Escalator: An Autonomous Scheduling Scheme for Convergecast in TSCH.

PubMed

Oh, Sukho; Hwang, DongYeop; Kim, Ki-Hyung; Kim, Kangseok

2018-04-16

Time Slotted Channel Hopping (TSCH) is widely used in the industrial wireless sensor networks due to its high reliability and energy efficiency. Various timeslot and channel scheduling schemes have been proposed for achieving high reliability and energy efficiency for TSCH networks. Recently proposed autonomous scheduling schemes provide flexible timeslot scheduling based on the routing topology, but do not take into account the network traffic and packet forwarding delays. In this paper, we propose an autonomous scheduling scheme for convergecast in TSCH networks with RPL as a routing protocol, named Escalator. Escalator generates a consecutive timeslot schedule along the packet forwarding path to minimize the packet transmission delay. The schedule is generated autonomously by utilizing only the local routing topology information without any additional signaling with other nodes. The generated schedule is guaranteed to be conflict-free, in that all nodes in the network could transmit packets to the sink in every slotframe cycle. We implement Escalator and evaluate its performance with existing autonomous scheduling schemes through a testbed and simulation. Experimental results show that the proposed Escalator has lower end-to-end delay and higher packet delivery ratio compared to the existing schemes regardless of the network topology.

A random-key encoded harmony search approach for energy-efficient production scheduling with shared resources

NASA Astrophysics Data System (ADS)

Garcia-Santiago, C. A.; Del Ser, J.; Upton, C.; Quilligan, F.; Gil-Lopez, S.; Salcedo-Sanz, S.

2015-11-01

When seeking near-optimal solutions for complex scheduling problems, meta-heuristics demonstrate good performance with affordable computational effort. This has resulted in a gravitation towards these approaches when researching industrial use-cases such as energy-efficient production planning. However, much of the previous research makes assumptions about softer constraints that affect planning strategies and about how human planners interact with the algorithm in a live production environment. This article describes a job-shop problem that focuses on minimizing energy consumption across a production facility of shared resources. The application scenario is based on real facilities made available by the Irish Center for Manufacturing Research. The formulated problem is tackled via harmony search heuristics with random keys encoding. Simulation results are compared to a genetic algorithm, a simulated annealing approach and a first-come-first-served scheduling. The superior performance obtained by the proposed scheduler paves the way towards its practical implementation over industrial production chains.

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.

78 FR 11996 - Energy Efficiency Program for Commercial and Industrial Equipment: Commercial and Industrial Pumps

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-21

.... EERE-2011-BT-STD-0031] RIN 1904-AC54 Energy Efficiency Program for Commercial and Industrial Equipment... meeting and availability of the Framework Document pertaining to the development of energy conservation... to and the issues presented by these equipment types, and in consideration of the travel schedules of...

An on-time power-aware scheduling scheme for medical sensor SoC-based WBAN systems.

PubMed

Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

2012-12-27

The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network-a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

PubMed Central

Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

2013-01-01

The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices. PMID:23271602

Heuristic Scheduling in Grid Environments: Reducing the Operational Energy Demand

NASA Astrophysics Data System (ADS)

Bodenstein, Christian

In a world where more and more businesses seem to trade in an online market, the supply of online services to the ever-growing demand could quickly reach its capacity limits. Online service providers may find themselves maxed out at peak operation levels during high-traffic timeslots but too little demand during low-traffic timeslots, although the latter is becoming less frequent. At this point deciding which user is allocated what level of service becomes essential. The concept of Grid computing could offer a meaningful alternative to conventional super-computing centres. Not only can Grids reach the same computing speeds as some of the fastest supercomputers, but distributed computing harbors a great energy-saving potential. When scheduling projects in such a Grid environment however, simply assigning one process to a system becomes so complex in calculation that schedules are often too late to execute, rendering their optimizations useless. Current schedulers attempt to maximize the utility, given some sort of constraint, often reverting to heuristics. This optimization often comes at the cost of environmental impact, in this case CO 2 emissions. This work proposes an alternate model of energy efficient scheduling while keeping a respectable amount of economic incentives untouched. Using this model, it is possible to reduce the total energy consumed by a Grid environment using 'just-in-time' flowtime management, paired with ranking nodes by efficiency.

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

PubMed Central

Hwang, I-Shyan

2017-01-01

The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized. PMID:29257078

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.

Power-based Shift Schedule for Pure Electric Vehicle with a Two-speed Automatic Transmission

NASA Astrophysics Data System (ADS)

Wang, Jiaqi; Liu, Yanfang; Liu, Qiang; Xu, Xiangyang

2016-11-01

This paper introduces a comprehensive shift schedule for a two-speed automatic transmission of pure electric vehicle. Considering about driving ability and efficiency performance of electric vehicles, the power-based shift schedule is proposed with three principles. This comprehensive shift schedule regards the vehicle current speed and motor load power as input parameters to satisfy the vehicle driving power demand with lowest energy consumption. A simulation model has been established to verify the dynamic and economic performance of comprehensive shift schedule. Compared with traditional dynamic and economic shift schedules, simulation results indicate that the power-based shift schedule is superior to traditional shift schedules.

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.

Channel and Timeslot Co-Scheduling with Minimal Channel Switching for Data Aggregation in MWSNs

PubMed Central

Yeoum, Sanggil; Kang, Byungseok; Lee, Jinkyu; Choo, Hyunseung

2017-01-01

Collision-free transmission and efficient data transfer between nodes can be achieved through a set of channels in multichannel wireless sensor networks (MWSNs). While using multiple channels, we have to carefully consider channel interference, channel and time slot (resources) optimization, channel switching delay, and energy consumption. Since sensor nodes operate on low battery power, the energy consumed in channel switching becomes an important challenge. In this paper, we propose channel and time slot scheduling for minimal channel switching in MWSNs, while achieving efficient and collision-free transmission between nodes. The proposed scheme constructs a duty-cycled tree while reducing the amount of channel switching. As a next step, collision-free time slots are assigned to every node based on the minimal data collection delay. The experimental results demonstrate that the validity of our scheme reduces the amount of channel switching by 17.5%, reduces energy consumption for channel switching by 28%, and reduces the schedule length by 46%, as compared to the existing schemes. PMID:28471416

Channel and Timeslot Co-Scheduling with Minimal Channel Switching for Data Aggregation in MWSNs.

PubMed

Yeoum, Sanggil; Kang, Byungseok; Lee, Jinkyu; Choo, Hyunseung

2017-05-04

Collision-free transmission and efficient data transfer between nodes can be achieved through a set of channels in multichannel wireless sensor networks (MWSNs). While using multiple channels, we have to carefully consider channel interference, channel and time slot (resources) optimization, channel switching delay, and energy consumption. Since sensor nodes operate on low battery power, the energy consumed in channel switching becomes an important challenge. In this paper, we propose channel and time slot scheduling for minimal channel switching in MWSNs, while achieving efficient and collision-free transmission between nodes. The proposed scheme constructs a duty-cycled tree while reducing the amount of channel switching. As a next step, collision-free time slots are assigned to every node based on the minimal data collection delay. The experimental results demonstrate that the validity of our scheme reduces the amount of channel switching by 17.5%, reduces energy consumption for channel switching by 28%, and reduces the schedule length by 46%, as compared to the existing schemes.

Technology for aircraft energy efficiency

NASA Technical Reports Server (NTRS)

Klineberg, J. M.

1977-01-01

Six technology programs for reducing fuel use in U.S. commercial aviation are discussed. The six NASA programs are divided into three groups: Propulsion - engine component improvement, energy efficient engine, advanced turboprops; Aerodynamics - energy efficient transport, laminar flow control; and Structures - composite primary structures. Schedules, phases, and applications of these programs are considered, and it is suggested that program results will be applied to current transport derivatives in the early 1980s and to all-new aircraft of the late 1980s and early 1990s.

DOE/ NREL Build One of the World's Most Energy Efficient Office Spaces

ScienceCinema

Radocy, Rachel; Livingston, Brian; von Luhrte, Rich

2018-05-18

Technology — from sophisticated computer modeling to advanced windows that actually open — will help the newest building at the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) be one of the world's most energy efficient offices. Scheduled to open this summer, the 222,000 square-foot RSF will house more than 800 staff and an energy efficient information technology data center. Because 19 percent of the country's energy is used by commercial buildings, DOE plans to make this facility a showcase for energy efficiency. DOE hopes the design of the RSF will be replicated by the building industry and help reduce the nation's energy consumption by changing the way commercial buildings are designed and built.

Energy-driven scheduling algorithm for nanosatellite energy harvesting maximization

NASA Astrophysics Data System (ADS)

Slongo, L. K.; Martínez, S. V.; Eiterer, B. V. B.; Pereira, T. G.; Bezerra, E. A.; Paiva, K. V.

2018-06-01

The number of tasks that a satellite may execute in orbit is strongly related to the amount of energy its Electrical Power System (EPS) is able to harvest and to store. The manner the stored energy is distributed within the satellite has also a great impact on the CubeSat's overall efficiency. Most CubeSat's EPS do not prioritize energy constraints in their formulation. Unlike that, this work proposes an innovative energy-driven scheduling algorithm based on energy harvesting maximization policy. The energy harvesting circuit is mathematically modeled and the solar panel I-V curves are presented for different temperature and irradiance levels. Considering the models and simulations, the scheduling algorithm is designed to keep solar panels working close to their maximum power point by triggering tasks in the appropriate form. Tasks execution affects battery voltage, which is coupled to the solar panels through a protection circuit. A software based Perturb and Observe strategy allows defining the tasks to be triggered. The scheduling algorithm is tested in FloripaSat, which is an 1U CubeSat. A test apparatus is proposed to emulate solar irradiance variation, considering the satellite movement around the Earth. Tests have been conducted to show that the scheduling algorithm improves the CubeSat energy harvesting capability by 4.48% in a three orbit experiment and up to 8.46% in a single orbit cycle in comparison with the CubeSat operating without the scheduling algorithm.

78 FR 77607 - Energy Conservation Program for Consumer Products: Energy Conservation Standards for Residential...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-24

... Fans AGENCY: Office of Energy Efficiency and Renewable Energy, Department of Energy. ACTION: Notice of extension of public comment period. SUMMARY: On October 25, 2013, the U.S. Department of Energy (DOE... furnace fans, with a comment period that was scheduled to close December 24, 2013. This document announces...

Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

ERIC Educational Resources Information Center

Yu, Chao

2013-01-01

In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

MIROS: A Hybrid Real-Time Energy-Efficient Operating System for the Resource-Constrained Wireless Sensor Nodes

PubMed Central

Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Shi, Hongling; Gholami, Khalid El

2014-01-01

Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant. PMID:25248069

MIROS: a hybrid real-time energy-efficient operating system for the resource-constrained wireless sensor nodes.

PubMed

Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Shi, Hongling; El Gholami, Khalid

2014-09-22

Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant.

A multi-group and preemptable scheduling of cloud resource based on HTCondor

NASA Astrophysics Data System (ADS)

Jiang, Xiaowei; Zou, Jiaheng; Cheng, Yaodong; Shi, Jingyan

2017-10-01

Due to the features of virtual machine-flexibility, easy controlling and various system environments, more and more fields utilize the virtualization technology to construct the distributed system with the virtual resources, also including high energy physics. This paper introduce a method used in high energy physics that supports multiple resource group and preemptable cloud resource scheduling, combining virtual machine with HTCondor (a batch system). It makes resource controlling more flexible and more efficient and makes resource scheduling independent of job scheduling. Firstly, the resources belong to different experiment-groups, and the type of user-groups mapping to resource-groups(same as experiment-group) is one-to-one or many-to-one. In order to make the confused group simply to be managed, we designed the permission controlling component to ensure that the different resource-groups can get the suitable jobs. Secondly, for the purpose of elastically allocating resources for suitable resource-group, it is necessary to schedule resources like scheduling jobs. So this paper designs the cloud resource scheduling to maintain a resource queue and allocate an appropriate amount of virtual resources to the request resource-group. Thirdly, in some kind of situations, because of the resource occupied for a long time, resources need to be preempted. This paper adds the preemption function for the resource scheduling that implement resource preemption based on the group priority. Additionally, the way to preempting is soft that when virtual resources are preempted, jobs will not be killed but also be held and rematched later. It is implemented with the help of HTCondor, storing the held job information in scheduler, releasing the job to idle status and doing second matcher. In IHEP (institute of high energy physics), we have built a batch system based on HTCondor with a virtual resources pool based on Openstack. And this paper will show some cases of experiment JUNO and LHAASO. The result indicates that multi-group and preemptable resource scheduling is efficient to support multi-group and soft preemption. Additionally, the permission controlling component has been used in the local computing cluster, supporting for experiment JUNO, CMS and LHAASO, and the scale will be expanded to more experiments at the first half year, including DYW, BES and so on. Its evidence that the permission controlling is efficient.

Analysis on energy use in reuse cement silo for campus building

NASA Astrophysics Data System (ADS)

Fidiya Nugrahani, Elita; Winda Murti, Izzati; Arifianti, Qurrotin M. O.

2018-03-01

Semen Gresik, the first cement factory in Indonesia owned by the government was operated since 1957 and stopped the operation around 1997. The owner, PT. Semen Indonesia (Persero) intended to reuse cement factory for the campus building, Universitas Internasional Semen Indonesia (UISI). This research proposed to analyze the future Energy Use Intensity (EUI) and recommendation energy efficiency in renovating silo through simulation. The result of future EUI in existing building was 234 kWh/m2.year. The scenarios created to reduce energy use in six sectors: window shades, window material, infiltration, daylighting, plug load, air-conditioning and operation schedule. The lowest EUI estimated at 98.27 by use 2/3 window shades, triple low emission window glass, lighting efficiency at 3.23 W/m2, maximize daylighting and occupancy control, minimize infiltration to 0.17 ACH, and 12/5 for operation schedule.

A Time Tree Medium Access Control for Energy Efficiency and Collision Avoidance in Wireless Sensor Networks

PubMed Central

Lee, Kilhung

2010-01-01

This paper presents a medium access control and scheduling scheme for wireless sensor networks. It uses time trees for sending data from the sensor node to the base station. For an energy efficient operation of the sensor networks in a distributed manner, time trees are built in order to reduce the collision probability and to minimize the total energy required to send data to the base station. A time tree is a data gathering tree where the base station is the root and each sensor node is either a relaying or a leaf node of the tree. Each tree operates in a different time schedule with possibly different activation rates. Through the simulation, the proposed scheme that uses time trees shows better characteristics toward burst traffic than the previous energy and data arrival rate scheme. PMID:22319270

Tests of an alternating current propulsion subsystem for electric vehicles on a road load simulator

NASA Astrophysics Data System (ADS)

Stenger, F. J.

1982-12-01

The test results of a breadboard version of an ac electric-vehicle propulsion subsystem are presented. The breadboard was installed in the NASA Lewis Research Center Road Load Simulator facility and tested under steady-state and transient conditions. Steady-state tests were run to characterize the system and component efficiencies over the complete speed-torque range within the capability of the propulsion subsystem in the motoring mode of operation. Transient tests were performed to determine the energy consumption of the breadboard over the acceleration and cruise portions of SAE J227 and driving schedules B, C, and D. Tests in the regenerative mode were limited to the low-gear-speed range of the two speed transaxle used in the subsystem. The maximum steady-state subsystem efficiency observed for the breadboard was 81.5 percent in the high-gear-speed range in the motoring mode, and 76 percent in the regenerative braking mode (low gear). The subsystem energy efficiency during the transient tests ranged from 49.2 percent for schedule B to 68.4 percent for Schedule D.

Tests of an alternating current propulsion subsystem for electric vehicles on a road load simulator

NASA Technical Reports Server (NTRS)

Stenger, F. J.

1982-01-01

The test results of a breadboard version of an ac electric-vehicle propulsion subsystem are presented. The breadboard was installed in the NASA Lewis Research Center Road Load Simulator facility and tested under steady-state and transient conditions. Steady-state tests were run to characterize the system and component efficiencies over the complete speed-torque range within the capability of the propulsion subsystem in the motoring mode of operation. Transient tests were performed to determine the energy consumption of the breadboard over the acceleration and cruise portions of SAE J227 and driving schedules B, C, and D. Tests in the regenerative mode were limited to the low-gear-speed range of the two speed transaxle used in the subsystem. The maximum steady-state subsystem efficiency observed for the breadboard was 81.5 percent in the high-gear-speed range in the motoring mode, and 76 percent in the regenerative braking mode (low gear). The subsystem energy efficiency during the transient tests ranged from 49.2 percent for schedule B to 68.4 percent for Schedule D.

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

A novel minimum cost maximum power algorithm for future smart home energy management.

PubMed

Singaravelan, A; Kowsalya, M

2017-11-01

With the latest development of smart grid technology, the energy management system can be efficiently implemented at consumer premises. In this paper, an energy management system with wireless communication and smart meter are designed for scheduling the electric home appliances efficiently with an aim of reducing the cost and peak demand. For an efficient scheduling scheme, the appliances are classified into two types: uninterruptible and interruptible appliances. The problem formulation was constructed based on the practical constraints that make the proposed algorithm cope up with the real-time situation. The formulated problem was identified as Mixed Integer Linear Programming (MILP) problem, so this problem was solved by a step-wise approach. This paper proposes a novel Minimum Cost Maximum Power (MCMP) algorithm to solve the formulated problem. The proposed algorithm was simulated with input data available in the existing method. For validating the proposed MCMP algorithm, results were compared with the existing method. The compared results prove that the proposed algorithm efficiently reduces the consumer electricity consumption cost and peak demand to optimum level with 100% task completion without sacrificing the consumer comfort.

Self-powered information measuring wireless networks using the distribution of tasks within multicore processors

NASA Astrophysics Data System (ADS)

Zhuravska, Iryna M.; Koretska, Oleksandra O.; Musiyenko, Maksym P.; Surtel, Wojciech; Assembay, Azat; Kovalev, Vladimir; Tleshova, Akmaral

2017-08-01

The article contains basic approaches to develop the self-powered information measuring wireless networks (SPIM-WN) using the distribution of tasks within multicore processors critical applying based on the interaction of movable components - as in the direction of data transmission as wireless transfer of energy coming from polymetric sensors. Base mathematic model of scheduling tasks within multiprocessor systems was modernized to schedule and allocate tasks between cores of one-crystal computer (SoC) to increase energy efficiency SPIM-WN objects.

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.

Time-optimum packet scheduling for many-to-one routing in wireless sensor networks

USGS Publications Warehouse

Song, W.-Z.; Yuan, F.; LaHuser, R.

2007-01-01

This paper studies the WSN application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is time-optimum and costs max(2N(u1) - 1, N(u 0) -1) time slots, assuming each node reports one unit of data in each round. Here N(u0) is the total number of sensors, while N(u 1) denotes the number of sensors in a sink's largest branch subtree. With a few adjustments, we then show that our algorithm also achieves time-optimum scheduling in heterogeneous scenarios, where each sensor reports a heterogeneous amount of data in each round. Then we give a distributed implementation to let each node calculate its duty-cycle locally and maximize efficiency globally. In this packet scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also eliminated. Finally, simulations are conducted to evaluate network performance using the Qualnet simulator. Among other contributions, our study also identifies the maximum reporting frequency that a deployed sensor network can handle. ??2006 IEEE.

Time-optimum packet scheduling for many-to-one routing in wireless sensor networks

USGS Publications Warehouse

Song, W.-Z.; Yuan, F.; LaHusen, R.; Shirazi, B.

2007-01-01

This paper studies the wireless sensor networks (WSN) application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is time-optimum and costs [image omitted], N(u0)-1) time slots, assuming each node reports one unit of data in each round. Here [image omitted] is the total number of sensors, while [image omitted] denotes the number of sensors in a sink's largest branch subtree. With a few adjustments, we then show that our algorithm also achieves time-optimum scheduling in heterogeneous scenarios, where each sensor reports a heterogeneous amount of data in each round. Then we give a distributed implementation to let each node calculate its duty-cycle locally and maximize efficiency globally. In this packet-scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also mitigated. Finally, simulations are conducted to evaluate network performance using the Qualnet simulator. Among other contributions, our study also identifies the maximum reporting frequency that a deployed sensor network can handle.

Sault Tribe Building Efficiency Energy Audits

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

Holt, Jeffrey W.

2013-09-26

The Sault Ste. Marie Tribe of Chippewa Indians is working to reduce energy consumption and expense in Tribally-owned governmental buildings. The Sault Ste. Marie Tribe of Chippewa Indians will conduct energy audits of nine Tribally-owned governmental buildings in three counties in the Upper Peninsula of Michigan to provide a basis for evaluating and selecting the technical and economic viability of energy efficiency improvement options. The Sault Ste. Marie Tribe of Chippewa Indians will follow established Tribal procurement policies and procedures to secure the services of a qualified provider to conduct energy audits of nine designated buildings. The contracted provider willmore » be required to provide a progress schedule to the Tribe prior to commencing the project and submit an updated schedule with their monthly billings. Findings and analysis reports will be required for buildings as completed, and a complete Energy Audit Summary Report will be required to be submitted with the provider?s final billing. Conducting energy audits of the nine governmental buildings will disclose building inefficiencies to prioritize and address, resulting in reduced energy consumption and expense. These savings will allow Tribal resources to be reallocated to direct services, which will benefit Tribal members and families.« less

Energy efficient mechanisms for high-performance Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Alsaify, Baha'adnan

2009-12-01

Due to recent advances in microelectronics, the development of low cost, small, and energy efficient devices became possible. Those advances led to the birth of the Wireless Sensor Networks (WSNs). WSNs consist of a large set of sensor nodes equipped with communication capabilities, scattered in the area to monitor. Researchers focus on several aspects of WSNs. Such aspects include the quality of service the WSNs provide (data delivery delay, accuracy of data, etc...), the scalability of the network to contain thousands of sensor nodes (the terms node and sensor node are being used interchangeably), the robustness of the network (allowing the network to work even if a certain percentage of nodes fails), and making the energy consumption in the network as low as possible to prolong the network's lifetime. In this thesis, we present an approach that can be applied to the sensing devices that are scattered in an area for Sensor Networks. This work will use the well-known approach of using a awaking scheduling to extend the network's lifespan. We designed a scheduling algorithm that will reduce the delay's upper bound the reported data will experience, while at the same time keeps the advantages that are offered by the use of the awaking scheduling -- the energy consumption reduction which will lead to the increase in the network's lifetime. The wakeup scheduling is based on the location of the node relative to its neighbors and its distance from the Base Station (the terms Base Station and sink are being used interchangeably). We apply the proposed method to a set of simulated nodes using the "ONE Simulator". We test the performance of this approach with three other approaches -- Direct Routing technique, the well known LEACH algorithm, and a multi-parent scheduling algorithm. We demonstrate a good improvement on the network's quality of service and a reduction of the consumed energy.

