies. Here we report a photovoltaic-electrolysis system with the highest STH efficiency for any water splitting technology to date, to the best of our knowledge. Our system consists of two polymer electrolyte membrane electrolysers in series with one InGaP/GaAs/GaInNAsSb triple-junction solar cell, which produces a large-enough voltage to drive both electrolysers with no additional energy input. The solar concentration is adjusted such that the maximum power point of the photovoltaic is well matched to the operating capacity of the electrolysers to optimize the system efficiency. The system achieves a 48-h average STH efficiency of 30%. These results demonstrate the potential of photovoltaic-electrolysis systems for cost-effective solar energy storage.

Optimization of a radiative membrane for gas sensing applications

NASA Astrophysics Data System (ADS)

Lefebvre, Anthony; Boutami, Salim; Greffet, Jean-Jacques; Benisty, Henri

2014-05-01

To engineer a cheap, portable and low-power optical gas sensor, incandescent sources are more suitable than expensive quantum cascade lasers and low-efficiency light-emitting diodes. Such sources of radiation have already been realized, using standard MEMS technology, consisting in free standing circular micro-hotplates. This paper deals with the design of such membranes in order to maximize their wall-plug efficiency. Specification constraints are taken into account, including available energy per measurement and maximum power delivered by the electrical supply source. The main drawback of these membranes is known to be the power lost through conduction to the substrate, thus not converted in (useful) radiated power. If the membrane temperature is capped by technological requirements, radiative flux can be favored by increasing the membrane radius. However, given a finite amount of energy, the larger the membrane and its heat capacity, the shorter the time it can be turned on. This clearly suggests that an efficiency optimum has to be found. Using simulations based on a spatio-temporal radial profile, we demonstrate how to optimally design such membrane systems, and provide an insight into the thermo-optical mechanisms governing this kind of devices, resulting in a nontrivial design with a substantial benefit over existing systems. To further improve the source, we also consider tailoring the membrane stack spectral emissivity to promote the infrared signal to be sensed as well as to maximize energy efficiency.

Ceramic Integration Technologies for Energy and Aerospace Applications

NASA Technical Reports Server (NTRS)

Singh, Mrityunjay; Asthana, Ralph N.

2007-01-01

Robust and affordable integration technologies for advanced ceramics are required to improve the performance, reliability, efficiency, and durability of components, devices, and systems based on them in a wide variety of energy, aerospace, and environmental applications. Many thermochemical and thermomechanical factors including joint design, analysis, and optimization must be considered in integration of similar and dissimilar material systems.

Efficient Monte Carlo Methods for Biomolecular Simulations.

NASA Astrophysics Data System (ADS)

Bouzida, Djamal

A new approach to efficient Monte Carlo simulations of biological molecules is presented. By relaxing the usual restriction to Markov processes, we are able to optimize performance while dealing directly with the inhomogeneity and anisotropy inherent in these systems. The advantage of this approach is that we can introduce a wide variety of Monte Carlo moves to deal with complicated motions of the molecule, while maintaining full optimization at every step. This enables the use of a variety of collective rotational moves that relax long-wavelength modes. We were able to show by explicit simulations that the resulting algorithms substantially increase the speed of the simulation while reproducing the correct equilibrium behavior. This approach is particularly intended for simulations of macromolecules, although we expect it to be useful in other situations. The dynamic optimization of the new Monte Carlo methods makes them very suitable for simulated annealing experiments on all systems whose state space is continuous in general, and to the protein folding problem in particular. We introduce an efficient annealing schedule using preferential bias moves. Our simulated annealing experiments yield structures whose free energies were lower than the equilibrated X-ray structure, which leads us to believe that the empirical energy function used does not fully represent the interatomic interactions. Furthermore, we believe that the largest discrepancies involve the solvent effects in particular.

The latest developments and outlook for hydrogen liquefaction technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ohlig, K.; Decker, L.

2014-01-29

Liquefied hydrogen is presently mainly used for space applications and the semiconductor industry. While clean energy applications, for e.g. the automotive sector, currently contribute to this demand with a small share only, their demand may see a significant boost in the next years with the need for large scale liquefaction plants exceeding the current plant sizes by far. Hydrogen liquefaction for small scale plants with a maximum capacity of 3 tons per day (tpd) is accomplished with a Brayton refrigeration cycle using helium as refrigerant. This technology is characterized by low investment costs but lower process efficiency and hence highermore » operating costs. For larger plants, a hydrogen Claude cycle is used, characterized by higher investment but lower operating costs. However, liquefaction plants meeting the potentially high demand in the clean energy sector will need further optimization with regard to energy efficiency and hence operating costs. The present paper gives an overview of the currently applied technologies, including their thermodynamic and technical background. Areas of improvement are identified to derive process concepts for future large scale hydrogen liquefaction plants meeting the needs of clean energy applications with optimized energy efficiency and hence minimized operating costs. Compared to studies in this field, this paper focuses on application of new technology and innovative concepts which are either readily available or will require short qualification procedures. They will hence allow implementation in plants in the close future.« less

Experimental investigation on the hydrodynamic performance of a wave energy converter

NASA Astrophysics Data System (ADS)