Sensor Transmission Power Schedule for Smart Grids

NASA Astrophysics Data System (ADS)

Gao, C.; Huang, Y. H.; Li, J.; Liu, X. D.

2017-11-01

Smart grid has attracted much attention by the requirement of new generation renewable energy. Nowadays, the real-time state estimation, with the help of phasor measurement unit, plays an important role to keep smart grid stable and efficient. However, the limitation of the communication channel is not considered by related work. Considering the familiar limited on-board batteries wireless sensor in smart grid, transmission power schedule is designed in this paper, which minimizes energy consumption with proper EKF filtering performance requirement constrain. Based on the event-triggered estimation theory, the filtering algorithm is also provided to utilize the information contained in the power schedule. Finally, its feasibility and performance is demonstrated using the standard IEEE 39-bus system with phasor measurement units (PMUs).

Energy Awareness and Scheduling in Mobile Devices and High End Computing

ERIC Educational Resources Information Center

Pawaskar, Sachin S.

2013-01-01

In the context of the big picture as energy demands rise due to growing economies and growing populations, there will be greater emphasis on sustainable supply, conservation, and efficient usage of this vital resource. Even at a smaller level, the need for minimizing energy consumption continues to be compelling in embedded, mobile, and server…

Cost Minimization for Joint Energy Management and Production Scheduling Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Shah, Rahul H.

Production costs account for the largest share of the overall cost of manufacturing facilities. With the U.S. industrial sector becoming more and more competitive, manufacturers are looking for more cost and resource efficient working practices. Operations management and production planning have shown their capability to dramatically reduce manufacturing costs and increase system robustness. When implementing operations related decision making and planning, two fields that have shown to be most effective are maintenance and energy. Unfortunately, the current research that integrates both is limited. Additionally, these studies fail to consider parameter domains and optimization on joint energy and maintenance driven production planning. Accordingly, production planning methodology that considers maintenance and energy is investigated. Two models are presented to achieve well-rounded operating strategy. The first is a joint energy and maintenance production scheduling model. The second is a cost per part model considering maintenance, energy, and production. The proposed methodology will involve a Time-of-Use electricity demand response program, buffer and holding capacity, station reliability, production rate, station rated power, and more. In practice, the scheduling problem can be used to determine a joint energy, maintenance, and production schedule. Meanwhile, the cost per part model can be used to: (1) test the sensitivity of the obtained optimal production schedule and its corresponding savings by varying key production system parameters; and (2) to determine optimal system parameter combinations when using the joint energy, maintenance, and production planning model. Additionally, a factor analysis on the system parameters is conducted and the corresponding performance of the production schedule under variable parameter conditions, is evaluated. Also, parameter optimization guidelines that incorporate maintenance and energy parameter decision making in the production planning framework are discussed. A modified Particle Swarm Optimization solution technique is adopted to solve the proposed scheduling problem. The algorithm is described in detail and compared to Genetic Algorithm. Case studies are presented to illustrate the benefits of using the proposed model and the effectiveness of the Particle Swarm Optimization approach. Numerical Experiments are implemented and analyzed to test the effectiveness of the proposed model. The proposed scheduling strategy can achieve savings of around 19 to 27 % in cost per part when compared to the baseline scheduling scenarios. By optimizing key production system parameters from the cost per part model, the baseline scenarios can obtain around 20 to 35 % in savings for the cost per part. These savings further increase by 42 to 55 % when system parameter optimization is integrated with the proposed scheduling problem. Using this method, the most influential parameters on the cost per part are the rated power from production, the production rate, and the initial machine reliabilities. The modified Particle Swarm Optimization algorithm adopted allows greater diversity and exploration compared to Genetic Algorithm for the proposed joint model which results in it being more computationally efficient in determining the optimal scheduling. While Genetic Algorithm could achieve a solution quality of 2,279.63 at an expense of 2,300 seconds in computational effort. In comparison, the proposed Particle Swarm Optimization algorithm achieved a solution quality of 2,167.26 in less than half the computation effort which is required by Genetic Algorithm.

Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

NASA Astrophysics Data System (ADS)

Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

2017-10-01

Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

Machines that Manage.

ERIC Educational Resources Information Center

Kennedy, Mike

2003-01-01

Describes how facilities-management systems use technology to help schools and universities operate their buildings more efficiently, reduce energy consumption, manage inventory more accurately, keep track of supplies and maintenance schedules, and save money. (EV)

ECS: efficient communication scheduling for underwater sensor networks.

PubMed

Hong, Lu; Hong, Feng; Guo, Zhongwen; Li, Zhengbao

2011-01-01

TDMA protocols have attracted a lot of attention for underwater acoustic sensor networks (UWSNs), because of the unique characteristics of acoustic signal propagation such as great energy consumption in transmission, long propagation delay and long communication range. Previous TDMA protocols all allocated transmission time to nodes based on discrete time slots. This paper proposes an efficient continuous time scheduling TDMA protocol (ECS) for UWSNs, including the continuous time based and sender oriented conflict analysis model, the transmission moment allocation algorithm and the distributed topology maintenance algorithm. Simulation results confirm that ECS improves network throughput by 20% on average, compared to existing MAC protocols.

75 FR 12743 - Office of Energy Efficiency and Renewable Energy; Request for Information; Weatherization...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-17

..., and realistic schedule and milestones. The specifics of the outreach/marketing strategy, the funding... on a non-attribution basis for program planning and funding opportunity strategy development. DOE will review and consider all responses in its formulation of program strategies in the pursuant FOA...

ECS: Efficient Communication Scheduling for Underwater Sensor Networks

PubMed Central

Hong, Lu; Hong, Feng; Guo, Zhongwen; Li, Zhengbao

2011-01-01

TDMA protocols have attracted a lot of attention for underwater acoustic sensor networks (UWSNs), because of the unique characteristics of acoustic signal propagation such as great energy consumption in transmission, long propagation delay and long communication range. Previous TDMA protocols all allocated transmission time to nodes based on discrete time slots. This paper proposes an efficient continuous time scheduling TDMA protocol (ECS) for UWSNs, including the continuous time based and sender oriented conflict analysis model, the transmission moment allocation algorithm and the distributed topology maintenance algorithm. Simulation results confirm that ECS improves network throughput by 20% on average, compared to existing MAC protocols. PMID:22163775

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

Kim, Woohyun; Katipamula, Srinivas; Lutes, Robert G.

Small- and medium-sized (<100,000 sf) commercial buildings (SMBs) represent over 95% of the U.S. commercial building stock and consume over 60% of total site energy consumption. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability, no monitoring or failure management. Therefore, many of these buildings are operated inefficiently and consume excess energy. SMBs typically utilize packaged rooftop units (RTUs) that are controlled by an individual thermostat. There is increased urgency to improve the operating efficiency of existing commercial building stock in the U.S. for many reasons, chief among them is to mitigate the climatemore » change impacts. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy and cost savings. Another problem associated with RTUs is short-cycling, where an RTU goes through ON and OFF cycles too frequently. Excessive cycling can lead to excessive wear and lead to premature failure of the compressor or its components. The short cycling can result in a significantly decreased average efficiency (up to 10%), even if there are no physical failures in the equipment. Also, SMBs use a time-of-day scheduling is to start the RTUs before the building will be occupied and shut it off when unoccupied. Ensuring correct use of the zone set points and eliminating frequent cycling of RTUs thereby leading to persistent building operations can significantly increase the operational efficiency of the SMBs. A growing trend is to use low-cost control infrastructure that can enable scalable and cost-effective intelligent building operations. The work reported in this report describes three algorithms for detecting the zone set point temperature, RTU cycling rate and occupancy schedule detection that can be deployed on the low-cost infrastructure. These algorithms only require the zone temperature data for detection. The algorithms have been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithms were successful in detecting the set points and ON/OFF cycles accurately using the peak detection technique and occupancy schedule using symbolic aggregate approximation technique. The report describes the three algorithms, results from testing the algorithms using field data, how the algorithms can be used to improve SMBs efficiency, and presents related conclusions.« less

System-level power optimization for real-time distributed embedded systems

NASA Astrophysics Data System (ADS)

Luo, Jiong

Power optimization is one of the crucial design considerations for modern electronic systems. In this thesis, we present several system-level power optimization techniques for real-time distributed embedded systems, based on dynamic voltage scaling, dynamic power management, and management of peak power and variance of the power profile. Dynamic voltage scaling has been widely acknowledged as an important and powerful technique to trade off dynamic power consumption and delay. Efficient dynamic voltage scaling requires effective variable-voltage scheduling mechanisms that can adjust voltages and clock frequencies adaptively based on workloads and timing constraints. For this purpose, we propose static variable-voltage scheduling algorithms utilizing criticalpath driven timing analysis for the case when tasks are assumed to have uniform switching activities, as well as energy-gradient driven slack allocation for a more general scenario. The proposed techniques can achieve closeto-optimal power savings with very low computational complexity, without violating any real-time constraints. We also present algorithms for power-efficient joint scheduling of multi-rate periodic task graphs along with soft aperiodic tasks. The power issue is addressed through both dynamic voltage scaling and power management. Periodic task graphs are scheduled statically. Flexibility is introduced into the static schedule to allow the on-line scheduler to make local changes to PE schedules through resource reclaiming and slack stealing, without interfering with the validity of the global schedule. We provide a unified framework in which the response times of aperiodic tasks and power consumption are dynamically optimized simultaneously. Interconnection network fabrics point to a new generation of power-efficient and scalable interconnection architectures for distributed embedded systems. As the system bandwidth continues to increase, interconnection networks become power/energy limited as well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

Evapotranspiration-based irrigation scheduling of lettuce and broccoli

USDA-ARS?s Scientific Manuscript database

Estimation of crop evapotranspiration supports efficient irrigation water management, which in turn supports water conservation, mitigation of groundwater depletion/degradation, energy savings, and crop quality maintenance. Past research in California has revealed strong relationships between fract...

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.

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

PubMed Central

Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong

2014-01-01

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. PMID:25384005

A high performance load balance strategy for real-time multicore systems.

PubMed

Cho, Keng-Mao; Tsai, Chun-Wei; Chiu, Yi-Shiuan; Yang, Chu-Sing

2014-01-01

Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS). Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper.

A High Performance Load Balance Strategy for Real-Time Multicore Systems

PubMed Central

Cho, Keng-Mao; Tsai, Chun-Wei; Chiu, Yi-Shiuan; Yang, Chu-Sing

2014-01-01

Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS). Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper. PMID:24955382

Energy-aware scheduling of surveillance in wireless multimedia sensor networks.

PubMed

Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao

2010-01-01

Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.

Energy-efficient fault tolerance in multiprocessor real-time systems

NASA Astrophysics Data System (ADS)

Guo, Yifeng

The recent progress in the multiprocessor/multicore systems has important implications for real-time system design and operation. From vehicle navigation to space applications as well as industrial control systems, the trend is to deploy multiple processors in real-time systems: systems with 4 -- 8 processors are common, and it is expected that many-core systems with dozens of processing cores will be available in near future. For such systems, in addition to general temporal requirement common for all real-time systems, two additional operational objectives are seen as critical: energy efficiency and fault tolerance. An intriguing dimension of the problem is that energy efficiency and fault tolerance are typically conflicting objectives, due to the fact that tolerating faults (e.g., permanent/transient) often requires extra resources with high energy consumption potential. In this dissertation, various techniques for energy-efficient fault tolerance in multiprocessor real-time systems have been investigated. First, the Reliability-Aware Power Management (RAPM) framework, which can preserve the system reliability with respect to transient faults when Dynamic Voltage Scaling (DVS) is applied for energy savings, is extended to support parallel real-time applications with precedence constraints. Next, the traditional Standby-Sparing (SS) technique for dual processor systems, which takes both transient and permanent faults into consideration while saving energy, is generalized to support multiprocessor systems with arbitrary number of identical processors. Observing the inefficient usage of slack time in the SS technique, a Preference-Oriented Scheduling Framework is designed to address the problem where tasks are given preferences for being executed as soon as possible (ASAP) or as late as possible (ALAP). A preference-oriented earliest deadline (POED) scheduler is proposed and its application in multiprocessor systems for energy-efficient fault tolerance is investigated, where tasks' main copies are executed ASAP while backup copies ALAP to reduce the overlapped execution of main and backup copies of the same task and thus reduce energy consumption. All proposed techniques are evaluated through extensive simulations and compared with other state-of-the-art approaches. The simulation results confirm that the proposed schemes can preserve the system reliability while still achieving substantial energy savings. Finally, for both SS and POED based Energy-Efficient Fault-Tolerant (EEFT) schemes, a series of recovery strategies are designed when more than one (transient and permanent) faults need to be tolerated.

Energy-Efficient Scheduling for Hybrid Tasks in Control Devices for the Internet of Things

PubMed Central

Gao, Zhigang; Wu, Yifan; Dai, Guojun; Xia, Haixia

2012-01-01

In control devices for the Internet of Things (IoT), energy is one of the critical restriction factors. Dynamic voltage scaling (DVS) has been proved to be an effective method for reducing the energy consumption of processors. This paper proposes an energy-efficient scheduling algorithm for IoT control devices with hard real-time control tasks (HRCTs) and soft real-time tasks (SRTs). The main contribution of this paper includes two parts. First, it builds the Hybrid tasks with multi-subtasks of different function Weight (HoW) task model for IoT control devices. HoW describes the structure of HRCTs and SRTs, and their properties, e.g., deadlines, execution time, preemption properties, and energy-saving goals, etc. Second, it presents the Hybrid Tasks' Dynamic Voltage Scaling (HTDVS) algorithm. HTDVS first sets the slowdown factors of subtasks while meeting the different real-time requirements of HRCTs and SRTs, and then dynamically reclaims, reserves, and reuses the slack time of the subtasks to meet their ideal energy-saving goals. Experimental results show HTDVS can reduce energy consumption about 10%–80% while meeting the real-time requirements of HRCTs, HRCTs help to reduce the deadline miss ratio (DMR) of systems, and HTDVS has comparable performance with the greedy algorithm and is more favorable to keep the subtasks' ideal speeds. PMID:23112659

SPIKE: Application for ASTRO-D mission planning

NASA Technical Reports Server (NTRS)

Isobe, T.; Johnston, M.; Morgan, E.; Clark, G.

1992-01-01

SPIKE is a mission planning software system developed by a team of programmers at the STScI for use with the Hubble Space Telescope (HST). SPIKE has been developed for the purpose of automating observatory scheduling to increase the effective utilization and ultimately, scientific return from orbiting telescopes. High-level scheduling strategies using both rule-based and neural network approaches have been incorporated. Graphical displays of activities, constraints, and schedules are an important feature of the system. Although SPIKE was originally developed for the HST, it can be used for other astronomy missions including ground-based observatories. One of the missions that has decided to use SPIKE is ASTRO-D, a Japanese X-ray satellite for which the U.S. is providing a part of the scientific payload. Scheduled to fly in Feb. 1993, its four telescopes will focus X-rays over a wide energy range onto CCD's and imaging gas proportional counters. ASTRO-D will be the first X-ray imaging mission operating over the 0.5-12 keV band with high energy resolution. This combination of capabilities will enable a varied and exciting program of astronomical research to be carried out. ASTRO-D is expected to observe 5 to 20 objects per day and a total of several thousands per year. This requires the implementation of an efficient planning and scheduling system which SPIKE can provide. Although the version of SPIKE that will be used for ASTRO-D mission is almost identical to that used for the HST, there are a few differences. For example, ASTRO-D will use two ground stations for data downlinks, instead of the TDRSS system for data transmission. As a consequence ASTRO-D is constrained by limited on-board data storage capacity to schedule high data-rate observations during periods of frequent high bit rate observations accordingly. We will demonstrate the ASTRO-D version of SPIKE to show what SPIKE can provide and how efficiently it creates an observational schedule.

Smart HVAC Control in IoT: Energy Consumption Minimization with User Comfort Constraints

PubMed Central

Verikoukis, Christos

2014-01-01

Smart grid is one of the main applications of the Internet of Things (IoT) paradigm. Within this context, this paper addresses the efficient energy consumption management of heating, ventilation, and air conditioning (HVAC) systems in smart grids with variable energy price. To that end, first, we propose an energy scheduling method that minimizes the energy consumption cost for a particular time interval, taking into account the energy price and a set of comfort constraints, that is, a range of temperatures according to user's preferences for a given room. Then, we propose an energy scheduler where the user may select to relax the temperature constraints to save more energy. Moreover, thanks to the IoT paradigm, the user may interact remotely with the HVAC control system. In particular, the user may decide remotely the temperature of comfort, while the temperature and energy consumption information is sent through Internet and displayed at the end user's device. The proposed algorithms have been implemented in a real testbed, highlighting the potential gains that can be achieved in terms of both energy and cost. PMID:25054163

Smart HVAC control in IoT: energy consumption minimization with user comfort constraints.

PubMed

Serra, Jordi; Pubill, David; Antonopoulos, Angelos; Verikoukis, Christos

2014-01-01

Smart grid is one of the main applications of the Internet of Things (IoT) paradigm. Within this context, this paper addresses the efficient energy consumption management of heating, ventilation, and air conditioning (HVAC) systems in smart grids with variable energy price. To that end, first, we propose an energy scheduling method that minimizes the energy consumption cost for a particular time interval, taking into account the energy price and a set of comfort constraints, that is, a range of temperatures according to user's preferences for a given room. Then, we propose an energy scheduler where the user may select to relax the temperature constraints to save more energy. Moreover, thanks to the IoT paradigm, the user may interact remotely with the HVAC control system. In particular, the user may decide remotely the temperature of comfort, while the temperature and energy consumption information is sent through Internet and displayed at the end user's device. The proposed algorithms have been implemented in a real testbed, highlighting the potential gains that can be achieved in terms of both energy and cost.

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

Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC

PubMed Central

Li, Xiangyu; Xie, Nijie; Tian, Xinyue

2017-01-01

This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget. PMID:28208730

Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC.

PubMed

Li, Xiangyu; Xie, Nijie; Tian, Xinyue

2017-02-08

This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget.

Energy-Efficient Data Collection Method for Sensor Networks by Integrating Asymmetric Communication and Wake-Up Radio

PubMed Central

Iwata, Masanari; Tang, Suhua; Obana, Sadao

2018-01-01

In large-scale wireless sensor networks (WSNs), nodes close to sink nodes consume energy more quickly than other nodes due to packet forwarding. A mobile sink is a good solution to this issue, although it causes two new problems to nodes: (i) overhead of updating routing information; and (ii) increased operating time due to aperiodic query. To solve these problems, this paper proposes an energy-efficient data collection method, Sink-based Centralized transmission Scheduling (SC-Sched), by integrating asymmetric communication and wake-up radio. Specifically, each node is equipped with a low-power wake-up receiver. The sink node determines transmission scheduling, and transmits a wake-up message using a large transmission power, directly activating a pair of nodes simultaneously which will communicate with a normal transmission power. This paper further investigates how to deal with frame loss caused by fading and how to mitigate the impact of the wake-up latency of communication modules. Simulation evaluations confirm that using multiple channels effectively reduces data collection time and SC-Sched works well with a mobile sink. Compared with the conventional duty-cycling method, SC-Sched greatly reduces total energy consumption and improves the network lifetime by 7.47 times in a WSN with 4 data collection points and 300 sensor nodes. PMID:29642397

The Hour of Truth: The Conflict in Ukraine - Implications for Europe’s Energy Security and the Lessons for the U.S. Army

DTIC Science & Technology

2015-11-01

energy efficiency.25 The rules are scheduled to go into effect in 2016. One of the toughest components for coal power plants to meet will be the NOx...coal power plants out of business by the early-2020s.30 High Cost and Other Challenges of Renewables. Renewable energy has been a focus of the envi...will be explained later in detail. Coal: An Environmentally Problematic Energy Source. Besides CO2 emissions, burning coal pollutes the environment

Greenbuilt Retrofit Test House Final Report

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

Sparn, B.; Hudon, K.; Earle, L.

2014-06-01

The Greenbuilt house is a 1980's era house in the Sacramento area that was a prominent part of Sacramento Municipal Utility District's (SMUD) Energy Efficient Remodel Demonstration Program. The house underwent an extensive remodel, aimed at improving overall energy efficiency with a goal of reducing the home's energy use by 50%. NREL researchers performed a number of tests on the major systems touched by the retrofit to ensure they were working as planned. Additionally, SMUD rented the house from Greenbuilt Construction for a year to allow NREL to perform a number of tests on the cooling system and the watermore » heating system. The goal of the space conditioning tests was to find the best ways to cut cooling loads and shift the summer peak. The water heating system, comprised of an add-on heat pump water heater and an integrated collector-storage solar water heater, was operated with a number of different draw profiles to see how varying hot water draw volume and schedule affected the performance of the system as a whole. All the experiments were performed with the house empty, with a simulated occupancy schedule running in the house to mimic the load imposed by real occupants.« less

Variable Scheduling to Mitigate Channel Losses in Energy-Efficient Body Area Networks

PubMed Central

Tselishchev, Yuriy; Boulis, Athanassios; Libman, Lavy

2012-01-01

We consider a typical body area network (BAN) setting in which sensor nodes send data to a common hub regularly on a TDMA basis, as defined by the emerging IEEE 802.15.6 BAN standard. To reduce transmission losses caused by the highly dynamic nature of the wireless channel around the human body, we explore variable TDMA scheduling techniques that allow the order of transmissions within each TDMA round to be decided on the fly, rather than being fixed in advance. Using a simple Markov model of the wireless links, we devise a number of scheduling algorithms that can be performed by the hub, which aim to maximize the expected number of successful transmissions in a TDMA round, and thereby significantly reduce transmission losses as compared with a static TDMA schedule. Importantly, these algorithms do not require a priori knowledge of the statistical properties of the wireless channels, and the reliability improvement is achieved entirely via shuffling the order of transmissions among devices, and does not involve any additional energy consumption (e.g., retransmissions). We evaluate these algorithms directly on an experimental set of traces obtained from devices strapped to human subjects performing regular daily activities, and confirm that the benefits of the proposed variable scheduling algorithms extend to this practical setup as well. PMID:23202183

Energy-efficient algorithm for broadcasting in ad hoc wireless sensor networks.

PubMed

Xiong, Naixue; Huang, Xingbo; Cheng, Hongju; Wan, Zheng

2013-04-12

Broadcasting is a common and basic operation used to support various network protocols in wireless networks. To achieve energy-efficient broadcasting is especially important for ad hoc wireless sensor networks because sensors are generally powered by batteries with limited lifetimes. Energy consumption for broadcast operations can be reduced by minimizing the number of relay nodes based on the observation that data transmission processes consume more energy than data reception processes in the sensor nodes, and how to improve the network lifetime is always an interesting issue in sensor network research. The minimum-energy broadcast problem is then equivalent to the problem of finding the minimum Connected Dominating Set (CDS) for a connected graph that is proved NP-complete. In this paper, we introduce an Efficient Minimum CDS algorithm (EMCDS) with help of a proposed ordered sequence list. EMCDS does not concern itself with node energy and broadcast operations might fail if relay nodes are out of energy. Next we have proposed a Minimum Energy-consumption Broadcast Scheme (MEBS) with a modified version of EMCDS, and aimed at providing an efficient scheduling scheme with maximized network lifetime. The simulation results show that the proposed EMCDS algorithm can find smaller CDS compared with related works, and the MEBS can help to increase the network lifetime by efficiently balancing energy among nodes in the networks.

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.

Smart Energy Management of Multiple Full Cell Powered Applications

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

MOhammad S. Alam

2007-04-23

In this research project the University of South Alabama research team has been investigating smart energy management and control of multiple fuel cell power sources when subjected to varying demands of electrical and thermal loads together with demands of hydrogen production. This research has focused on finding the optimal schedule of the multiple fuel cell power plants in terms of electric, thermal and hydrogen energy. The optimal schedule is expected to yield the lowest operating cost. Our team is also investigating the possibility of generating hydrogen using photoelectrochemical (PEC) solar cells through finding materials for efficient light harvesting photoanodes. Themore » goal is to develop an efficient and cost effective PEC solar cell system for direct electrolysis of water. In addition, models for hydrogen production, purification, and storage will be developed. The results obtained and the data collected will be then used to develop a smart energy management algorithm whose function is to maximize energy conservation within a managed set of appliances, thereby lowering O/M costs of the Fuel Cell power plant (FCPP), and allowing more hydrogen generation opportunities. The Smart Energy Management and Control (SEMaC) software, developed earlier, controls electrical loads in an individual home to achieve load management objectives such that the total power consumption of a typical residential home remains below the available power generated from a fuel cell. In this project, the research team will leverage the SEMaC algorithm developed earlier to create a neighborhood level control system.« less

A genetic algorithm-based job scheduling model for big data analytics.

PubMed

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications

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

Ramamurthy, Byravamurthy

2014-05-05

In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published severalmore » conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.« less

Energy-efficient orthogonal frequency division multiplexing-based passive optical network based on adaptive sleep-mode control and dynamic bandwidth allocation

NASA Astrophysics Data System (ADS)

Zhang, Chongfu; Xiao, Nengwu; Chen, Chen; Yuan, Weicheng; Qiu, Kun

2016-02-01

We propose an energy-efficient orthogonal frequency division multiplexing-based passive optical network (OFDM-PON) using adaptive sleep-mode control and dynamic bandwidth allocation. In this scheme, a bidirectional-centralized algorithm named the receiver and transmitter accurate sleep control and dynamic bandwidth allocation (RTASC-DBA), which has an overall bandwidth scheduling policy, is employed to enhance the energy efficiency of the OFDM-PON. The RTASC-DBA algorithm is used in an optical line terminal (OLT) to control the sleep mode of an optical network unit (ONU) sleep and guarantee the quality of service of different services of the OFDM-PON. The obtained results show that, by using the proposed scheme, the average power consumption of the ONU is reduced by ˜40% when the normalized ONU load is less than 80%, compared with the average power consumption without using the proposed scheme.

Energy efficient engine sector combustor rig test program

NASA Technical Reports Server (NTRS)

Dubiel, D. J.; Greene, W.; Sundt, C. V.; Tanrikut, S.; Zeisser, M. H.

1981-01-01

Under the NASA-sponsored Energy Efficient Engine program, Pratt & Whitney Aircraft has successfully completed a comprehensive combustor rig test using a 90-degree sector of an advanced two-stage combustor with a segmented liner. Initial testing utilized a combustor with a conventional louvered liner and demonstrated that the Energy Efficient Engine two-stage combustor configuration is a viable system for controlling exhaust emissions, with the capability to meet all aerothermal performance goals. Goals for both carbon monoxide and unburned hydrocarbons were surpassed and the goal for oxides of nitrogen was closely approached. In another series of tests, an advanced segmented liner configuration with a unique counter-parallel FINWALL cooling system was evaluated at engine sea level takeoff pressure and temperature levels. These tests verified the structural integrity of this liner design. Overall, the results from the program have provided a high level of confidence to proceed with the scheduled Combustor Component Rig Test Program.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

PubMed Central

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

PubMed

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-10-14

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

Supercritical Carbon Dioxide Power Generation System Definition: Concept Definition and Capital Cost Estimate

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

Stoddard, Larry; Galluzzo, Geoff; Andrew, Daniel

The Department of Energy’s (DOE’s) Office of Renewable Power (ORP) has been tasked to provide effective program management and strategic direction for all of the DOE’s Energy Efficiency & Renewable Energy’s (EERE’s) renewable power programs. The ORP’s efforts to accomplish this mission are aligned with national energy policies, DOE strategic planning, EERE’s strategic planning, Congressional appropriation, and stakeholder advice. ORP is supported by three renewable energy offices, of which one is the Solar Energy Technology Office (SETO) whose SunShot Initiative has a mission to accelerate research, development and large scale deployment of solar technologies in the United States. SETO hasmore » a goal of reducing the cost of Concentrating Solar Power (CSP) by 75 percent of 2010 costs by 2020 to reach parity with base-load energy rates, and 30 percent further reductions by 2030. The SunShot Initiative is promoting the implementation of high temperature CSP with thermal energy storage allowing generation during high demand hours. The SunShot Initiative has funded significant research and development work on component testing, with attention to high temperature molten salts, heliostats, receiver designs, and high efficiency high temperature supercritical CO 2 (sCO2) cycles. DOE retained Black & Veatch to support SETO’s SunShot Initiative for CSP solar power tower technology in the following areas: 1. Concept definition, including costs and schedule, of a flexible test facility to be used to test and prove components in part to support financing. 2. Concept definition, including costs and schedule, of an integrated high temperature molten salt (MS) facility with thermal energy storage and with a supercritical CO 2 cycle generating approximately 10MWe. 3. Concept definition, including costs and schedule, of an integrated high temperature falling particle facility with thermal energy storage and with a supercritical CO 2 cycle generating approximately 10MWe. This report addresses the concept definition of the sCO2 power generation system, a sub-set of items 2 and 3 above. Other reports address the balance of items 1 to 3 above as well as the MS/sCO2 integrated 10MWe facility, Item 2.« less

Molten Salt: Concept Definition and Capital Cost Estimate

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

Stoddard, Larry; Andrew, Daniel; Adams, Shannon

The Department of Energy’s (DOE’s) Office of Renewable Power (ORP) has been tasked to provide effective program management and strategic direction for all of the DOE’s Energy Efficiency & Renewable Energy’s (EERE’s) renewable power programs. The ORP’s efforts to accomplish this mission are aligned with national energy policies, DOE strategic planning, EERE’s strategic planning, Congressional appropriation, and stakeholder advice. ORP is supported by three renewable energy offices, of which one is the Solar Energy Technology Office (SETO) whose SunShot Initiative has a mission to accelerate research, development and large scale deployment of solar technologies in the United States. SETO hasmore » a goal of reducing the cost of Concentrating Solar Power (CSP) by 75 percent of 2010 costs by 2020 to reach parity with base-load energy rates, and to reduce costs 30 percent further by 2030. The SunShot Initiative is promoting the implementation of high temperature CSP with thermal energy storage allowing generation during high demand hours. The SunShot Initiative has funded significant research and development work on component testing, with attention to high temperature molten salts, heliostats, receiver designs, and high efficiency high temperature supercritical CO 2 (sCO2) cycles. DOE retained Black & Veatch to support SETO’s SunShot Initiative for CSP solar power tower technology in the following areas: 1. Concept definition, including costs and schedule, of a flexible test facility to be used to test and prove components in part to support financing. 2. Concept definition, including costs and schedule, of an integrated high temperature molten salt (MS) facility with thermal energy storage and with a supercritical CO 2 cycle generating approximately 10MWe. 3. Concept definition, including costs and schedule, of an integrated high temperature falling particle facility with thermal energy storage and with a supercritical CO 2 cycle generating approximately 10MWe. This report addresses the concept definition of the MS/sCO2 integrated 10MWe facility, Item No. 2 above. Other reports address Items No. 1 and No. 3 above.« less

Chance-constrained economic dispatch with renewable energy and storage

DOE PAGES

Cheng, Jianqiang; Chen, Richard Li-Yang; Najm, Habib N.; ...

2018-04-19

Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample averagemore » approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.« less

Chance-constrained economic dispatch with renewable energy and storage

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

Cheng, Jianqiang; Chen, Richard Li-Yang; Najm, Habib N.

Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample averagemore » approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.« less

A Robust and Energy-Efficient Transport Protocol for Cognitive Radio Sensor Networks

PubMed Central

Salim, Shelly; Moh, Sangman

2014-01-01

A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. CRSNs benefit from cognitive radio capabilities such as dynamic spectrum access and transmission parameters reconfigurability; but cognitive radio also brings additional challenges and leads to higher energy consumption. Motivated to improve the energy efficiency in CRSNs, we propose a robust and energy-efficient transport protocol (RETP). The novelties of RETP are two-fold: (I) it combines distributed channel sensing and channel decision with centralized schedule-based data transmission; and (II) it differentiates the types of data transmission on the basis of data content and adopts different acknowledgment methods for different transmission types. To the best of our knowledge, no transport layer protocols have yet been designed for CRSNs. Simulation results show that the proposed protocol achieves remarkably longer network lifetime and shorter event-detection delay compared to those achieved with a conventional transport protocol, while simultaneously preserving event-detection reliability. PMID:25333288

Optimizing energy for a ‘green’ vaccine supply chain

PubMed Central

Lloyd, John; McCarney, Steve; Ouhichi, Ramzi; Lydon, Patrick; Zaffran, Michel

2015-01-01

This paper describes an approach piloted in the Kasserine region of Tunisia to increase the energy efficiency of the distribution of vaccines and temperature sensitive drugs. The objectives of an approach, known as the ‘net zero energy’ (NZE) supply chain were demonstrated within the first year of operation. The existing distribution system was modified to store vaccines and medicines in the same buildings and to transport them according to pre-scheduled and optimized delivery circuits. Electric utility vehicles, dedicated to the integrated delivery of vaccines and medicines, improved the regularity and reliability of the supply chains. Solar energy, linked to the electricity grid at regional and district stores, supplied over 100% of consumption meeting all energy needs for storage, cooling and transportation. Significant benefits to the quality and costs of distribution were demonstrated. Supply trips were scheduled, integrated and reliable, energy consumption was reduced, the recurrent cost of electricity was eliminated and the release of carbon to the atmosphere was reduced. Although the initial capital cost of scaling up implementation of NZE remain high today, commercial forecasts predict cost reduction for solar energy and electric vehicles that may permit a step-wise implementation over the next 7–10 years. Efficiency in the use of energy and in the deployment of transport is already a critical component of distribution logistics in both private and public sectors of industrialized countries. The NZE approach has an intensified rationale in countries where energy costs threaten the maintenance of public health services in areas of low population density. In these countries where the mobility of health personnel and timely arrival of supplies is at risk, NZE has the potential to reduce energy costs and release recurrent budget to other needs of service delivery while also improving the supply chain. PMID:25444811

Incentive-compatible demand-side management for smart grids based on review strategies

NASA Astrophysics Data System (ADS)

Xu, Jie; van der Schaar, Mihaela

2015-12-01

Demand-side load management is able to significantly improve the energy efficiency of smart grids. Since the electricity production cost depends on the aggregate energy usage of multiple consumers, an important incentive problem emerges: self-interested consumers want to increase their own utilities by consuming more than the socially optimal amount of energy during peak hours since the increased cost is shared among the entire set of consumers. To incentivize self-interested consumers to take the socially optimal scheduling actions, we design a new class of protocols based on review strategies. These strategies work as follows: first, a review stage takes place in which a statistical test is performed based on the daily prices of the previous billing cycle to determine whether or not the other consumers schedule their electricity loads in a socially optimal way. If the test fails, the consumers trigger a punishment phase in which, for a certain time, they adjust their energy scheduling in such a way that everybody in the consumer set is punished due to an increased price. Using a carefully designed protocol based on such review strategies, consumers then have incentives to take the socially optimal load scheduling to avoid entering this punishment phase. We rigorously characterize the impact of deploying protocols based on review strategies on the system's as well as the users' performance and determine the optimal design (optimal billing cycle, punishment length, etc.) for various smart grid deployment scenarios. Even though this paper considers a simplified smart grid model, our analysis provides important and useful insights for designing incentive-compatible demand-side management schemes based on aggregate energy usage information in a variety of practical scenarios.

A Green Prison: Santa Rita Jail Creeps Towards Zero Net Energy (ZNE)

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

Marnay, Chris; DeForest, Nicholas; Stadler, Michael

2011-03-18

A large project is underway at Alameda County's twenty-year old 45 ha 4,000-inmate Santa Rita Jail, about 70 km east of San Francisco. Often described as a green prison, it has a considerable installed base of distributed energy resources including a seven-year old 1.2 MW PV array, a four-year old 1 MW fuel cell with heat recovery, and efficiency investments. A current US$14 M expansion will add approximately 2 MW of NaS batteries, and undetermined wind capacity and a concentrating solar thermal system. This ongoing effort by a progressive local government with considerable Federal and State support provides some excellentmore » lessons for the struggle to lower building carbon footprint. The Distributed Energy Resources Customer Adoption Model (DER-CAM) finds true optimal combinations of equipment and operating schedules for microgrids that minimize energy bills and/or carbon emissions without 2 of 12 significant searching or rules-of-thumb prioritization, such as"efficiency first then on-site generation." The results often recommend complex systems, and sensitivities show how policy changes will affect choices. This paper reports an analysis of the historic performance of the PV system and fuel cell, describes the complex optimization applied to the battery scheduling, and shows how results will affect the jail's operational costs, energy consumption, and carbon footprint. DER-CAM is used to assess the existing and proposed DER equipment in its ability to reduce tariff charges.« less

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

Erhart, Steven C.; Spencer, Charles G.

The accomplishments to date and the long-range planning of the Y-12 Energy Management and Sustainability and Stewardship programs support the U.S. Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) vision for a commitment to energy effi ciency and sustainability and to achievement of the Guiding Principles. Specifi cally, the Y-12 vision is to support the Environment, Safety and Health Policy and the DOE Strategic Sustainability Performance Plan (SSPP), while promoting overall sustainability and reduction of greenhouse gas (GHG) emissions. The mission of the Y-12 Energy Management program is to incorporate energy-efficient technologies site-wide and to position Y-12more » to meet NNSA energy requirement needs through 2025 and beyond. This plan addresses: Greenhouse Gas Reduction and Comprehensive Greenhouse Gas Inventory; Buildings, ESPC Initiative Schedule, and Regional and Local Planning; Fleet Management; Water Use Efficiency and Management; Pollution Prevention and Waste Reduction; Sustainable Acquisition; Electronic Stewardship and Data Centers; Renewable Energy; Climate Change; and Budget and Funding.« less

Development of Next Generation Energy Audit Protocols for the Rapid and Advanced Analysis of Building Energy Use

NASA Astrophysics Data System (ADS)

Hartley, Christopher Ahlvin

Current building energy auditing techniques are outdated and lack targeted, actionable information. These analyses only use one year's worth of monthly electricity and gas bills to define energy conservation and efficiency measures. These limited data sets cannot provide robust, directed energy reduction recommendations. The need is apparent for an overhaul of existing energy audit protocols to utilize all data that is available from the building's utility provider, installed energy management system (EMS), and sub-metering devices. This thesis analyzed the current state-of-the-art in energy audits, generated a next generation energy audit protocol, and conducted both audits types on four case study buildings to find out what additional information can be obtained from additional data sources and increased data gathering resolutions. Energy data from each case study building were collected using a variety of means including utility meters, whole building energy meters, EMS systems, and sub-metering devices. In addition to conducting an energy analysis for each case study building using the current and next generation energy audit protocols, two building energy models were created using the programs eQuest and EnergyPlus. The current and next generation energy audit protocol results were compared to one another upon completion. The results show that using the current audit protocols, only variations in season are apparent. Results from the developed next generation energy audit protocols show that in addition to seasonal variations, building heating, ventilation and air conditioning (HVAC) schedules, occupancy schedules, baseline and peak energy demand levels, and malfunctioning equipment can be found. This new protocol may also be used to quickly generate accurate building models because of the increased resolution that yields scheduling information. The developed next generation energy auditing protocol is scalable and can work for many building types across the United States, and perhaps the world.

Experimental energy consumption of Frame Slotted ALOHA and Distributed Queuing for data collection scenarios.

PubMed

Tuset-Peiro, Pere; Vazquez-Gallego, Francisco; Alonso-Zarate, Jesus; Alonso, Luis; Vilajosana, Xavier

2014-07-24

Data collection is a key scenario for the Internet of Things because it enables gathering sensor data from distributed nodes that use low-power and long-range wireless technologies to communicate in a single-hop approach. In this kind of scenario, the network is composed of one coordinator that covers a particular area and a large number of nodes, typically hundreds or thousands, that transmit data to the coordinator upon request. Considering this scenario, in this paper we experimentally validate the energy consumption of two Medium Access Control (MAC) protocols, Frame Slotted ALOHA (FSA) and Distributed Queuing (DQ). We model both protocols as a state machine and conduct experiments to measure the average energy consumption in each state and the average number of times that a node has to be in each state in order to transmit a data packet to the coordinator. The results show that FSA is more energy efficient than DQ if the number of nodes is known a priori because the number of slots per frame can be adjusted accordingly. However, in such scenarios the number of nodes cannot be easily anticipated, leading to additional packet collisions and a higher energy consumption due to retransmissions. Contrarily, DQ does not require to know the number of nodes in advance because it is able to efficiently construct an ad hoc network schedule for each collection round. This kind of a schedule ensures that there are no packet collisions during data transmission, thus leading to an energy consumption reduction above 10% compared to FSA.

Baseline tests of the battronic Minivan electric delivery van

NASA Technical Reports Server (NTRS)

Dustin, M. O.; Soltis, R. F.; Bozek, J. M.; Maslowski, E. A.

1977-01-01

An electric passenger vehicle was tested to develop data characterizing the state of the art of electric and hybrid vehicles. The test measured vehicle maximum speed, range at constant speed, range over stop-and-go driving schedules, maximum acceleration, gradeability and limit, road energy consumption, road power, indicated energy consumption, braking capability and battery charge efficiency. The data obtained are to serve as a baseline to compare improvements in electric and hybrid vehicle technologies and to assist in establishing performance standards.

Baseline tests of the EPC Hummingbird electric passenger vehicle

NASA Technical Reports Server (NTRS)

Slavik, R. J.; Maslowski, E. A.; Sargent, N. B.; Birchenough, A. G.

1977-01-01

The rear-mounted internal combustion engine in a four-passenger Volkswagen Thing was replaced with an electric motor made by modifying an aircraft generator and powered by 12 heavy-duty, lead-acid battery modules. Vehicle performance tests were conducted to measure vehicle maximum speed, range at constant speed, range over stop-and-go driving schedules, maximum acceleration, gradeability limit, road energy consumption, road power, indicated energy consumption, braking capability, battery charger efficiency, and battery characteristics. Test results are presented in tables and charts.

The high energy astronomy observatories

NASA Technical Reports Server (NTRS)

Neighbors, A. K.; Doolittle, R. F.; Halpers, R. E.

1977-01-01

The forthcoming NASA project of orbiting High Energy Astronomy Observatories (HEAO's) designed to probe the universe by tracing celestial radiations and particles is outlined. Solutions to engineering problems concerning HEAO's which are integrated, yet built to function independently are discussed, including the onboard digital processor, mirror assembly and the thermal shield. The principle of maximal efficiency with minimal cost and the potential capability of the project to provide explanations to black holes, pulsars and gamma-ray bursts are also stressed. The first satellite is scheduled for launch in April 1977.

Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks

PubMed Central

Wei, Yunkai; Ma, Xiaohui; Yang, Ning; Chen, Yijin

2017-01-01

Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller’s direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20–40% while ensuring feasible data delay. PMID:28914816

Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks.

PubMed

Wei, Yunkai; Ma, Xiaohui; Yang, Ning; Chen, Yijin

2017-09-15

Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller's direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20-40% while ensuring feasible data delay.

TV Energy Consumption Trends and Energy-Efficiency Improvement Options

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

Park, Won Young; Phadke, Amol; Shah, Nihar

2011-07-01

The SEAD initiative aims to transform the global market by increasing the penetration of highly efficient equipment and appliances. SEAD is a government initiative whose activities and projects engage the private sector to realize the large global energy savings potential from improved appliance and equipment efficiency. SEAD seeks to enable high-level global action by informing the Clean Energy Ministerial dialogue as one of the initiatives in the Global Energy Efficiency Challenge. In keeping with its goal of achieving global energy savings through efficiency, SEAD was approved as a task within the International Partnership for Energy Efficiency Cooperation (IPEEC) in Januarymore » 2010. SEAD partners work together in voluntary activities to: (1) ?raise the efficiency ceiling? by pulling super-efficient appliances and equipment into the market through cooperation on measures like incentives, procurement, awards, and research and development (R&D) investments; (2) ?raise the efficiency floor? by working together to bolster national or regional policies like minimum efficiency standards; and (3) ?strengthen the efficiency foundations? of programs by coordinating technical work to support these activities. Although not all SEAD partners may decide to participate in every SEAD activity, SEAD partners have agreed to engage actively in their particular areas of interest through commitment of financing, staff, consultant experts, and other resources. In addition, all SEAD partners are committed to share information, e.g., on implementation schedules for and the technical detail of minimum efficiency standards and other efficiency programs. Information collected and created through SEAD activities will be shared among all SEAD partners and, to the extent appropriate, with the global public.As of April 2011, the governments participating in SEAD are: Australia, Brazil, Canada, the European Commission, France, Germany, India, Japan, Korea, Mexico, Russia, South Africa, Sweden, the United Arab Emirates, the United Kingdom, and the United States. More information on SEAD is available from its website at http://www.superefficient.org/.« less

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.

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

Comprehensive Anti-error Study on Power Grid Dispatching Based on Regional Regulation and Integration

NASA Astrophysics Data System (ADS)

Zhang, Yunju; Chen, Zhongyi; Guo, Ming; Lin, Shunsheng; Yan, Yinyang

2018-01-01

With the large capacity of the power system, the development trend of the large unit and the high voltage, the scheduling operation is becoming more frequent and complicated, and the probability of operation error increases. This paper aims at the problem of the lack of anti-error function, single scheduling function and low working efficiency for technical support system in regional regulation and integration, the integrated construction of the error prevention of the integrated architecture of the system of dispatching anti - error of dispatching anti - error of power network based on cloud computing has been proposed. Integrated system of error prevention of Energy Management System, EMS, and Operation Management System, OMS have been constructed either. The system architecture has good scalability and adaptability, which can improve the computational efficiency, reduce the cost of system operation and maintenance, enhance the ability of regional regulation and anti-error checking with broad development prospects.

Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy

DOE PAGES

Rosewater, David; Ferreira, Summer; Schoenwald, David; ...

2018-01-25

Battery energy storage systems (BESS) are a critical technology for integrating high penetration renewable power on an intelligent electrical grid. As limited energy restricts the steady-state operational state-of-charge (SoC) of storage systems, SoC forecasting models are used to determine feasible charge and discharge schedules that supply grid services. Smart grid controllers use SoC forecasts to optimize BESS schedules to make grid operation more efficient and resilient. This study presents three advances in BESS state-of-charge forecasting. First, two forecasting models are reformulated to be conducive to parameter optimization. Second, a new method for selecting optimal parameter values based on operational datamore » is presented. Last, a new framework for quantifying model accuracy is developed that enables a comparison between models, systems, and parameter selection methods. The accuracies achieved by both models, on two example battery systems, with each method of parameter selection are then compared in detail. The results of this analysis suggest variation in the suitability of these models for different battery types and applications. Finally, the proposed model formulations, optimization methods, and accuracy assessment framework can be used to improve the accuracy of SoC forecasts enabling better control over BESS charge/discharge schedules.« less

Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy

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

Rosewater, David; Ferreira, Summer; Schoenwald, David

Battery energy storage systems (BESS) are a critical technology for integrating high penetration renewable power on an intelligent electrical grid. As limited energy restricts the steady-state operational state-of-charge (SoC) of storage systems, SoC forecasting models are used to determine feasible charge and discharge schedules that supply grid services. Smart grid controllers use SoC forecasts to optimize BESS schedules to make grid operation more efficient and resilient. This study presents three advances in BESS state-of-charge forecasting. First, two forecasting models are reformulated to be conducive to parameter optimization. Second, a new method for selecting optimal parameter values based on operational datamore » is presented. Last, a new framework for quantifying model accuracy is developed that enables a comparison between models, systems, and parameter selection methods. The accuracies achieved by both models, on two example battery systems, with each method of parameter selection are then compared in detail. The results of this analysis suggest variation in the suitability of these models for different battery types and applications. Finally, the proposed model formulations, optimization methods, and accuracy assessment framework can be used to improve the accuracy of SoC forecasts enabling better control over BESS charge/discharge schedules.« less

1993 Wholesale Power and Transmission Rate Schedules.

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

US Bonneville Power Administration

1993-10-01

Bonneville Power Administration 1993 Wholesale Power Rate Schedules and General Rate Schedule Provisions and 1993 Transmission Rate Schedules and General Transmission Rate Schedule Provisions, contained herein, were approved on an interim basis effective October 1, 1993. These rate schedules and provisions were approved by the Federal Energy Commission, United States Department of Energy, in September, 1993. These rate schedules and provisions supersede the Administration`s Wholesale Power Rate Schedules and General Rate Schedule Provisions and Transmission Rate Schedules and General Transmission Rate Schedule Provisions effective October 1, 1991.

Efficiently Scheduling Multi-core Guest Virtual Machines on Multi-core Hosts in Network Simulation

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

Yoginath, Srikanth B; Perumalla, Kalyan S

2011-01-01

Virtual machine (VM)-based simulation is a method used by network simulators to incorporate realistic application behaviors by executing actual VMs as high-fidelity surrogates for simulated end-hosts. A critical requirement in such a method is the simulation time-ordered scheduling and execution of the VMs. Prior approaches such as time dilation are less efficient due to the high degree of multiplexing possible when multiple multi-core VMs are simulated on multi-core host systems. We present a new simulation time-ordered scheduler to efficiently schedule multi-core VMs on multi-core real hosts, with a virtual clock realized on each virtual core. The distinguishing features of ourmore » approach are: (1) customizable granularity of the VM scheduling time unit on the simulation time axis, (2) ability to take arbitrary leaps in virtual time by VMs to maximize the utilization of host (real) cores when guest virtual cores idle, and (3) empirically determinable optimality in the tradeoff between total execution (real) time and time-ordering accuracy levels. Experiments show that it is possible to get nearly perfect time-ordered execution, with a slight cost in total run time, relative to optimized non-simulation VM schedulers. Interestingly, with our time-ordered scheduler, it is also possible to reduce the time-ordering error from over 50% of non-simulation scheduler to less than 1% realized by our scheduler, with almost the same run time efficiency as that of the highly efficient non-simulation VM schedulers.« less

Carbon emissions from U.S. ethylene production under climate change policies.

PubMed

Ruth, Matthias; Amato, Anthony D; Davidsdottir, Brynhildur

2002-01-15

This paper presents the results from a dynamic computer model of U.S. ethylene production, designed to explore implications of alternative climate change policies for the industry's energy use and carbon emissions profiles. The model applies to the aggregate ethylene industry but distinguishes its main cracker types, fuels used as feedstocks and for process energy, as well as the industry's capital vintage structure and vintage-specific efficiencies. Results indicate that policies which increase the cost of carbon of process energy-such as carbon taxes or carbon permit systems-are relatively blunt instruments for cutting carbon emissions from ethylene production. In contrast, policies directly affecting the relative efficiencies of new to old capital-such as R&D stimuli or accelerated depreciation schedules-may be more effective in leveraging the industry's potential for carbon emissions reductions.

Stochastic Modelling of Wireless Energy Transfer

NASA Technical Reports Server (NTRS)

Veilleux, Shaun; Almaghasilah, Ahmed; Abedi, Ali; Wilkerson, DeLisa

2017-01-01

This study investigates the efficiency of a new method of powering remote sensors by the means of wireless energy transfer. The increased use of sensors for data collection comes with the inherent cost of supplying power from sources such as power cables or batteries. Wireless energy transfer technology eliminates the need for power cables or periodic battery replacement. The time and cost of setting up or expanding a sensor network will be reduced while allowing sensors to be placed in areas where running power cables or battery replacement is not feasible. This paper models wireless channels for power and data separately. Smart scheduling for the data channel is proposed to avoid transmitting data on a noisy channel where the probability of data loss is high to improve power efficiency. Analytical models have been developed and verified using simulations.

Advanced lighting guidelines: 1993. Final report

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

Eley, C.; Tolen, T.M.; Benya, J.R.

1993-12-31

The 1993 Advanced Lighting Guidelines document consists of twelve guidelines that provide an overview of specific lighting technologies and design application techniques utilizing energy-efficient lighting practice. Lighting Design Practice assesses energy-efficient lighting strategies, discusses lighting issues, and explains how to obtain quality lighting design and consulting services. Luminaires and Lighting Systems surveys luminaire equipment designed to take advantage of advanced technology lamp products and includes performance tables that allow for accurate estimation of luminaire light output and power input. The additional ten guidelines -- Computer-Aided Lighting Design, Energy-Efficient Fluorescent Ballasts, Full-Size Fluorescent Lamps, Compact Fluorescent Lamps, Tungsten-Halogen Lamps, Metal Halidemore » and HPS Lamps, Daylighting and Lumen Maintenance, Occupant Sensors, Time Scheduling Systems, and Retrofit Control Technologies -- each provide a product technology overview, discuss current products on the lighting equipment market, and provide application techniques. This document is intended for use by electric utility personnel involved in lighting programs, lighting designers, electrical engineers, architects, lighting manufacturers` representatives, and other lighting professionals.« less

Strategies for Optimal MAC Parameters Tuning in IEEE 802.15.6 Wearable Wireless Sensor Networks.

PubMed

Alam, Muhammad Mahtab; Ben Hamida, Elyes

2015-09-01

Wireless body area networks (WBAN) has penetrated immensely in revolutionizing the classical heath-care system. Recently, number of WBAN applications has emerged which introduce potential limits to existing solutions. In particular, IEEE 802.15.6 standard has provided great flexibility, provisions and capabilities to deal emerging applications. In this paper, we investigate the application-specific throughput analysis by fine-tuning the physical (PHY) and medium access control (MAC) parameters of the IEEE 802.15.6 standard. Based on PHY characterizations in narrow band, at the MAC layer, carrier sense multiple access collision avoidance (CSMA/CA) and scheduled access protocols are extensively analyzed. It is concluded that, IEEE 802.15.6 standard can satisfy most of the WBANs applications throughput requirements by maximum achieving 680 Kbps. However, those emerging applications which require high quality audio or video transmissions, standard is not able to meet their constraints. Moreover, delay, energy efficiency and successful packet reception are considered as key performance metrics for comparing the MAC protocols. CSMA/CA protocol provides the best results to meet the delay constraints of medical and non-medical WBAN applications. Whereas, the scheduled access approach, performs very well both in energy efficiency and packet reception ratio.

Fuel economy and life-cycle cost analysis of a fuel cell hybrid vehicle

NASA Astrophysics Data System (ADS)

Jeong, Kwi Seong; Oh, Byeong Soo

The most promising vehicle engine that can overcome the problem of present internal combustion is the hydrogen fuel cell. Fuel cells are devices that change chemical energy directly into electrical energy without combustion. Pure fuel cell vehicles and fuel cell hybrid vehicles (i.e. a combination of fuel cell and battery) as energy sources are studied. Considerations of efficiency, fuel economy, and the characteristics of power output in hybridization of fuel cell vehicle are necessary. In the case of Federal Urban Driving Schedule (FUDS) cycle simulation, hybridization is more efficient than a pure fuel cell vehicle. The reason is that it is possible to capture regenerative braking energy and to operate the fuel cell system within a more efficient range by using battery. Life-cycle cost is largely affected by the fuel cell size, fuel cell cost, and hydrogen cost. When the cost of fuel cell is high, hybridization is profitable, but when the cost of fuel cell is less than 400 US$/kW, a pure fuel cell vehicle is more profitable.

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

Results of the ETV-1 breadboard tests under steady-state and transient conditions. [conducted in the NASA-LeRC Road Load Simulator

NASA Technical Reports Server (NTRS)

Sargent, N. B.; Dustin, M. O.

1981-01-01

Steady state tests were run to characterize the system and component efficiencies over the complete speed-torque capabilities of the propulsion system in both motoring and regenerative modes of operation. The steady state data were obtained using a battery simulator to separate the effects on efficiency caused by changing battery state-of-charge and component temperature. Transient tests were performed to determine the energy profiles of the propulsion system operating over the SAE J227a driving schedules.

Improving the Efficiency of Free Energy Calculations in the Amber Molecular Dynamics Package.

PubMed

Kaus, Joseph W; Pierce, Levi T; Walker, Ross C; McCammont, J Andrew

2013-09-10

Alchemical transformations are widely used methods to calculate free energies. Amber has traditionally included support for alchemical transformations as part of the sander molecular dynamics (MD) engine. Here we describe the implementation of a more efficient approach to alchemical transformations in the Amber MD package. Specifically we have implemented this new approach within the more computational efficient and scalable pmemd MD engine that is included with the Amber MD package. The majority of the gain in efficiency comes from the improved design of the calculation, which includes better parallel scaling and reduction in the calculation of redundant terms. This new implementation is able to reproduce results from equivalent simulations run with the existing functionality, but at 2.5 times greater computational efficiency. This new implementation is also able to run softcore simulations at the λ end states making direct calculation of free energies more accurate, compared to the extrapolation required in the existing implementation. The updated alchemical transformation functionality will be included in the next major release of Amber (scheduled for release in Q1 2014) and will be available at http://ambermd.org, under the Amber license.

Improving the Efficiency of Free Energy Calculations in the Amber Molecular Dynamics Package

PubMed Central

Pierce, Levi T.; Walker, Ross C.; McCammont, J. Andrew

2013-01-01

Alchemical transformations are widely used methods to calculate free energies. Amber has traditionally included support for alchemical transformations as part of the sander molecular dynamics (MD) engine. Here we describe the implementation of a more efficient approach to alchemical transformations in the Amber MD package. Specifically we have implemented this new approach within the more computational efficient and scalable pmemd MD engine that is included with the Amber MD package. The majority of the gain in efficiency comes from the improved design of the calculation, which includes better parallel scaling and reduction in the calculation of redundant terms. This new implementation is able to reproduce results from equivalent simulations run with the existing functionality, but at 2.5 times greater computational efficiency. This new implementation is also able to run softcore simulations at the λ end states making direct calculation of free energies more accurate, compared to the extrapolation required in the existing implementation. The updated alchemical transformation functionality will be included in the next major release of Amber (scheduled for release in Q1 2014) and will be available at http://ambermd.org, under the Amber license. PMID:24185531

CENet: A Cabinet Environmental Sensing Network

PubMed Central

Zhang, Zusheng; Yu, Fengqi; Chen, Liang; Cao, Guangmin

2010-01-01

For data center cooling and intelligent substation systems, real time cabinet environmental monitoring is a strong requirement. Monitoring data, such as temperature, humidity, and noise, is important for operators to manage the facilities in cabinets. We here propose a sensing network, called CENet, which is energy efficient and reliable for cabinet environmental monitoring. CENet achieves above 93% reliable data yield and sends fewer beacons compared to periodic beaconing. It does so through a data-aided routing protocol. In addition, based on B-MAC, we propose a scheduling scheme to increase the lifetime of the network by reducing unnecessary message snooping and channel listening, thus it is more energy efficient than B-MAC. The performance of CENet is evaluated by simulations and experiments. PMID:22205856

10 CFR 490.302 - Vehicle acquisition mandate schedule.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 3 2012-01-01 2012-01-01 false Vehicle acquisition mandate schedule. 490.302 Section 490.302 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Alternative Fuel Provider Vehicle Acquisition Mandate § 490.302 Vehicle acquisition mandate schedule. (a...

10 CFR 490.302 - Vehicle acquisition mandate schedule.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Vehicle acquisition mandate schedule. 490.302 Section 490.302 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Alternative Fuel Provider Vehicle Acquisition Mandate § 490.302 Vehicle acquisition mandate schedule. (a...

10 CFR 490.302 - Vehicle acquisition mandate schedule.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 3 2011-01-01 2011-01-01 false Vehicle acquisition mandate schedule. 490.302 Section 490.302 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Alternative Fuel Provider Vehicle Acquisition Mandate § 490.302 Vehicle acquisition mandate schedule. (a...

10 CFR 490.302 - Vehicle acquisition mandate schedule.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 3 2013-01-01 2013-01-01 false Vehicle acquisition mandate schedule. 490.302 Section 490.302 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Alternative Fuel Provider Vehicle Acquisition Mandate § 490.302 Vehicle acquisition mandate schedule. (a...

10 CFR 490.302 - Vehicle acquisition mandate schedule.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 3 2014-01-01 2014-01-01 false Vehicle acquisition mandate schedule. 490.302 Section 490.302 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Alternative Fuel Provider Vehicle Acquisition Mandate § 490.302 Vehicle acquisition mandate schedule. (a...

Optimizing energy for a 'green' vaccine supply chain.

PubMed

Lloyd, John; McCarney, Steve; Ouhichi, Ramzi; Lydon, Patrick; Zaffran, Michel

2015-02-11

This paper describes an approach piloted in the Kasserine region of Tunisia to increase the energy efficiency of the distribution of vaccines and temperature sensitive drugs. The objectives of an approach, known as the 'net zero energy' (NZE) supply chain were demonstrated within the first year of operation. The existing distribution system was modified to store vaccines and medicines in the same buildings and to transport them according to pre-scheduled and optimized delivery circuits. Electric utility vehicles, dedicated to the integrated delivery of vaccines and medicines, improved the regularity and reliability of the supply chains. Solar energy, linked to the electricity grid at regional and district stores, supplied over 100% of consumption meeting all energy needs for storage, cooling and transportation. Significant benefits to the quality and costs of distribution were demonstrated. Supply trips were scheduled, integrated and reliable, energy consumption was reduced, the recurrent cost of electricity was eliminated and the release of carbon to the atmosphere was reduced. Although the initial capital cost of scaling up implementation of NZE remain high today, commercial forecasts predict cost reduction for solar energy and electric vehicles that may permit a step-wise implementation over the next 7-10 years. Efficiency in the use of energy and in the deployment of transport is already a critical component of distribution logistics in both private and public sectors of industrialized countries. The NZE approach has an intensified rationale in countries where energy costs threaten the maintenance of public health services in areas of low population density. In these countries where the mobility of health personnel and timely arrival of supplies is at risk, NZE has the potential to reduce energy costs and release recurrent budget to other needs of service delivery while also improving the supply chain. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

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

Friese, Ryan; Khemka, Bhavesh; Maciejewski, Anthony A

Rising costs of energy consumption and an ongoing effort for increases in computing performance are leading to a significant need for energy-efficient computing. Before systems such as supercomputers, servers, and datacenters can begin operating in an energy-efficient manner, the energy consumption and performance characteristics of the system must be analyzed. In this paper, we provide an analysis framework that will allow a system administrator to investigate the tradeoffs between system energy consumption and utility earned by a system (as a measure of system performance). We model these trade-offs as a bi-objective resource allocation problem. We use a popular multi-objective geneticmore » algorithm to construct Pareto fronts to illustrate how different resource allocations can cause a system to consume significantly different amounts of energy and earn different amounts of utility. We demonstrate our analysis framework using real data collected from online benchmarks, and further provide a method to create larger data sets that exhibit similar heterogeneity characteristics to real data sets. This analysis framework can provide system administrators with insight to make intelligent scheduling decisions based on the energy and utility needs of their systems.« less

Throughput Maximization for Sensor-Aided Cognitive Radio Networks with Continuous Energy Arrivals

PubMed Central

Nguyen, Thanh-Tung; Koo, Insoo

2015-01-01

We consider a Sensor-Aided Cognitive Radio Network (SACRN) in which sensors capable of harvesting energy are distributed throughout the network to support secondary transmitters for sensing licensed channels in order to improve both energy and spectral efficiency. Harvesting ambient energy is one of the most promising solutions to mitigate energy deficiency, prolong device lifetime, and partly reduce the battery size of devices. So far, many works related to SACRN have considered single secondary users capable of harvesting energy in whole slot as well as short-term throughput. In the paper, we consider two types of energy harvesting sensor nodes (EHSN): Type-I sensor nodes will harvest ambient energy in whole slot duration, whereas type-II sensor nodes will only harvest energy after carrying out spectrum sensing. In the paper, we also investigate long-term throughput in the scheduling window, and formulate the throughput maximization problem by considering energy-neutral operation conditions of type-I and -II sensors and the target detection probability. Through simulations, it is shown that the sensing energy consumption of all sensor nodes can be efficiently managed with the proposed scheme to achieve optimal long-term throughput in the window. PMID:26633393

Non-Evolutionary Algorithms for Scheduling Dependent Tasks in Distributed Heterogeneous Computing Environments

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

Wayne F. Boyer; Gurdeep S. Hura

2005-09-01

The Problem of obtaining an optimal matching and scheduling of interdependent tasks in distributed heterogeneous computing (DHC) environments is well known to be an NP-hard problem. In a DHC system, task execution time is dependent on the machine to which it is assigned and task precedence constraints are represented by a directed acyclic graph. Recent research in evolutionary techniques has shown that genetic algorithms usually obtain more efficient schedules that other known algorithms. We propose a non-evolutionary random scheduling (RS) algorithm for efficient matching and scheduling of inter-dependent tasks in a DHC system. RS is a succession of randomized taskmore » orderings and a heuristic mapping from task order to schedule. Randomized task ordering is effectively a topological sort where the outcome may be any possible task order for which the task precedent constraints are maintained. A detailed comparison to existing evolutionary techniques (GA and PSGA) shows the proposed algorithm is less complex than evolutionary techniques, computes schedules in less time, requires less memory and fewer tuning parameters. Simulation results show that the average schedules produced by RS are approximately as efficient as PSGA schedules for all cases studied and clearly more efficient than PSGA for certain cases. The standard formulation for the scheduling problem addressed in this paper is Rm|prec|Cmax.,« less

Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

NASA Astrophysics Data System (ADS)

Prada, Jose Fernando

Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm posted prices. It is price-based but does not rely on multiple iterations, minimizes information exchange and simplifies the market clearing process. Simulations of the distributed method performed on a six-bus test system showed that, using an appropriate set of prices, it is possible to emulate the results of a conventional centralized solution, without need of providing make-whole payments to generators. Likewise, they showed that the distributed method can accommodate transactions with different products and complex security constraints.