Zheng, Xiong-bo; Ma, Yong; Zhang, Liang; Jiang, Jin; Liu, Heng-xu

2017-06-01

Wave energy is an important type of marine renewable energy. A wave energy converter (WEC) moored with two floating bodies was developed in the present study. To analyze the dynamic performance of the WEC, an experimental device was designed and tested in a tank. The experiment focused on the factors which impact the motion and energy conversion performance of the WEC. Dynamic performance was evaluated by the relative displacements and velocities of the oscillator and carrier which served as the floating bodies of WEC. Four factors were tested, i.e. wave height, wave period, power take-off (PTO) damping, and mass ratio ( R M) of the oscillator and carrier. Experimental results show that these factors greatly affect the energy conversion performance, especially when the wave period matches R M and PTO damping. According to the results, we conclude that: (a) the maximization of the relative displacements and velocities leads to the maximization of the energy conversion efficiency; (b) the larger the wave height, the higher the energy conversion efficiency will be; (c) the relationships of energy conversion efficiency with wave period, PTO damping, and R M are nonlinear, but the maximum efficiency is obtained when these three factors are optimally matched. Experimental results demonstrated that the energy conversion efficiency reached the peak at 28.62% when the wave height was 120 mm, wave period was 1.0 s, R M was 0.21, and the PTO damping was corresponding to the resistance of 100 Ω.

A Survey on an Energy-Efficient and Energy-Balanced Routing Protocol for Wireless Sensor Networks.

PubMed

Ogundile, Olayinka O; Alfa, Attahiru S

2017-05-10

Wireless sensor networks (WSNs) form an important part of industrial application. There has been growing interest in the potential use of WSNs in applications such as environment monitoring, disaster management, health care monitoring, intelligence surveillance and defence reconnaissance. In these applications, the sensor nodes (SNs) are envisaged to be deployed in sizeable numbers in an outlying area, and it is quite difficult to replace these SNs after complete deployment in many scenarios. Therefore, as SNs are predominantly battery powered devices, the energy consumption of the nodes must be properly managed in order to prolong the network lifetime and functionality to a rational time. Different energy-efficient and energy-balanced routing protocols have been proposed in literature over the years. The energy-efficient routing protocols strive to increase the network lifetime by minimizing the energy consumption in each SN. On the other hand, the energy-balanced routing protocols protract the network lifetime by uniformly balancing the energy consumption among the nodes in the network. There have been various survey papers put forward by researchers to review the performance and classify the different energy-efficient routing protocols for WSNs. However, there seems to be no clear survey emphasizing the importance, concepts, and principles of load-balanced energy routing protocols for WSNs. In this paper, we provide a clear picture of both the energy-efficient and energy-balanced routing protocols for WSNs. More importantly, this paper presents an extensive survey of the different state-of-the-art energy-efficient and energy-balanced routing protocols. A taxonomy is introduced in this paper to classify the surveyed energy-efficient and energy-balanced routing protocols based on their proposed mode of communication towards the base station (BS). In addition, we classified these routing protocols based on the solution types or algorithms, and the input decision variables defined in the routing algorithm. The strengths and weaknesses of the choice of the decision variables used in the design of these energy-efficient and energy-balanced routing protocols are emphasised. Finally, we suggest possible research directions in order to optimize the energy consumption in sensor networks.

A Survey on an Energy-Efficient and Energy-Balanced Routing Protocol for Wireless Sensor Networks

PubMed Central

Ogundile, Olayinka O.; Alfa, Attahiru S.

2017-01-01

Wireless sensor networks (WSNs) form an important part of industrial application. There has been growing interest in the potential use of WSNs in applications such as environment monitoring, disaster management, health care monitoring, intelligence surveillance and defence reconnaissance. In these applications, the sensor nodes (SNs) are envisaged to be deployed in sizeable numbers in an outlying area, and it is quite difficult to replace these SNs after complete deployment in many scenarios. Therefore, as SNs are predominantly battery powered devices, the energy consumption of the nodes must be properly managed in order to prolong the network lifetime and functionality to a rational time. Different energy-efficient and energy-balanced routing protocols have been proposed in literature over the years. The energy-efficient routing protocols strive to increase the network lifetime by minimizing the energy consumption in each SN. On the other hand, the energy-balanced routing protocols protract the network lifetime by uniformly balancing the energy consumption among the nodes in the network. There have been various survey papers put forward by researchers to review the performance and classify the different energy-efficient routing protocols for WSNs. However, there seems to be no clear survey emphasizing the importance, concepts, and principles of load-balanced energy routing protocols for WSNs. In this paper, we provide a clear picture of both the energy-efficient and energy-balanced routing protocols for WSNs. More importantly, this paper presents an extensive survey of the different state-of-the-art energy-efficient and energy-balanced routing protocols. A taxonomy is introduced in this paper to classify the surveyed energy-efficient and energy-balanced routing protocols based on their proposed mode of communication towards the base station (BS). In addition, we classified these routing protocols based on the solution types or algorithms, and the input decision variables defined in the routing algorithm. The strengths and weaknesses of the choice of the decision variables used in the design of these energy-efficient and energy-balanced routing protocols are emphasised. Finally, we suggest possible research directions in order to optimize the energy consumption in sensor networks. PMID:28489054

Research on Matching Method of Power Supply Parameters for Dual Energy Source Electric Vehicles

NASA Astrophysics Data System (ADS)

Jiang, Q.; Luo, M. J.; Zhang, S. K.; Liao, M. W.

2018-03-01

A new type of power source is proposed, which is based on the traffic signal matching method of the dual energy source power supply composed of the batteries and the supercapacitors. First, analyzing the power characteristics is required to meet the excellent dynamic characteristics of EV, studying the energy characteristics is required to meet the mileage requirements and researching the physical boundary characteristics is required to meet the physical conditions of the power supply. Secondly, the parameter matching design with the highest energy efficiency is adopted to select the optimal parameter group with the method of matching deviation. Finally, the simulation analysis of the vehicle is carried out in MATLABSimulink, The mileage and energy efficiency of dual energy sources are analyzed in different parameter models, and the rationality of the matching method is verified.