Strategic avionics technology definition studies. Subtask 3-1A: Electrical Actuation (ELA) systems

NASA Technical Reports Server (NTRS)

Lum, Ben T. F.; Pond, Charles; Dermott, William

1993-01-01

This interim report presents the preliminary results of an electrical actuation (ELA) system study (subtask TA3-1A) to support the NASA strategic avionics technology definition studies. The final report of this ELA study is scheduled for September 30, 1993. The topics are presented in viewgraph form and include the following ELA technology demonstration testing; ELA system baseline; power and energy requirements for shuttle effector systems; power efficiency and losses of ELA effector systems; and power and energy requirements for ELA power sources.

Probabilistic QoS Analysis In Wireless Sensor Networks

DTIC Science & Technology

2012-04-01

and A.O. Fapojuwo. TDMA scheduling with optimized energy efficiency and minimum delay in clustered wireless sensor networks . IEEE Trans. on Mobile...Research Computer Science and Engineering, Department of 5-1-2012 Probabilistic QoS Analysis in Wireless Sensor Networks Yunbo Wang University of...Wang, Yunbo, "Probabilistic QoS Analysis in Wireless Sensor Networks " (2012). Computer Science and Engineering: Theses, Dissertations, and Student

Optimal Scheduling for Underwater Communications in Multiple-User Scenarios

DTIC Science & Technology

2015-09-30

term goals of this project is to analyze and propose energy-efficient communication techniques for underwater acoustic sensor networks . These...investigate the possibility that these underwater acoustic networks disrupt the behavior of surrounding species of marine mammals. As a consequence of... underwater VHF acoustics , high data rate/short range acoustic communications and networking , and acoustic sensing in the VHF regime. WORK COMPLETED We

An Energy-Efficient Underground Localization System Based on Heterogeneous Wireless Networks

PubMed Central

Yuan, Yazhou; Chen, Cailian; Guan, Xinping; Yang, Qiuling

2015-01-01

A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners' should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations. In this paper, an underground localization system is designed to enable the adaptation to kinds of harsh tunnel environments, but also to reduce the energy consumption and thus prolong the lifetime of the network. Three key techniques are developed and implemented to improve the system performance, including a step counting algorithm with accelerometers, a power control algorithm and an adaptive packets scheduling scheme. The simulation study and experimental results show the effectiveness of the proposed algorithms and the implementation. PMID:26016918

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

PubMed Central

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms. PMID:26473166

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter.

PubMed

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks

PubMed Central

Sha, Chao; Qiu, Jian-mei; Li, Shu-yan; Qiang, Meng-ye; Wang, Ru-chuan

2016-01-01

To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs), a type of low-latency data gathering method with multi-Sink (LDGM for short) is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathering units and the leader of each region is selected according to its residual energy as well as distance to all of the other nodes. Only the leaders in each region need to communicate with the mobile Sinks which have effectively reduced energy consumption and the end-to-end delay. Moreover, with the help of the sleep scheduling and the sensing radius adjustment strategies, redundancy in network coverage could also be effectively reduced. Simulation results show that LDGM is energy efficient in comparison with MST as well as MWST and its time efficiency on data collection is higher than one Sink based data gathering methods. PMID:27338401

Dynamic VMs placement for energy efficiency by PSO in cloud computing

NASA Astrophysics Data System (ADS)

Dashti, Seyed Ebrahim; Rahmani, Amir Masoud

2016-03-01

Recently, cloud computing is growing fast and helps to realise other high technologies. In this paper, we propose a hieratical architecture to satisfy both providers' and consumers' requirements in these technologies. We design a new service in the PaaS layer for scheduling consumer tasks. In the providers' perspective, incompatibility between specification of physical machine and user requests in cloud leads to problems such as energy-performance trade-off and large power consumption so that profits are decreased. To guarantee Quality of service of users' tasks, and reduce energy efficiency, we proposed to modify Particle Swarm Optimisation to reallocate migrated virtual machines in the overloaded host. We also dynamically consolidate the under-loaded host which provides power saving. Simulation results in CloudSim demonstrated that whatever simulation condition is near to the real environment, our method is able to save as much as 14% more energy and the number of migrations and simulation time significantly reduces compared with the previous works.

TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds.

PubMed

Yuan, Haitao; Bi, Jing; Tan, Wei; Zhou, MengChu; Li, Bo Hu; Li, Jianqiang

2017-11-01

The economy of scale provided by cloud attracts a growing number of organizations and industrial companies to deploy their applications in cloud data centers (CDCs) and to provide services to users around the world. The uncertainty of arriving tasks makes it a big challenge for private CDC to cost-effectively schedule delay bounded tasks without exceeding their delay bounds. Unlike previous studies, this paper takes into account the cost minimization problem for private CDC in hybrid clouds, where the energy price of private CDC and execution price of public clouds both show the temporal diversity. Then, this paper proposes a temporal task scheduling algorithm (TTSA) to effectively dispatch all arriving tasks to private CDC and public clouds. In each iteration of TTSA, the cost minimization problem is modeled as a mixed integer linear program and solved by a hybrid simulated-annealing particle-swarm-optimization. The experimental results demonstrate that compared with the existing methods, the optimal or suboptimal scheduling strategy produced by TTSA can efficiently increase the throughput and reduce the cost of private CDC while meeting the delay bounds of all the tasks.

Real-Time Optimization in Complex Stochastic Environment

DTIC Science & Technology

2015-06-24

simpler ones, thus addressing scalability and the limited resources of networked wireless devices. This, however, comes at the expense of increased...Maximization of Wireless Sensor Networks with Non-ideal Batteries”, IEEE Trans. on Control of Network Systems, Vol. 1, 1, pp. 86-98, 2014. [27...C.G., “Optimal Energy-Efficient Downlink Transmission Scheduling for Real-Time Wireless Networks ”, subm. to IEEE Trans. on Control of Network Systems

Frito-Lay North America/NREL CRADA: Cooperative Research and Development Final Report, CRADA Number CRD-06-176

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

Walker, A.

2013-06-01

Frito Lay North America (FLNA) requires technical assistance for the evaluation and implementation of renewable energy and energy efficiency projects in production facilities and distribution centers across North America. Services provided by NREL do not compete with those available in the private sector, but rather provide FLNA with expertise to create opportunities for the private sector renewable/efficiency industries and to inform FLNA decision making regarding cost-effective projects. Services include: identifying the most cost-effective project locations based on renewable energy resource data, utility data, incentives and other parameters affecting projects; assistance with feasibility studies; procurement specifications; design reviews; and other servicesmore » to support FNLA in improving resource efficiency at facilities. This Cooperative Research and Development Agreement (CRADA) establishes the terms and conditions under which FLNA may access capabilities unique to the laboratory and required by FLNA. Each subsequent task issued under this umbrella agreement would include a scope-of-work, budget, schedule, and provisions for intellectual property specific to that task.« less

Modernised Portuguese schools - From IAQ and thermal comfort towards energy efficiency plans

NASA Astrophysics Data System (ADS)

Pereira, Luisa Maria Dias

A major rehabilitation and refurbishment programme of secondary school buildings has been carried out in the last few years in Portugal, led by the state-owned company Parque Escolar E.P.E. (PE), known as Secondary School Buildings Modernisation Programme. This programme took into consideration renewable energy systems, mostly solar panels for domestic hot water (DHW) production. Nevertheless, with the introduction of HVAC systems in buildings that were previously naturally ventilated, an increase on energy consumption has been verified. During the first occupancy phase of new and refurbished buildings, energy and indoor climate quality (ICQ) audits are important strategies to improve the buildings’ energy use. In new buildings, the most common errors are due to poor operation and management. Schools energy management programmes often result in a list of energy efficiency measures that do not necessarily reflect occupants’ conditions or satisfaction. They are more directed to management control and comparison with benchmarks of energy use/m2 or cost/student to assess energy efficiency. In all cases, monitoring and consumption patterns are mandatory. In this context, this thesis aims at developing energy efficiency plans (EEP) for modernised Portuguese school buildings. The framework of the thesis starts with the development of an international overview of the recent research and development in the field of energy consumption in schools [searching for statistical benchmarks that could contribute to an accurate school building indicator (SBI)]. Then, based on a database provided by Parque Escolar, an energy consumption assessment of Portuguese school buildings is presented, between the pre and post intervention phases. Drawing on this procedure, eight representative modernised secondary schools were selected, geographically and climatically distributed. After, an energy audit and indoor environment quality (IEQ) monitoring is performed in this schools selection. The continuous monitoring period varied between schools, from a minimum of 48h monitoring up to three weeks, during the mid-season [spring - autumn period (excluding summer vacation) in 2013]. Air exchange rates (AER), more specifically infiltration rates, are quantified aiming at determining the current airtightness condition of the refurbished schools. A subjective IEQ assessment is also performed, focusing on occupants’ feedback, providing insight on the potential linkages between energy use and occupants’ satisfaction and comfort. The thesis builds on the current EEP panorama and practice, which is based only on cost/energy control, extending it to address the equilibrium between IEQ evaluation and occupants’ perceived conditions/preferences. This approach is applied in two schools - selected based on the previous study on energy and IEQ conditions of the eight schools. The EEP methodology starts by deepening the knowledge of each school, mostly focusing on crossing the schools occupancy schedule with systems operation [(mainly those controlled by the building management system (BMS)]. An analysis on recently updated legislation is also performed (in particular fresh air flow rates requirements). It is shown that some potential energy savings can be achieved and that IEQ conditions can be improved at very low or even negligible costs. Other considerations, namely addressing the thermal energy production systems of the schools (e.g., boilers scheduling), the lighting systems (e.g., lighting circuits) and non-controlled plug loads, are also mentioned. Based upon all these findings, a handbook of good practice is drafted for secondary school buildings in Portugal. This EEP is accompanied by a list of Energy Efficiency Measures (EEM). It is proposed that this document is headed by a School - Energy Performance Certificate (S-EPC) based on the billed energy consumption. This document suggests the establishment of the figure of the Energy Manager.

Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management.

PubMed

Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

2018-02-25

The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

Propagating Resource Constraints Using Mutual Exclusion Reasoning

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Sanchez, Romeo; Do, Minh B.; Clancy, Daniel (Technical Monitor)

2001-01-01

One of the most recent techniques for propagating resource constraints in Constraint Based scheduling is Energy Constraint. This technique focuses in precedence based scheduling, where precedence relations are taken into account rather than the absolute position of activities. Although, this particular technique proved to be efficient on discrete unary resources, it provides only loose bounds for jobs using discrete multi-capacity resources. In this paper we show how mutual exclusion reasoning can be used to propagate time bounds for activities using discrete resources. We show that our technique based on critical path analysis and mutex reasoning is just as effective on unary resources, and also shows that it is more effective on multi-capacity resources, through both examples and empirical study.

Engineering Sedimentary Geothermal Resources for Large-Scale Dispatchable Renewable Electricity

NASA Astrophysics Data System (ADS)

Bielicki, Jeffrey; Buscheck, Thomas; Chen, Mingjie; Sun, Yunwei; Hao, Yue; Saar, Martin; Randolph, Jimmy

2014-05-01

Mitigating climate change requires substantial penetration of renewable energy and economically viable options for CO2 capture and storage (CCS). We present an approach using CO2 and N2 in sedimentary basin geothermal resources that (1) generates baseload and dispatchable power, (2) efficiently stores large amounts of energy, and (3) enables seasonal storage of solar energy, all which (5) increase the value of CO2 and render CCS commercially viable. Unlike the variability of solar and wind resources, geothermal heat is a constant source of renewable energy. Using CO2 as a supplemental geothermal working fluid, in addition to brine, reduces the parasitic load necessary to recirculate fluids. Adding N2 is beneficial because it is cheaper, will not react with materials and subsurface formations, and enables bulk energy storage. The high coefficients of thermal expansion of CO2 and N2 (a) augment reservoir pressure, (b) generate artesian flow at the production wells, and (c) produce self-convecting thermosiphons that directly convert reservoir heat to mechanical energy for fluid recirculation. Stored pressure drives fluid production and responds faster than conventional brine-based geothermal systems. Our design uses concentric rings of horizontal wells to create a hydraulic divide that stores supplemental fluids and pressure. Production and injection wells are controlled to schedule power delivery and time-shift the parasitic power necessary to separate N2 from air and compress it for injection. The parasitic load can be scheduled during minimum power demand or when there is excess electricity from wind or solar. Net power output can nearly equal gross power output during peak demand, and energy storage is almost 100% efficient because it is achieved by the time-shift. Further, per-well production rates can take advantage of the large productivity of horizontal wells, with greater leveraging of well costs, which often constitute a major portion of capital costs for geothermal power systems.

Quantifying and understanding reproductive allocation schedules in plants.

PubMed

Wenk, Elizabeth Hedi; Falster, Daniel S

2015-12-01

A plant's reproductive allocation (RA) schedule describes the fraction of surplus energy allocated to reproduction as it increases in size. While theorists use RA schedules as the connection between life history and energy allocation, little is known about RA schedules in real vegetation. Here we review what is known about RA schedules for perennial plants using studies either directly quantifying RA or that collected data from which the shape of an RA schedule can be inferred. We also briefly review theoretical models describing factors by which variation in RA may arise. We identified 34 studies from which aspects of an RA schedule could be inferred. Within those, RA schedules varied considerably across species: some species abruptly shift all resources from growth to reproduction; most others gradually shift resources into reproduction, but under a variety of graded schedules. Available data indicate the maximum fraction of energy allocated to production ranges from 0.1 to 1 and that shorter lived species tend to have higher initial RA and increase their RA more quickly than do longer-lived species. Overall, our findings indicate, little data exist about RA schedules in perennial plants. Available data suggest a wide range of schedules across species. Collection of more data on RA schedules would enable a tighter integration between observation and a variety of models predicting optimal energy allocation, plant growth rates, and biogeochemical cycles.

Baseline tests of the power-train electric delivery van

NASA Technical Reports Server (NTRS)

Lumannick, S.; Dustin, M. O.; Bozek, J. M.

1977-01-01

Vehicle maximum speed, range at constant speed, range over stop-and-go driving schedules, maximum acceleration, gradeability, gradeability limit, road energy consumption, road power, indicated energy consumption, braking capability, battery charger efficiency, and battery characteristics were determined for a modified utility van powered by sixteen 6-volt batteries connected in series. A chopper controller actuated by a foot accelerator pedal changes the voltage applied to the 22-kilowatt (30-hp) series-wound drive motor. In addition to the conventional hydraulic braking system, the vehicle has hydraulic regenerative braking. Cycle tests and acceleration tests were conducted with and without hydraulic regeneration.

The comparison of predictive scheduling algorithms for different sizes of job shop scheduling problems

NASA Astrophysics Data System (ADS)

Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.; Krenczyk, D.

2016-08-01

In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how the ability of prediction of reliability characteristics influences over robustness criteria. The most important reliability characteristics are: Mean Time to Failure, Mean Time of Repair. Survey analysis is done for a job shop scheduling problem. The paper answers the question: what method generates robust schedules in the case of a bottleneck failure occurrence before, at the beginning of planned maintenance actions or after planned maintenance actions? Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion. This paper is the continuation of the research conducted in the paper [1], where the survey of predictive and reactive scheduling methods is done only for small size scheduling problems.

Design and implementation of priority and time-window based traffic scheduling and routing-spectrum allocation mechanism in elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan

2016-02-01

With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.

A System-Wide Approach to Physician Efficiency and Utilization Rates for Non-Operating Room Anesthesia Sites.

PubMed

Tsai, Mitchell H; Huynh, Tinh T; Breidenstein, Max W; O'Donnell, Stephen E; Ehrenfeld, Jesse M; Urman, Richard D

2017-07-01

There has been little in the development or application of operating room (OR) management metrics to non-operating room anesthesia (NORA) sites. This is in contrast to the well-developed management framework for the OR management. We hypothesized that by adopting the concept of physician efficiency, we could determine the applicability of this clinical productivity benchmark for physicians providing services for NORA cases at a tertiary care center. We conducted a retrospective data analysis of NORA sites at an academic, rural hospital, including both adult and pediatric patients. Using the time stamps from WiseOR® (Palo Alto, CA), we calculated site utilization and physician efficiency for each day. We defined scheduling efficiency (SE) as the number of staffed anesthesiologists divided by the number of staffed sites and stratified the data into three categories (SE < 1, SE = 1, and SE >1). The mean physician efficiency was 0.293 (95% CI, [0.281, 0.305]), and the mean site utilization was 0.328 (95% CI, [0.314, 0.343]). When days were stratified by scheduling efficiency (SE < 1, =1, or >1), we found differences between physician efficiency and site utilization. On days where scheduling efficiency was less than 1, that is, there are more sites than physicians, mean physician efficiency (95% CI, [0.326, 0.402]) was higher than mean site utilization (95% CI, [0.250, 0.296]). We demonstrate that scheduling efficiency vis-à-vis physician efficiency as an OR management metric diverge when anesthesiologists travel between NORA sites. When the opportunity to scale operational efficiencies is limited, increasing scheduling efficiency by incorporating different NORA sites into a "block" allocation on any given day may be the only suitable tactical alternative.

10 CFR Appendix A to Part 602 - Schedule of Renewal Applications and Reports

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 4 2012-01-01 2012-01-01 false Schedule of Renewal Applications and Reports A Appendix A to Part 602 Energy DEPARTMENT OF ENERGY (CONTINUED) ASSISTANCE REGULATIONS EPIDEMIOLOGY AND OTHER HEALTH STUDIES FINANCIAL ASSISTANCE PROGRAM Pt. 602, App. A Appendix A to Part 602—Schedule of Renewal...

10 CFR Appendix A to Part 602 - Schedule of Renewal Applications and Reports

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 4 2013-01-01 2013-01-01 false Schedule of Renewal Applications and Reports A Appendix A to Part 602 Energy DEPARTMENT OF ENERGY (CONTINUED) ASSISTANCE REGULATIONS EPIDEMIOLOGY AND OTHER HEALTH STUDIES FINANCIAL ASSISTANCE PROGRAM Pt. 602, App. A Appendix A to Part 602—Schedule of Renewal...

10 CFR Appendix A to Part 602 - Schedule of Renewal Applications and Reports

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 4 2014-01-01 2014-01-01 false Schedule of Renewal Applications and Reports A Appendix A to Part 602 Energy DEPARTMENT OF ENERGY (CONTINUED) ASSISTANCE REGULATIONS EPIDEMIOLOGY AND OTHER HEALTH STUDIES FINANCIAL ASSISTANCE PROGRAM Pt. 602, App. A Appendix A to Part 602—Schedule of Renewal...

Autonomous Hybrid Priority Queueing for Scheduling Residential Energy Demands

NASA Astrophysics Data System (ADS)

Kalimullah, I. Q.; Shamroukh, M.; Sahar, N.; Shetty, S.

2017-05-01

The advent of smart grid technologies has opened up opportunities to manage the energy consumption of the users within a residential smart grid system. Demand response management is particularly being employed to reduce the overall load on an electricity network which could in turn reduce outages and electricity costs. The objective of this paper is to develop an intelligible scheduler to optimize the energy available to a micro grid through hybrid queueing algorithm centered around the consumers’ energy demands. This is achieved by shifting certain schedulable load appliances to light load hours. Various factors such as the type of demand, grid load, consumers’ energy usage patterns and preferences are considered while formulating the logical constraints required for the algorithm. The algorithm thus obtained is then implemented in MATLAB workspace to simulate its execution by an Energy Consumption Scheduler (ECS) found within smart meters, which automatically finds the optimal energy consumption schedule tailor made to fit each consumer within the micro grid network.

Real Time Energy Management Control Strategies for Hybrid Powertrains

NASA Astrophysics Data System (ADS)

Zaher, Mohamed Hegazi Mohamed

In order to improve fuel efficiency and reduce emissions of mobile vehicles, various hybrid power-train concepts have been developed over the years. This thesis focuses on embedded control of hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real time energy management strategy for continuous operations. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, or the motion is driven by gravitational force, or load driven. There are three main concepts for regernerative energy storing devices in hybrid vehicles: electric, hydraulic, and flywheel. The real time control challenge is to balance the system power demand from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle, while making optimal use of the energy saving opportunities in a given operational, often repetitive cycle. In the worst case scenario, only engine is used and hybrid system completely disabled. A rule based control is developed and tuned for different work cycles and linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the machine and its position via GPS, and maps them to the gains.

Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments

PubMed Central

Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach. PMID:24319361

Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.

PubMed

Yassa, Sonia; Chelouah, Rachid; Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.

Re-scheduling as a tool for the power management on board a spacecraft

NASA Technical Reports Server (NTRS)

Albasheer, Omar; Momoh, James A.

1995-01-01

The scheduling of events on board a spacecraft is based on forecast energy levels. The real time values of energy may not coincide with the forecast values; consequently, a dynamic revising to the allocation of power is needed. The re-scheduling is also needed for other reasons on board a spacecraft like the addition of new event which must be scheduled, or a failure of an event due to many different contingencies. This need of rescheduling is very important to the survivability of the spacecraft. In this presentation, a re-scheduling tool will be presented as a part of an overall scheme for the power management on board a spacecraft from the allocation of energy point of view. The overall scheme is based on the optimal use of energy available on board a spacecraft using expert systems combined with linear optimization techniques. The system will be able to schedule maximum number of events utilizing most energy available. The outcome is more events scheduled to share the operation cost of that spacecraft. The system will also be able to re-schedule in case of a contingency with minimal time and minimal disturbance of the original schedule. The end product is a fully integrated planning system capable of producing the right decisions in short time with less human error. The overall system will be presented with the re-scheduling algorithm discussed in detail, then the tests and results will be presented for validations.

Improving HVAC operational efficiency in small-and medium-size commercial buildings

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

Kim, Woohyun; Katipamula, Srinivas; Lutes, Robert

Small- and medium-size (<100,000 sf) commercial buildings (SMBs) represent over 95% of the U.S. commercial building stock and consume over 60% of total site energy consumption. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability, no monitoring, or failure management. Therefore, many of these buildings are operated inefficiently and consume excess energy. SMBs typically use packaged rooftop units (RTUs) that are controlled by an individual thermostat. There is increased urgency to improve the operating efficiency of existing commercial building stock in the United States for many reasons, chief among them being to mitigate themore » climate change impacts. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy and cost savings. Another problem associated with RTUs is short cycling, when an RTU goes through ON and OFF cycles too frequently. Excessive cycling can lead to excessive wear and to premature failure of the compressor or its components. Also, short cycling can result in a significantly decreased average efficiency (up to 10%), even if there are no physical failures in the equipment. Ensuring correct use of the zone set points and eliminating frequent cycling of RTUs thereby leading to persistent building operations can significantly increase the operational efficiency of the SMBs. A growing trend is to use low-cost control infrastructure that can enable scalable and cost-effective intelligent building operations. The work reported in this paper describes two algorithms for detecting the zone set point temperature and RTU cycling rate that can be deployed on the low-cost infrastructure. These algorithms only require the zone temperature data for detection. The algorithms have been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithms were successful in detecting the set points and ON/OFF cycles accurately using the peak detection technique. The paper describes the two algorithms, results from testing the algorithms using field data, how the algorithms can be used to improve SMBs efficiency, and presents related conclusions.« less

Steady-state and dynamic evaluation of the electric propulsion system test bed vehicle on a road load simulator

NASA Technical Reports Server (NTRS)

Dustin, M. O.

1983-01-01

The propulsion system of the Lewis Research Center's electric propulsion system test bed vehicle was tested on the road load simulator under the DOE Electric and Hybrid Vehicle Program. This propulsion system, consisting of a series-wound dc motor controlled by an infinitely variable SCR chopper and an 84-V battery pack, is typical of those used in electric vehicles made in 1976. Steady-state tests were conducted over a wide range of differential output torques and vehicle speeds. Efficiencies of all of the components were determined. Effects of temperature and voltage variations on the motor and the effect of voltage changes on the controller were examined. Energy consumption and energy efficiency for the system were determined over the B and C driving schedules of the SAE J227a test procedure.

A Cross-Layer Duty Cycle MAC Protocol Supporting a Pipeline Feature for Wireless Sensor Networks

PubMed Central

Tong, Fei; Xie, Rong; Shu, Lei; Kim, Young-Chon

2011-01-01

Although the conventional duty cycle MAC protocols for Wireless Sensor Networks (WSNs) such as RMAC perform well in terms of saving energy and reducing end-to-end delivery latency, they were designed independently and require an extra routing protocol in the network layer to provide path information for the MAC layer. In this paper, we propose a new cross-layer duty cycle MAC protocol with data forwarding supporting a pipeline feature (P-MAC) for WSNs. P-MAC first divides the whole network into many grades around the sink. Each node identifies its grade according to its logical hop distance to the sink and simultaneously establishes a sleep/wakeup schedule using the grade information. Those nodes in the same grade keep the same schedule, which is staggered with the schedule of the nodes in the adjacent grade. Then a variation of the RTS/CTS handshake mechanism is used to forward data continuously in a pipeline fashion from the higher grade to the lower grade nodes and finally to the sink. No extra routing overhead is needed, thus increasing the network scalability while maintaining the superiority of duty-cycling. The simulation results in OPNET show that P-MAC has better performance than S-MAC and RMAC in terms of packet delivery latency and energy efficiency. PMID:22163895

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

DOE PAGES

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen; ...

2018-01-26

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

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

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

PubMed Central

Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

2018-01-01

The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism. PMID:29495346

18 CFR 35.1 - Application; obligation to file rate schedules, tariffs and certain service agreements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... specifically setting forth all rates and charges for any transmission or sale of electric energy subject to the... same rate schedule or tariff, each public utility transmitting or selling electric energy subject to... schedule, tariff, or service agreement applicable to a transmission or sale of electric energy, other than...

Investigating the Effect of Voltage-Switching on Low-Energy Task Scheduling in Hard Real-Time Systems

DTIC Science & Technology

2005-01-01

We investigate the effect of voltage-switching on task execution times and energy consumption for dual-speed hard real - time systems , and present a...scheduling algorithm and apply it to two real-life task sets. Our results show that energy can be conserved in embedded real - time systems using energy...aware task scheduling. We also show that switching times have a significant effect on the energy consumed in hard real - time systems .

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

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

None

This appendix summarizes building characteristics used to determine heating and cooling loads for each of the five building types in each of the four regions. For the selected five buildings, the following data are attached: new and existing construction characteristics; new and existing construction thermal resistance; floor plan and elevation; people load schedule; lighting load schedule; appliance load schedule; ventilation schedule; and hot water use schedule. For the five building types (single family, apartment buildings, commercial buildings, office buildings, and schools), data are compiled in 10 appendices. These are Building Characteristics; Alternate Energy Sources and Energy Conservation Techniques Description, Costs,more » Fuel Price Scenarios; Life Cycle Cost Model; Simulation Models; Solar Heating/Cooling System; Condensed Weather; Single and Multi-Family Dwelling Characteristics and Energy Conservation Techniques; Mixed Strategies for Energy Conservation and Alternative Energy Utilization in Buildings. An extensive bibliography is given in the final appendix. (MCW)« less

Energy Efficient Approach in RFID Network

NASA Astrophysics Data System (ADS)

Mahdin, Hairulnizam; Abawajy, Jemal; Salwani Yaacob, Siti

2016-11-01

Radio Frequency Identification (RFID) technology is among the key technology of Internet of Things (IOT). It is a sensor device that can monitor, identify, locate and tracking physical objects via its tag. The energy in RFID is commonly being used unwisely because they do repeated readings on the same tag as long it resides in the reader vicinity. Repeated readings are unnecessary because it only generate duplicate data that does not contain new information. The reading process need to be schedule accordingly to minimize the chances of repeated readings to save the energy. This will reduce operational cost and can prolong the tag's battery lifetime that cannot be replaced. In this paper, we propose an approach named SELECT to minimize energy spent during reading processes. Experiments conducted shows that proposed algorithm contribute towards significant energy savings in RFID compared to other approaches.

Extended Policies case

EIA Publications

2016-01-01

The Annual Energy Outlook 2016 (AEO2016) Extended Policies case includes selected policies that go beyond current laws and regulations. Existing tax credits that have scheduled reductions and sunset dates are assumed to remain unchanged through 2040. Other efficiency policies, including corporate average fuel economy standards, appliance standards, and building codes, are expanded beyond current provisions; and the U.S. Environmental Protection Agency (EPA) Clean Power Plan (CPP) regulations that reduce carbon dioxide emissions from electric power generation are tightened after 2030.

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%.

An efficient annealing in Boltzmann machine in Hopfield neural network

NASA Astrophysics Data System (ADS)

Kin, Teoh Yeong; Hasan, Suzanawati Abu; Bulot, Norhisam; Ismail, Mohammad Hafiz

2012-09-01

This paper proposes and implements Boltzmann machine in Hopfield neural network doing logic programming based on the energy minimization system. The temperature scheduling in Boltzmann machine enhancing the performance of doing logic programming in Hopfield neural network. The finest temperature is determined by observing the ratio of global solution and final hamming distance using computer simulations. The study shows that Boltzmann Machine model is more stable and competent in term of representing and solving difficult combinatory problems.

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

Performance of the Sleep-Mode Mechanism of the New IEEE 802.16m Proposal for Correlated Downlink Traffic

NASA Astrophysics Data System (ADS)

de Turck, Koen; de Vuyst, Stijn; Fiems, Dieter; Wittevrongel, Sabine; Bruneel, Herwig

There is a considerable interest nowadays in making wireless telecommunication more energy-efficient. The sleep-mode mechanism in WiMAX (IEEE 802.16e) is one of such energy saving measures. Recently, Samsung proposed some modifications on the sleep-mode mechanism, scheduled to appear in the forthcoming IEEE 802.16m standard, aimed at minimizing the signaling overhead. In this work, we present a performance analysis of this proposal and clarify the differences with the standard mechanism included in IEEE 802.16e. We also propose some special algorithms aimed at reducing the computational complexity of the analysis.

Scheduling lessons learned from the Autonomous Power System

NASA Technical Reports Server (NTRS)

Ringer, Mark J.

1992-01-01

The Autonomous Power System (APS) project at NASA LeRC is designed to demonstrate the applications of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution systems. The project consists of three elements: the Autonomous Power Expert System (APEX) for Fault Diagnosis, Isolation, and Recovery (FDIR); the Autonomous Intelligent Power Scheduler (AIPS) to efficiently assign activities start times and resources; and power hardware (Brassboard) to emulate a space-based power system. The AIPS scheduler was tested within the APS system. This scheduler is able to efficiently assign available power to the requesting activities and share this information with other software agents within the APS system in order to implement the generated schedule. The AIPS scheduler is also able to cooperatively recover from fault situations by rescheduling the affected loads on the Brassboard in conjunction with the APEX FDIR system. AIPS served as a learning tool and an initial scheduling testbed for the integration of FDIR and automated scheduling systems. Many lessons were learned from the AIPS scheduler and are now being integrated into a new scheduler called SCRAP (Scheduler for Continuous Resource Allocation and Planning). This paper will service three purposes: an overview of the AIPS implementation, lessons learned from the AIPS scheduler, and a brief section on how these lessons are being applied to the new SCRAP scheduler.

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

Hooker, J.N.

This report describes an investigation of energy consumption and efficiency of oil pipelines in the US in 1978. It is based on a simulation of the actual movement of oil on a very detailed representation of the pipeline network, and it uses engineering equations to calculate the energy that pipeline pumps must have exerted on the oil to move it in this manner. The efficiencies of pumps and drivers are estimated so as to arrive at the amount of energy consumed at pumping stations. The throughput in each pipeline segment is estimated by distributing each pipeline company's reported oil movementsmore » over its segments in proportions predicted by regression equations that show typical throughput and throughput capacity as functions of pipe diameter. The form of the equations is justified by a generalized cost-engineering study of pipelining, and their parameters are estimated using new techniques developed for the purpose. A simplified model of flow scheduling is chosen on the basis of actual energy use data obtained from a few companies. The study yields energy consumption and intensiveness estimates for crude oil trunk lines, crude oil gathering lines and oil products lines, for the nation as well as by state and by pipe diameter. It characterizes the efficiency of typical pipelines of various diameters operating at capacity. Ancillary results include estimates of oil movements by state and by diameter and approximate pipeline capacity utilization nationwide.« less

An Efficient Downlink Scheduling Strategy Using Normal Graphs for Multiuser MIMO Wireless Systems

NASA Astrophysics Data System (ADS)

Chen, Jung-Chieh; Wu, Cheng-Hsuan; Lee, Yao-Nan; Wen, Chao-Kai

Inspired by the success of the low-density parity-check (LDPC) codes in the field of error-control coding, in this paper we propose transforming the downlink multiuser multiple-input multiple-output scheduling problem into an LDPC-like problem using the normal graph. Based on the normal graph framework, soft information, which indicates the probability that each user will be scheduled to transmit packets at the access point through a specified angle-frequency sub-channel, is exchanged among the local processors to iteratively optimize the multiuser transmission schedule. Computer simulations show that the proposed algorithm can efficiently schedule simultaneous multiuser transmission which then increases the overall channel utilization and reduces the average packet delay.

Increasing operating room efficiency through electronic medical record analysis.

PubMed

Attaallah, A F; Elzamzamy, O M; Phelps, A L; Ranganthan, P; Vallejo, M C

2016-05-01

We used electronic medical record (EMR) analysis to determine errors in operating room (OR) time utilisation. Over a two year period EMR data of 44,503 surgical procedures was analysed for OR duration, on-time, first case, and add-on time performance, within 19 surgical specialties. Maximal OR time utilisation at our institution could have saved over 302,620 min or 5,044 hours of OR efficiency over a two year period. Most specialties (78.95%) had inaccurately scheduled procedure times and therefore used the OR more than their scheduled allotment time. Significant differences occurred between the mean scheduled surgical durations (101.38 ± 87.11 min) and actual durations (108.18 ± 102.27 min; P < 0.001). Significant differences also occurred between the mean scheduled add-on durations (111.4 ± 75.5 min) and the actual add-on scheduled durations (118.6 ± 90.1 minutes; P < 0.001). EMR quality improvement analysis can be used to determine scheduling error and bias, in order to improve efficiency and increase OR time utilisation.

10 CFR 490.201 - Alternative fueled vehicle acquisition mandate schedule.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 3 2012-01-01 2012-01-01 false Alternative fueled vehicle acquisition mandate schedule. 490.201 Section 490.201 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Mandatory State Fleet Program § 490.201 Alternative fueled vehicle acquisition mandate...

10 CFR 490.201 - Alternative fueled vehicle acquisition mandate schedule.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Alternative fueled vehicle acquisition mandate schedule. 490.201 Section 490.201 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Mandatory State Fleet Program § 490.201 Alternative fueled vehicle acquisition mandate...

10 CFR 490.201 - Alternative fueled vehicle acquisition mandate schedule.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 3 2011-01-01 2011-01-01 false Alternative fueled vehicle acquisition mandate schedule. 490.201 Section 490.201 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Mandatory State Fleet Program § 490.201 Alternative fueled vehicle acquisition mandate...

10 CFR 490.201 - Alternative fueled vehicle acquisition mandate schedule.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 3 2013-01-01 2013-01-01 false Alternative fueled vehicle acquisition mandate schedule. 490.201 Section 490.201 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Mandatory State Fleet Program § 490.201 Alternative fueled vehicle acquisition mandate...

10 CFR 490.201 - Alternative fueled vehicle acquisition mandate schedule.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 3 2014-01-01 2014-01-01 false Alternative fueled vehicle acquisition mandate schedule. 490.201 Section 490.201 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Mandatory State Fleet Program § 490.201 Alternative fueled vehicle acquisition mandate...

10 CFR 51.15 - Time schedules.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 2 2010-01-01 2010-01-01 false Time schedules. 51.15 Section 51.15 Energy NUCLEAR... REGULATORY FUNCTIONS National Environmental Policy Act-Regulations Implementing Section 102(2) § 51.15 Time... proposed action or a petitioner for rulemaking shall, establish a time schedule for all or any constituent...

10 CFR 51.15 - Time schedules.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 2 2014-01-01 2014-01-01 false Time schedules. 51.15 Section 51.15 Energy NUCLEAR... REGULATORY FUNCTIONS National Environmental Policy Act-Regulations Implementing Section 102(2) § 51.15 Time... proposed action or a petitioner for rulemaking shall, establish a time schedule for all or any constituent...

10 CFR 51.15 - Time schedules.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 2 2011-01-01 2011-01-01 false Time schedules. 51.15 Section 51.15 Energy NUCLEAR... REGULATORY FUNCTIONS National Environmental Policy Act-Regulations Implementing Section 102(2) § 51.15 Time... proposed action or a petitioner for rulemaking shall, establish a time schedule for all or any constituent...

10 CFR 51.15 - Time schedules.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 2 2013-01-01 2013-01-01 false Time schedules. 51.15 Section 51.15 Energy NUCLEAR... REGULATORY FUNCTIONS National Environmental Policy Act-Regulations Implementing Section 102(2) § 51.15 Time... proposed action or a petitioner for rulemaking shall, establish a time schedule for all or any constituent...

78 FR 18582 - FM Energy Scheduling, LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-27

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. ER13-1107-000] FM Energy Scheduling, LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes Request for Blanket Section 204 Authorization This is a supplemental notice in the above-referenced proceeding, of FM Energy...

10 CFR 205.308 - Filing schedule and annual reports.

Code of Federal Regulations, 2010 CFR

2010-01-01

....308 Energy DEPARTMENT OF ENERGY OIL ADMINISTRATIVE PROCEDURES AND SANCTIONS Electric Power System... to Transmit Electric Energy to A Foreign Country § 205.308 Filing schedule and annual reports. (a) Persons authorized to transmit electric energy from the United States shall promptly file all supplements...

10 CFR 205.308 - Filing schedule and annual reports.

Code of Federal Regulations, 2011 CFR

2011-01-01

....308 Energy DEPARTMENT OF ENERGY OIL ADMINISTRATIVE PROCEDURES AND SANCTIONS Electric Power System... to Transmit Electric Energy to A Foreign Country § 205.308 Filing schedule and annual reports. (a) Persons authorized to transmit electric energy from the United States shall promptly file all supplements...

CARMENES instrument control system and operational scheduler

NASA Astrophysics Data System (ADS)

Garcia-Piquer, Alvaro; Guàrdia, Josep; Colomé, Josep; Ribas, Ignasi; Gesa, Lluis; Morales, Juan Carlos; Pérez-Calpena, Ana; Seifert, Walter; Quirrenbach, Andreas; Amado, Pedro J.; Caballero, José A.; Reiners, Ansgar

2014-07-01

The main goal of the CARMENES instrument is to perform high-accuracy measurements of stellar radial velocities (1m/s) with long-term stability. CARMENES will be installed in 2015 at the 3.5 m telescope in the Calar Alto Observatory (Spain) and it will be equipped with two spectrographs covering from the visible to the near-infrared. It will make use of its near-IR capabilities to observe late-type stars, whose peak of the spectral energy distribution falls in the relevant wavelength interval. The technology needed to develop this instrument represents a challenge at all levels. We present two software packages that play a key role in the control layer for an efficient operation of the instrument: the Instrument Control System (ICS) and the Operational Scheduler. The coordination and management of CARMENES is handled by the ICS, which is responsible for carrying out the operations of the different subsystems providing a tool to operate the instrument in an integrated manner from low to high user interaction level. The ICS interacts with the following subsystems: the near-IR and visible channels, composed by the detectors and exposure meters; the calibration units; the environment sensors; the front-end electronics; the acquisition and guiding module; the interfaces with telescope and dome; and, finally, the software subsystems for operational scheduling of tasks, data processing, and data archiving. We describe the ICS software design, which implements the CARMENES operational design and is planned to be integrated in the instrument by the end of 2014. The CARMENES operational scheduler is the second key element in the control layer described in this contribution. It is the main actor in the translation of the survey strategy into a detailed schedule for the achievement of the optimization goals. The scheduler is based on Artificial Intelligence techniques and computes the survey planning by combining the static constraints that are known a priori (i.e., target visibility, sky background, required time sampling coverage) and the dynamic change of the system conditions (i.e., weather, system conditions). Off-line and on-line strategies are integrated into a single tool for a suitable transfer of the target prioritization made by the science team to the real-time schedule that will be used by the instrument operators. A suitable solution will be expected to increase the efficiency of telescope operations, which will represent an important benefit in terms of scientific return and operational costs. We present the operational scheduling tool designed for CARMENES, which is based on two algorithms combining a global and a local search: Genetic Algorithms and Hill Climbing astronomy-based heuristics, respectively. The algorithm explores a large amount of potential solutions from the vast search space and is able to identify the most efficient ones. A planning solution is considered efficient when it optimizes the objectives defined, which, in our case, are related to the reduction of the time that the telescope is not in use and the maximization of the scientific return, measured in terms of the time coverage of each target in the survey. We present the results obtained using different test cases.

Steering a new course

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

Gordon, D.

1991-01-01

This book offers for the first time a comprehensive survey and analysis of America's transportation system - how it contributes to our environmental problems, and how we could make it safer, more efficient, and less costly. The book includes a history of modern American transportation, an overview of the U.S. transportation sector, and an in-depth discussion of the strategies that hold the most promise for the future. The book provides a wealth of information about innovative transportation options such as: alternative fuels, advances in mass transit, ultra- fuel-efficient vehicles, high-occupancy vehicle facilities, and telecommuting and alternative work schedules. Deborah Gordonmore » is a transportation and energy analyst for the Union of Concerned Scientists.« less

Multi-time scale energy management of wind farms based on comprehensive evaluation technology

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.

9 CFR 307.4 - Schedule of operations.

Code of Federal Regulations, 2010 CFR

2010-01-01

... inspectors shall not, except as provided herein, occur prior to 4 hours after the beginning of scheduled... efficient and effective use of inspection personnel. The work schedule must specify daily clock hours of... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Schedule of operations. 307.4 Section...

Stochastic Routing and Scheduling Policies for Energy Harvesting Communication Networks

NASA Astrophysics Data System (ADS)

Calvo-Fullana, Miguel; Anton-Haro, Carles; Matamoros, Javier; Ribeiro, Alejandro

2018-07-01

In this paper, we study the joint routing-scheduling problem in energy harvesting communication networks. Our policies, which are based on stochastic subgradient methods on the dual domain, act as an energy harvesting variant of the stochastic family of backpresure algorithms. Specifically, we propose two policies: (i) the Stochastic Backpressure with Energy Harvesting (SBP-EH), in which a node's routing-scheduling decisions are determined by the difference between the Lagrange multipliers associated to their queue stability constraints and their neighbors'; and (ii) the Stochastic Soft Backpressure with Energy Harvesting (SSBP-EH), an improved algorithm where the routing-scheduling decision is of a probabilistic nature. For both policies, we show that given sustainable data and energy arrival rates, the stability of the data queues over all network nodes is guaranteed. Numerical results corroborate the stability guarantees and illustrate the minimal gap in performance that our policies offer with respect to classical ones which work with an unlimited energy supply.

W-MAC: A Workload-Aware MAC Protocol for Heterogeneous Convergecast in Wireless Sensor Networks

PubMed Central

Xia, Ming; Dong, Yabo; Lu, Dongming

2011-01-01

The power consumption and latency of existing MAC protocols for wireless sensor networks (WSNs) are high in heterogeneous convergecast, where each sensor node generates different amounts of data in one convergecast operation. To solve this problem, we present W-MAC, a workload-aware MAC protocol for heterogeneous convergecast in WSNs. A subtree-based iterative cascading scheduling mechanism and a workload-aware time slice allocation mechanism are proposed to minimize the power consumption of nodes, while offering a low data latency. In addition, an efficient schedule adjustment mechanism is provided for adapting to data traffic variation and network topology change. Analytical and simulation results show that the proposed protocol provides a significant energy saving and latency reduction in heterogeneous convergecast, and can effectively support data aggregation to further improve the performance. PMID:22163753

Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

USDA-ARS?s Scientific Manuscript database

A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...

Final Report from The University of Texas at Austin for DEGAS: Dynamic Global Address Space programming environments

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

Erez, Mattan; Yelick, Katherine; Sarkar, Vivek

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. Our approach is to provide an efficient and scalable programming model that can be adapted to application needs through the use of dynamic runtime features and domain-specific languages for computational kernels. We address the following technical challenges: Programmability: Rich set of programming constructs based on a Hierarchical Partitioned Global Address Space (HPGAS) model, demonstrated in UPC++. Scalability: Hierarchical locality control, lightweight communication (extended GASNet), and ef- ficient synchronization mechanisms (Phasers). Performance Portability:more » Just-in-time specialization (SEJITS) for generating hardware-specific code and scheduling libraries for domain-specific adaptive runtimes (Habanero). Energy Efficiency: Communication-optimal code generation to optimize energy efficiency by re- ducing data movement. Resilience: Containment Domains for flexible, domain-specific resilience, using state capture mechanisms and lightweight, asynchronous recovery mechanisms. Interoperability: Runtime and language interoperability with MPI and OpenMP to encourage broad adoption.« less

Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale

PubMed Central

Huang, Muhuan; Wu, Di; Yu, Cody Hao; Fang, Zhenman; Interlandi, Matteo; Condie, Tyson; Cong, Jason

2017-01-01

With the end of CPU core scaling due to dark silicon limitations, customized accelerators on FPGAs have gained increased attention in modern datacenters due to their lower power, high performance and energy efficiency. Evidenced by Microsoft’s FPGA deployment in its Bing search engine and Intel’s 16.7 billion acquisition of Altera, integrating FPGAs into datacenters is considered one of the most promising approaches to sustain future datacenter growth. However, it is quite challenging for existing big data computing systems—like Apache Spark and Hadoop—to access the performance and energy benefits of FPGA accelerators. In this paper we design and implement Blaze to provide programming and runtime support for enabling easy and efficient deployments of FPGA accelerators in datacenters. In particular, Blaze abstracts FPGA accelerators as a service (FaaS) and provides a set of clean programming APIs for big data processing applications to easily utilize those accelerators. Our Blaze runtime implements an FaaS framework to efficiently share FPGA accelerators among multiple heterogeneous threads on a single node, and extends Hadoop YARN with accelerator-centric scheduling to efficiently share them among multiple computing tasks in the cluster. Experimental results using four representative big data applications demonstrate that Blaze greatly reduces the programming efforts to access FPGA accelerators in systems like Apache Spark and YARN, and improves the system throughput by 1.7 × to 3× (and energy efficiency by 1.5× to 2.7×) compared to a conventional CPU-only cluster. PMID:28317049

Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale.

PubMed

Huang, Muhuan; Wu, Di; Yu, Cody Hao; Fang, Zhenman; Interlandi, Matteo; Condie, Tyson; Cong, Jason

2016-10-01

With the end of CPU core scaling due to dark silicon limitations, customized accelerators on FPGAs have gained increased attention in modern datacenters due to their lower power, high performance and energy efficiency. Evidenced by Microsoft's FPGA deployment in its Bing search engine and Intel's 16.7 billion acquisition of Altera, integrating FPGAs into datacenters is considered one of the most promising approaches to sustain future datacenter growth. However, it is quite challenging for existing big data computing systems-like Apache Spark and Hadoop-to access the performance and energy benefits of FPGA accelerators. In this paper we design and implement Blaze to provide programming and runtime support for enabling easy and efficient deployments of FPGA accelerators in datacenters. In particular, Blaze abstracts FPGA accelerators as a service (FaaS) and provides a set of clean programming APIs for big data processing applications to easily utilize those accelerators. Our Blaze runtime implements an FaaS framework to efficiently share FPGA accelerators among multiple heterogeneous threads on a single node, and extends Hadoop YARN with accelerator-centric scheduling to efficiently share them among multiple computing tasks in the cluster. Experimental results using four representative big data applications demonstrate that Blaze greatly reduces the programming efforts to access FPGA accelerators in systems like Apache Spark and YARN, and improves the system throughput by 1.7 × to 3× (and energy efficiency by 1.5× to 2.7×) compared to a conventional CPU-only cluster.

Chip-set for quality of service support in passive optical networks

NASA Astrophysics Data System (ADS)

Ringoot, Edwin; Hoebeke, Rudy; Slabbinck, B. Hans; Verhaert, Michel

1998-10-01

In this paper the design of a chip-set for QoS provisioning in ATM-based Passive Optical Networks is discussed. The implementation of a general-purpose switch chip on the Optical Network Unit is presented, with focus on the design of the cell scheduling and buffer management logic. The cell scheduling logic supports `colored' grants, priority jumping and weighted round-robin scheduling. The switch chip offers powerful buffer management capabilities enabling the efficient support of GFR and UBR services. Multicast forwarding is also supported. In addition, the architecture of a MAC controller chip developed for a SuperPON access network is introduced. In particular, the permit scheduling logic and its implementation on the Optical Line Termination will be discussed. The chip-set enables the efficient support of services with different service requirements on the SuperPON. The permit scheduling logic built into the MAC controller chip in combination with the cell scheduling and buffer management capabilities of the switch chip can be used by network operators to offer guaranteed service performance to delay sensitive services, and to efficiently and fairly distribute any spare capacity to delay insensitive services.

Increasing operating room productivity by duration categories and a newsvendor model.

PubMed

Lehtonen, Juha-Matti; Torkki, Paulus; Peltokorpi, Antti; Moilanen, Teemu

2013-01-01

Previous studies approach surgery scheduling mainly from the mathematical modeling perspective which is often hard to apply in a practical environment. The aim of this study is to develop a practical scheduling system that considers the advantages of both surgery categorization and newsvendor model to surgery scheduling. The research was carried out in a Finnish orthopaedic specialist centre that performs only joint replacement surgery. Four surgery categorization scenarios were defined and their productivity analyzed by simulation and newsvendor model. Detailed analyses of surgery durations and the use of more accurate case categories and their combinations in scheduling improved OR productivity 11.3 percent when compared to the base case. Planning to have one OR team to work longer led to remarkable decrease in scheduling inefficiency. In surgical services, productivity and cost-efficiency can be improved by utilizing historical data in case scheduling and by increasing flexibility in personnel management. The study increases the understanding of practical scheduling methods used to improve efficiency in surgical services.

Comparison of OPC job prioritization schemes to generate data for mask manufacturing

NASA Astrophysics Data System (ADS)

Lewis, Travis; Veeraraghavan, Vijay; Jantzen, Kenneth; Kim, Stephen; Park, Minyoung; Russell, Gordon; Simmons, Mark

2015-03-01

Delivering mask ready OPC corrected data to the mask shop on-time is critical for a foundry to meet the cycle time commitment for a new product. With current OPC compute resource sharing technology, different job scheduling algorithms are possible, such as, priority based resource allocation and fair share resource allocation. In order to maximize computer cluster efficiency, minimize the cost of the data processing and deliver data on schedule, the trade-offs of each scheduling algorithm need to be understood. Using actual production jobs, each of the scheduling algorithms will be tested in a production tape-out environment. Each scheduling algorithm will be judged on its ability to deliver data on schedule and the trade-offs associated with each method will be analyzed. It is now possible to introduce advance scheduling algorithms to the OPC data processing environment to meet the goals of on-time delivery of mask ready OPC data while maximizing efficiency and reducing cost.

A Study on the Effect on Scheduling and Management of Surgeries with the Introduction of Excellent Medical Information.

PubMed

Mei, Tsai Ching

2016-01-01

The services of OR play an important role in the medical business for department of surgery. The most important issue for OR is about the scheduling and management of surgeries. Good surgery schedule could elevate the utilization efficiency of OR. Therefore, the introduction of excellent medical information can both dramatically elevate the work efficiency of health care employees and reduce workload to reach win-win benefits in both management and performance.

A Hybrid Memetic Framework for Coverage Optimization in Wireless Sensor Networks.

PubMed

Chen, Chia-Pang; Mukhopadhyay, Subhas Chandra; Chuang, Cheng-Long; Lin, Tzu-Shiang; Liao, Min-Sheng; Wang, Yung-Chung; Jiang, Joe-Air

2015-10-01

One of the critical concerns in wireless sensor networks (WSNs) is the continuous maintenance of sensing coverage. Many particular applications, such as battlefield intrusion detection and object tracking, require a full-coverage at any time, which is typically resolved by adding redundant sensor nodes. With abundant energy, previous studies suggested that the network lifetime can be maximized while maintaining full coverage through organizing sensor nodes into a maximum number of disjoint sets and alternately turning them on. Since the power of sensor nodes is unevenly consumed over time, and early failure of sensor nodes leads to coverage loss, WSNs require dynamic coverage maintenance. Thus, the task of permanently sustaining full coverage is particularly formulated as a hybrid of disjoint set covers and dynamic-coverage-maintenance problems, and both have been proven to be nondeterministic polynomial-complete. In this paper, a hybrid memetic framework for coverage optimization (Hy-MFCO) is presented to cope with the hybrid problem using two major components: 1) a memetic algorithm (MA)-based scheduling strategy and 2) a heuristic recursive algorithm (HRA). First, the MA-based scheduling strategy adopts a dynamic chromosome structure to create disjoint sets, and then the HRA is utilized to compensate the loss of coverage by awaking some of the hibernated nodes in local regions when a disjoint set fails to maintain full coverage. The results obtained from real-world experiments using a WSN test-bed and computer simulations indicate that the proposed Hy-MFCO is able to maximize sensing coverage while achieving energy efficiency at the same time. Moreover, the results also show that the Hy-MFCO significantly outperforms the existing methods with respect to coverage preservation and energy efficiency.

Scheduling job shop - A case study

NASA Astrophysics Data System (ADS)

Abas, M.; Abbas, A.; Khan, W. A.

2016-08-01

The scheduling in job shop is important for efficient utilization of machines in the manufacturing industry. There are number of algorithms available for scheduling of jobs which depend on machines tools, indirect consumables and jobs which are to be processed. In this paper a case study is presented for scheduling of jobs when parts are treated on available machines. Through time and motion study setup time and operation time are measured as total processing time for variety of products having different manufacturing processes. Based on due dates different level of priority are assigned to the jobs and the jobs are scheduled on the basis of priority. In view of the measured processing time, the times for processing of some new jobs are estimated and for efficient utilization of the machines available an algorithm is proposed and validated.

Path planning and energy management of solar-powered unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Kaplan, Adam

Many of the applications pertinent to unmanned vehicles, such as environmental research and analysis, communications, and information-surveillance and reconnaissance, benefit from prolonged vehicle operation time. Conventional efforts to increase the operational time of electric-powered unmanned vehicles have traditionally focused on the design of energy-efficient components and the identification of energy efficient search patterns, while little attention has been paid to the vehicle's mission-level path plan and power management. This thesis explores the formulation and generation of integrated motion-plans and power-schedules for solar-panel equipped mobile robots operating under strict energy constraints, which cannot be effectively addressed through conventional motion planning algorithms. Transit problems are considered to design time-optimal paths using both Balkcom-Mason and Pseudo-Dubins curves. Additionally, a more complicated problem to generate mission plans for vehicles which must persistently travel between certain locations, similar to the traveling salesperson problem (TSP), is presented. A comparison between one of the common motion-planning algorithms and experimental results of the prescribed algorithms, made possible by use of a test environment and mobile robot designed and developed specifically for this research, are presented and discussed.

Water Management Planning: A Case Study at Blue Grass Army Depot

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

Solana, Amy E.; Mcmordie, Katherine

2006-04-03

Executive Order 13123, Greening the Government Through Efficient Energy Management, mandates an aggressive policy for reducing potable water consumption at federal facilities. Implementation guid¬ance from the U.S. Department of Energy (DOE) set a requirement for each federal agency to “reduce potable water usage by implementing life cycle, cost-effective water efficiency programs that include a water management plan, and not less than four Federal Energy Management Program (FEMP) Best Manage¬ment Practices (BMPs).” The objective of this plan is to gain full compliance with Executive Order 13123 and associated DOE implementation guidance on behalf of Blue Grass Army Depot (BGAD), Richmond, Kentucky.more » In accordance with this plan, BGAD must: • Incorporate the plan as a component of the Installation energy conservation plan • Investigate the water savings potential and life-cycle cost effectiveness of the Operations and Maintenance (O&M) and retrofit/replacement options associated with the ten FEMP BMPs • Put into practice all applicable O&M options • Identify retrofit/replacement options appropriate for implementation (based upon calculation of the simple payback periods) • Establish a schedule for implementation of applicable and cost-effective retrofit/replacement options.« less

Applying dynamic priority scheduling scheme to static systems of pinwheel task model in power-aware scheduling.

PubMed

Seol, Ye-In; Kim, Young-Kuk

2014-01-01

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10-80% over the existing algorithms.

Applying Dynamic Priority Scheduling Scheme to Static Systems of Pinwheel Task Model in Power-Aware Scheduling

PubMed Central

2014-01-01

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10–80% over the existing algorithms. PMID:25121126

Assessing Potential Energy Savings in Household Travel: Methodological and Empirical Considerations of Vehicle Capability Constraints and Multi-day Activity Patterns

NASA Astrophysics Data System (ADS)

Bolon, Kevin M.

The lack of multi-day data for household travel and vehicle capability requirements is an impediment to evaluations of energy savings strategies, since (1) travel requirements vary from day-to-day, and (2) energy-saving transportation options often have reduced capability. This work demonstrates a survey methodology and modeling system for evaluating the energy-savings potential of household travel, considering multi-day travel requirements and capability constraints imposed by the available transportation resources. A stochastic scheduling model is introduced---the multi-day Household Activity Schedule Estimator (mPHASE)---which generates synthetic daily schedules based on "fuzzy" descriptions of activity characteristics using a finite-element representation of activity flexibility, coordination among household members, and scheduling conflict resolution. Results of a thirty-household pilot study are presented in which responses to an interactive computer assisted personal interview were used as inputs to the mPHASE model in order to illustrate the feasibility of generating complex, realistic multi-day household schedules. Study vehicles were equipped with digital cameras and GPS data acquisition equipment to validate the model results. The synthetically generated schedules captured an average of 60 percent of household travel distance, and exhibited many of the characteristics of complex household travel, including day-to-day travel variation, and schedule coordination among household members. Future advances in the methodology may improve the model results, such as encouraging more detailed and accurate responses by providing a selection of generated schedules during the interview. Finally, the Constraints-based Transportation Resource Assignment Model (CTRAM) is introduced. Using an enumerative optimization approach, CTRAM determines the energy-minimizing vehicle-to-trip assignment decisions, considering trip schedules, occupancy, and vehicle capability. Designed to accept either actual or synthetic schedules, results of an application of the optimization model to the 2001 and 2009 National Household Travel Survey data show that U.S. households can reduce energy use by 10 percent, on average, by modifying the assignment of existing vehicles to trips. Households in 2009 show a higher tendency to assign vehicles optimally than in 2001, and multi-vehicle households with diverse fleets have greater savings potential, indicating that fleet modification strategies may be effective, particularly under higher energy price conditions.

Performance Evaluation of Energy-Autonomous Sensors Using Power-Harvesting Beacons for Environmental Monitoring in Internet of Things (IoT).

PubMed

Moiş, George Dan; Sanislav, Teodora; Folea, Silviu Corneliu; Zeadally, Sherali

2018-05-25

Environmental conditions and air quality monitoring have become crucial today due to the undeniable changes of the climate and accelerated urbanization. To efficiently monitor environmental parameters such as temperature, humidity, and the levels of pollutants, such as fine particulate matter (PM2.5) and volatile organic compounds (VOCs) in the air, and to collect data covering vast geographical areas, the development of cheap energy-autonomous sensors for large scale deployment and fine-grained data acquisition is required. Rapid advances in electronics and communication technologies along with the emergence of paradigms such as Cyber-Physical Systems (CPSs) and the Internet of Things (IoT) have led to the development of low-cost sensor devices that can operate unattended for long periods of time and communicate using wired or wireless connections through the Internet. We investigate the energy efficiency of an environmental monitoring system based on Bluetooth Low Energy (BLE) beacons that operate in the IoT environment. The beacons developed measure the temperature, the relative humidity, the light intensity, and the CO₂ and VOC levels in the air. Based on our analysis we have developed efficient sleep scheduling algorithms that allow the sensor nodes developed to operate autonomously without requiring the replacement of the power supply. The experimental results show that low-power sensors communicating using BLE technology can operate autonomously (from the energy perspective) in applications that monitor the environment or the air quality in indoor or outdoor settings.

Thermostat Interface and Usability: A Survey

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

Meier, Alan; Peffer, Therese; Pritoni, Marco

2010-09-04

This report investigates the history of thermostats to better understand the context and legacy regarding the development of this important tool, as well as thermostats' relationships to heating, cooling, and other environmental controls. We analyze the architecture, interfaces, and modes of interaction used by different types of thermostats. For over sixty years, home thermostats have translated occupants' temperature preferences into heating and cooling system operations. In this position of an intermediary, the millions of residential thermostats control almost half of household energy use, which corresponds to about 10percent of the nation's total energy use. Thermostats are currently undergoing rapid developmentmore » in response to emerging technologies, new consumer and utility demands, and declining manufacturing costs. Energy-efficient homes require more careful balancing of comfort, energy consumption, and health. At the same time, new capabilities will be added to thermostats, including scheduling, control of humidity and ventilation, responsiveness to dynamic electricity prices, and the ability to join communication networks inside homes. Recent studies have found that as many as 50percent of residential programmable thermostats are in permanent"hold" status. Other evaluations found that homes with programmable thermostats consumed more energy than those relying on manual thermostats. Occupants find thermostats cryptic and baffling to operate because manufacturers often rely on obscure, and sometimes even contradictory, terms, symbols, procedures, and icons. It appears that many people are unable to fully exploit even the basic features in today's programmable thermostats, such as setting heating and cooling schedules. It is important that people can easily, reliably, and confidently operate thermostats in their homes so as to remain comfortable while minimizing energy use.« less

A heuristic approach to incremental and reactive scheduling

NASA Technical Reports Server (NTRS)

Odubiyi, Jide B.; Zoch, David R.

1989-01-01

An heuristic approach to incremental and reactive scheduling is described. Incremental scheduling is the process of modifying an existing schedule if the initial schedule does not meet its stated initial goals. Reactive scheduling occurs in near real-time in response to changes in available resources or the occurrence of targets of opportunity. Only minor changes are made during both incremental and reactive scheduling because a goal of re-scheduling procedures is to minimally impact the schedule. The described heuristic search techniques, which are employed by the Request Oriented Scheduling Engine (ROSE), a prototype generic scheduler, efficiently approximate the cost of reaching a goal from a given state and effective mechanisms for controlling search.

Hidden Efficiencies: Making Completion of the Pediatric Vaccine Schedule More Efficient for Physicians

PubMed Central

Ciarametaro, Mike; Bradshaw, Steven E.; Guiglotto, Jillian; Hahn, Beth; Meier, Genevieve

2015-01-01

Abstract The objective of this work is to demonstrate the potential time and labor savings that may result from increased use of combination vaccinations. The study (GSK study identifier: HO-12-4735) was a model developed to evaluate the efficiency of the pediatric vaccine schedule, using time and motion studies. The model considered vaccination time and the associated labor costs, but vaccination acquisition costs were not considered. We also did not consider any efficacy or safety differences between formulations. The model inputs were supported by a targeted literature review. The reference year for the model was 2012. The most efficient vaccination program using currently available vaccines was predicted to reduce costs through a combination of fewer injections (62%) and less time per vaccination (38%). The most versus the least efficient vaccine program was predicted to result in a 47% reduction in vaccination time and a 42% reduction in labor and supply costs. The estimated administration cost saving with the most versus the least efficient program was estimated to be nearly US $45 million. If hypothetical 6- or 7-valent vaccines are developed using the already most efficient schedule by adding additional antigens (pneumococcal conjugate vaccine and Haemophilus influenzae type b) to the most efficient 5-valent vaccine, the savings are predicted to be even greater. Combination vaccinations reduce the time burden of the childhood immunization schedule and could create the potential to improve vaccination uptake and compliance as a result of fewer required injections. PMID:25634165

Guide to Operating and Maintaining EnergySmart Schools

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

None

Through a commitment to high performance, school districts are discovering that smart energy choices can create lasting benefits for students, communities, and the environment. For example, an energy efficient school district with 4,000 students can save as much as $160,000 a year in energy costs. Over 10 years, those savings can reach $1.6 million, translating into the ability to hire more teachers, purchase more textbooks and computers, or invest in additional high performance facilities. Beyond these bottomline benefits, schools can better foster student health, decrease absenteeism, and serve as centers of community life. The U.S. Department of Energy's EnergySmart Schoolsmore » Program promotes a 30 percent improvement in existing school energy use. It also encourages the building of new schools that exceed code (ASHRAE 90.11999) by 50 percent or more. The program provides resources like this Guide to Operating and Maintaining EnergySmart Schools to assist school decisionmakers in planning, financing, operating, and maintaining energy efficient, high performance schools. It also offers education and training for building industry professionals. Operations and maintenance refer to all scheduled and unscheduled actions for preventing equipment failure or decline with the goal of increasing efficiency, reliability, and safety. A preventative maintenance program is the organized and planned performance of maintenance activities in order to prevent system or production problems or failures from occurring. In contrast, deferred maintenance or reactive maintenance (also called diagnostic or corrective maintenance) is conducted to address an existing problem. This guide is a primary resource for developing and implementing a districtor schoolwide operations and maintenance (O&M) program that focuses on energy efficiency. The EnergySmart Schools Solutions companion CD contains additional supporting information for design, renovation, and retrofit projects. The objective of this guide is to provide organizational and technical information for integrating energy and high performance facility management into existing O&M practices. The guide allows users to adapt and implement suggested O&M strategies to address specific energy efficiency goals. It recognizes and expands on existing tools and resources that are widely used throughout the high performance school industry. External resources are referenced throughout the guide and are also listed within the EnergySmart Schools O&M Resource List (Appendix J). While this guide emphasizes the impact of the energy efficiency component of O&M, it encourages taking a holistic approach to maintaining a high-performance school. This includes considering various environmental factors where energy plays an indirect or direct role. For example, indoor air quality, site selection, building orientation, and water efficiency should be considered. Resources to support these overlapping aspects will be cited throughout the guide.« less

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

18 CFR 5.19 - Tendering notice and schedule.

Code of Federal Regulations, 2013 CFR

2013-04-01

... application for a license developed pursuant to this part, the Director of the Office of Energy Projects will... schedule. 5.19 Section 5.19 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS § 5.19...

18 CFR 5.19 - Tendering notice and schedule.

Code of Federal Regulations, 2014 CFR

2014-04-01

... application for a license developed pursuant to this part, the Director of the Office of Energy Projects will... schedule. 5.19 Section 5.19 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS § 5.19...

18 CFR 5.19 - Tendering notice and schedule.

Code of Federal Regulations, 2012 CFR

2012-04-01

... application for a license developed pursuant to this part, the Director of the Office of Energy Projects will... schedule. 5.19 Section 5.19 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS § 5.19...

78 FR 62627 - Sam Rayburn Dam Rate

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-22

..., Wholesale Rates for Hydro Power and Energy Sold to Sam Rayburn Dam Electric Cooperative, Inc. (Contract No... Schedule SRD-08, Wholesale Rates for Hydro Power and Energy Sold to Sam Rayburn Dam Electric Cooperative... ADMINISTRATION RATE SCHEDULE SRD-13 \\1\\ WHOLESALE RATES FOR HYDRO POWER AND ENERGY SOLD TO SAM RAYBURN DAM...

Computer-aided resource planning and scheduling for radiological services

NASA Astrophysics Data System (ADS)

Garcia, Hong-Mei C.; Yun, David Y.; Ge, Yiqun; Khan, Javed I.

1996-05-01

There exists tremendous opportunity in hospital-wide resource optimization based on system integration. This paper defines the resource planning and scheduling requirements integral to PACS, RIS and HIS integration. An multi-site case study is conducted to define the requirements. A well-tested planning and scheduling methodology, called Constrained Resource Planning model, has been applied to the chosen problem of radiological service optimization. This investigation focuses on resource optimization issues for minimizing the turnaround time to increase clinical efficiency and customer satisfaction, particularly in cases where the scheduling of multiple exams are required for a patient. How best to combine the information system efficiency and human intelligence in improving radiological services is described. Finally, an architecture for interfacing a computer-aided resource planning and scheduling tool with the existing PACS, HIS and RIS implementation is presented.

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Strategies GeoCape Intelligent Observation Studies @ GSFC

NASA Technical Reports Server (NTRS)

Cappelaere, Pat; Frye, Stu; Moe, Karen; Mandl, Dan; LeMoigne, Jacqueline; Flatley, Tom; Geist, Alessandro

2015-01-01

This presentation provides information a summary of the tradeoff studies conducted for GeoCape by the GSFC team in terms of how to optimize GeoCape observation efficiency. Tradeoffs include total ground scheduling with simple priorities, ground scheduling with cloud forecast, ground scheduling with sub-area forecast, onboard scheduling with onboard cloud detection and smart onboard scheduling and onboard image processing. The tradeoffs considered optimzing cost, downlink bandwidth and total number of images acquired.

Charge scheduling of an energy storage system under time-of-use pricing and a demand charge.

PubMed

Yoon, Yourim; Kim, Yong-Hyuk

2014-01-01

A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power.

Charge Scheduling of an Energy Storage System under Time-of-Use Pricing and a Demand Charge

PubMed Central

Yoon, Yourim

2014-01-01

A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power. PMID:25197720

An inlet analysis for the NASA hypersonic research engine aerothermodynamic integration model

NASA Technical Reports Server (NTRS)

Andrews, E. H., Jr.; Russell, J. W.; Mackley, E. A.; Simmonds, A. L.

1974-01-01

A theoretical analysis for the inlet of the NASA Hypersonic Research Engine (HRE) Aerothermodynamic Integration Model (AIM) has been undertaken by use of a method-of-characteristics computer program. The purpose of the analysis was to obtain pretest information on the full-scale HRE inlet in support of the experimental AIM program (completed May 1974). Mass-flow-ratio and additive-drag-coefficient schedules were obtained that well defined the range effected in the AIM tests. Mass-weighted average inlet total-pressure recovery, kinetic energy efficiency, and throat Mach numbers were obtained.

Integration of Openstack cloud resources in BES III computing cluster

NASA Astrophysics Data System (ADS)

Li, Haibo; Cheng, Yaodong; Huang, Qiulan; Cheng, Zhenjing; Shi, Jingyan

2017-10-01

Cloud computing provides a new technical means for data processing of high energy physics experiment. However, the resource of each queue is fixed and the usage of the resource is static in traditional job management system. In order to make it simple and transparent for physicist to use, we developed a virtual cluster system (vpmanager) to integrate IHEPCloud and different batch systems such as Torque and HTCondor. Vpmanager provides dynamic virtual machines scheduling according to the job queue. The BES III use case results show that resource efficiency is greatly improved.

Operating and maintaining your heat recovery ventilator (HRV) -- Revised edition. Home heating and cooling series, Number 8

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

NONE

Heat recovery ventilators (HRVs) differ from other mechanical ventilation devices by their ability to exchange heat between supply and exhaust air streams, which reduces the cost of heating or cooling fresh air. This booklet discusses the need for mechanical ventilation in conventional and energy-efficient homes, an explains the components of a HRV system, how to operate and maintain the system, and how to solve operating problems. A maintenance chart and schedule and a HRV troubleshooting guide are included.

Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming.

PubMed

Xie, Shengli; Zhong, Weifeng; Xie, Kan; Yu, Rong; Zhang, Yan

2016-08-01

Research on the smart grid is being given enormous supports worldwide due to its great significance in solving environmental and energy crises. Electric vehicles (EVs), which are powered by clean energy, are adopted increasingly year by year. It is predictable that the huge charge load caused by high EV penetration will have a considerable impact on the reliability of the smart grid. Therefore, fair energy scheduling for EV charge and discharge is proposed in this paper. By using the vehicle-to-grid technology, the scheduler controls the electricity loads of EVs considering fairness in the residential distribution network. We propose contribution-based fairness, in which EVs with high contributions have high priorities to obtain charge energy. The contribution value is defined by both the charge/discharge energy and the timing of the action. EVs can achieve higher contribution values when discharging during the load peak hours. However, charging during this time will decrease the contribution values seriously. We formulate the fair energy scheduling problem as an infinite-horizon Markov decision process. The methodology of adaptive dynamic programming is employed to maximize the long-term fairness by processing online network training. The numerical results illustrate that the proposed EV energy scheduling is able to mitigate and flatten the peak load in the distribution network. Furthermore, contribution-based fairness achieves a fast recovery of EV batteries that have deeply discharged and guarantee fairness in the full charge time of all EVs.

Human-Machine Collaborative Optimization via Apprenticeship Scheduling

DTIC Science & Technology

2016-09-09

prenticeship Scheduling (COVAS), which performs ma- chine learning using human expert demonstration, in conjunction with optimization, to automatically and ef...ficiently produce optimal solutions to challenging real- world scheduling problems. COVAS first learns a policy from human scheduling demonstration via...apprentice- ship learning , then uses this initial solution to provide a tight bound on the value of the optimal solution, thereby substantially

Irrigation scheduling and controlling crop water use efficiency with Infrared Thermometry

USDA-ARS?s Scientific Manuscript database

Scientific methods for irrigation scheduling include weather, soil and plant-based techniques. Infrared thermometers can be used a non-invasive practice to monitor canopy temperature and better manage irrigation scheduling. This presentation will discuss the theoretical basis for monitoring crop can...

Car painting process scheduling with harmony search algorithm

NASA Astrophysics Data System (ADS)

Syahputra, M. F.; Maiyasya, A.; Purnamawati, S.; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.

2018-02-01

Automotive painting program in the process of painting the car body by using robot power, making efficiency in the production system. Production system will be more efficient if pay attention to scheduling of car order which will be done by considering painting body shape of car. Flow shop scheduling is a scheduling model in which the job-job to be processed entirely flows in the same product direction / path. Scheduling problems often arise if there are n jobs to be processed on the machine, which must be specified which must be done first and how to allocate jobs on the machine to obtain a scheduled production process. Harmony Search Algorithm is a metaheuristic optimization algorithm based on music. The algorithm is inspired by observations that lead to music in search of perfect harmony. This musical harmony is in line to find optimal in the optimization process. Based on the tests that have been done, obtained the optimal car sequence with minimum makespan value.

Feelings of energy, exercise-related self-efficacy, and voluntary exercise participation.

PubMed

Yoon, Seok; Buckworth, Janet; Focht, Brian; Ko, Bomna

2013-12-01

This study used a path analysis approach to examine the relationship between feelings of energy, exercise-related self-efficacy beliefs, and exercise participation. A cross-sectional mailing survey design was used to measure feelings of physical and mental energy, task and scheduling self-efficacy beliefs, and voluntary moderate and vigorous exercise participation in 368 healthy, full-time undergraduate students (mean age = 21.43 ± 2.32 years). The path analysis revealed that the hypothesized path model had a strong fit to the study data. The path model showed that feelings of physical energy had significant direct effects on task and scheduling self-efficacy beliefs as well as exercise behaviors. In addition, scheduling self-efficacy had direct effects on moderate and vigorous exercise participation. However, there was no significant direct relationship between task self-efficacy and exercise participation. The path model also revealed that scheduling self-efficacy partially mediated the relationship between feelings of physical energy and exercise participation.

Collaborative Distributed Scheduling Approaches for Wireless Sensor Network

PubMed Central

Niu, Jianjun; Deng, Zhidong

2009-01-01

Energy constraints restrict the lifetime of wireless sensor networks (WSNs) with battery-powered nodes, which poses great challenges for their large scale application. In this paper, we propose a family of collaborative distributed scheduling approaches (CDSAs) based on the Markov process to reduce the energy consumption of a WSN. The family of CDSAs comprises of two approaches: a one-step collaborative distributed approach and a two-step collaborative distributed approach. The approaches enable nodes to learn the behavior information of its environment collaboratively and integrate sleep scheduling with transmission scheduling to reduce the energy consumption. We analyze the adaptability and practicality features of the CDSAs. The simulation results show that the two proposed approaches can effectively reduce nodes' energy consumption. Some other characteristics of the CDSAs like buffer occupation and packet delay are also analyzed in this paper. We evaluate CDSAs extensively on a 15-node WSN testbed. The test results show that the CDSAs conserve the energy effectively and are feasible for real WSNs. PMID:22408491

Agricultural residue availability in the United States.

PubMed

Haq, Zia; Easterly, James L

2006-01-01

The National Energy Modeling System (NEMS) is used by the Energy Information Administration (EIA) to forecast US energy production, consumption, and price trends for a 25-yr-time horizon. Biomass is one of the technologies within NEMS, which plays a key role in several scenarios. An endogenously determined biomass supply schedule is used to derive the price-quantity relationship of biomass. There are four components to the NEMS biomass supply schedule including: agricultural residues, energy crops, forestry residues, and urban wood waste/mill residues. The EIA's Annual Energy Outlook 2005 includes updated estimates of the agricultural residue portion of the biomass supply schedule. The changes from previous agricultural residue supply estimates include: revised assumptions concerning corn stover and wheat straw residue availabilities, inclusion of non-corn and non-wheat agricultural residues (such as barley, rice straw, and sugarcane bagasse), and the implementation of assumptions concerning increases in no-till farming. This article will discuss the impact of these changes on the supply schedule.

Optimizing Schedules of Retrieval Practice for Durable and Efficient Learning: How Much Is Enough?

ERIC Educational Resources Information Center

Rawson, Katherine A.; Dunlosky, John

2011-01-01

The literature on testing effects is vast but supports surprisingly few prescriptive conclusions for how to schedule practice to achieve both durable and efficient learning. Key limitations are that few studies have examined the effects of initial learning criterion or the effects of relearning, and no prior research has examined the combined…

The GBT Dynamic Scheduling System: A New Scheduling Paradigm

NASA Astrophysics Data System (ADS)

O'Neil, K.; Balser, D.; Bignell, C.; Clark, M.; Condon, J.; McCarty, M.; Marganian, P.; Shelton, A.; Braatz, J.; Harnett, J.; Maddalena, R.; Mello, M.; Sessoms, E.

2009-09-01

The Robert C. Byrd Green Bank Telescope (GBT) is implementing a new Dynamic Scheduling System (DSS) designed to maximize the observing efficiency of the telescope while ensuring that none of the flexibility and ease of use of the GBT is harmed and that the data quality of observations is not adversely affected. To accomplish this, the GBT DSS is implementing a dynamic scheduling system which schedules observers, rather than running scripts. The DSS works by breaking each project into one or more sessions which have associated observing criteria such as RA, Dec, and frequency. Potential observers may also enter dates when members of their team will not be available for either on-site or remote observing. The scheduling algorithm uses those data, along with the predicted weather, to determine the most efficient schedule for the GBT. The DSS provides all observers at least 24 hours notice of their upcoming observing. In the uncommon (< 20%) case where the actual weather does not match the predictions, a backup project, chosen from the database, is run instead. Here we give an overview of the GBT DSS project, including the ranking and scheduling algorithms for the sessions, the scheduling probabilities generation, the web framework for the system, and an overview of the results from the beta testing which were held from June - September, 2008.

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

Holt, Jeffrey W.

The Tribe is working to reduce energy consumption and expense in Tribally-owned governmental buildings and low income housing sites. In 2009, the Tribe applied to the U. S. Department of Energy for funding to conduct energy audits of Tribally-owned governmental buildings. Findings from the energy audits would define the extent and types of energy efficiency improvements needed, establish a basis for energy priorities, strategies and action plans, and provide a benchmark for measuring improvements from energy efficiency implementations. In 2010, the DOE awarded a grant in the amount of $95,238 to the Tribe to fund the energy audits of ninemore » governmental buildings and to pay for travel expenses associated with attendance and participation at the DOE annual program reviews. In 2011, the Tribe applied for and was awarded a DOE grant in the amount of $75,509 to conduct energy audits of the remaining 30 Tribally-owned governmental buildings. Repeating mobilization steps performed during the first DOE energy audits grant, the Tribe initiated the second round of governmental building energy audits by completing energy auditor procurement. The selected energy auditor successfully passed DOE debarment and Sault Tribe background clearances. The energy audits contract was awarded to U. P. Engineers and Architects, Inc. of Sault Ste. Marie, Michigan. The Tribe continued mobilizing for the energy audits by providing the energy auditor with one year of electric, gas and water utility invoice copies per building, as well as supplemental building information, such as operating hours. The Tribe also contacted building occupants to coordinate scheduling for the on-site energy audit inspections and arranged for facilities management personnel to guide the energy auditor through the buildings and answer questions regarding building systems.« less

10 CFR 474.4 - Test procedures.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 3 2011-01-01 2011-01-01 false Test procedures. 474.4 Section 474.4 Energy DEPARTMENT OF...; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION § 474.4 Test procedures. (a) The electric vehicle energy... Schedule and Urban Dynamometer Driving Schedule test cycles at 40 CFR parts 86 and 600. (b) The “Special...

A new distributed systems scheduling algorithm: a swarm intelligence approach

NASA Astrophysics Data System (ADS)

Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi

2011-12-01

The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.

Wave scheduling - Decentralized scheduling of task forces in multicomputers

NASA Technical Reports Server (NTRS)

Van Tilborg, A. M.; Wittie, L. D.

1984-01-01

Decentralized operating systems that control large multicomputers need techniques to schedule competing parallel programs called task forces. Wave scheduling is a probabilistic technique that uses a hierarchical distributed virtual machine to schedule task forces by recursively subdividing and issuing wavefront-like commands to processing elements capable of executing individual tasks. Wave scheduling is highly resistant to processing element failures because it uses many distributed schedulers that dynamically assign scheduling responsibilities among themselves. The scheduling technique is trivially extensible as more processing elements join the host multicomputer. A simple model of scheduling cost is used by every scheduler node to distribute scheduling activity and minimize wasted processing capacity by using perceived workload to vary decentralized scheduling rules. At low to moderate levels of network activity, wave scheduling is only slightly less efficient than a central scheduler in its ability to direct processing elements to accomplish useful work.

EQUITY EVALUATION OF PADDY IRRIGATION WATER DISTRIBUTION BY SOCIETY-JUSTICE-WATER DISTRIBUTION RULE HYPOTHESIS

NASA Astrophysics Data System (ADS)

Tanji, Hajime; Kiri, Hirohide; Kobayashi, Shintaro

When total supply is smaller than total demand, it is difficult to apply the paddy irrigation water distribution rule. The gap must be narrowed by decreasing demand. Historically, the upstream served rule, rotation schedule, or central schedule weight to irrigated area was adopted. This paper proposes the hypothesis that these rules are dependent on social justice, a hypothesis called the "Society-Justice-Water Distribution Rule Hypothesis". Justice, which means a balance of efficiency and equity of distribution, is discussed under the political philosophy of utilitarianism, liberalism (Rawls), libertarianism, and communitarianism. The upstream served rule can be derived from libertarianism. The rotation schedule and central schedule can be derived from communitarianism. Liberalism can provide arranged schedule to adjust supply and demand based on "the Difference Principle". The authors conclude that to achieve efficiency and equity, liberalism may provide the best solution after modernization.

Simulated annealing with probabilistic analysis for solving traveling salesman problems

NASA Astrophysics Data System (ADS)

Hong, Pei-Yee; Lim, Yai-Fung; Ramli, Razamin; Khalid, Ruzelan

2013-09-01

Simulated Annealing (SA) is a widely used meta-heuristic that was inspired from the annealing process of recrystallization of metals. Therefore, the efficiency of SA is highly affected by the annealing schedule. As a result, in this paper, we presented an empirical work to provide a comparable annealing schedule to solve symmetric traveling salesman problems (TSP). Randomized complete block design is also used in this study. The results show that different parameters do affect the efficiency of SA and thus, we propose the best found annealing schedule based on the Post Hoc test. SA was tested on seven selected benchmarked problems of symmetric TSP with the proposed annealing schedule. The performance of SA was evaluated empirically alongside with benchmark solutions and simple analysis to validate the quality of solutions. Computational results show that the proposed annealing schedule provides a good quality of solution.

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.

A generalized network flow model for the multi-mode resource-constrained project scheduling problem with discounted cash flows

NASA Astrophysics Data System (ADS)

Chen, Miawjane; Yan, Shangyao; Wang, Sin-Siang; Liu, Chiu-Lan

2015-02-01

An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time-precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.

Computing the Expected Cost of an Appointment Schedule for Statistically Identical Customers with Probabilistic Service Times

PubMed Central

Dietz, Dennis C.

2014-01-01

A cogent method is presented for computing the expected cost of an appointment schedule where customers are statistically identical, the service time distribution has known mean and variance, and customer no-shows occur with time-dependent probability. The approach is computationally efficient and can be easily implemented to evaluate candidate schedules within a schedule optimization algorithm. PMID:24605070

Optimal load scheduling in commercial and residential microgrids

NASA Astrophysics Data System (ADS)

Ganji Tanha, Mohammad Mahdi

Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants' comfort level, and microgrid operation constraints. The CBOLS' objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying single-unit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.

Profit-based conventional resource scheduling with renewable energy penetration

NASA Astrophysics Data System (ADS)

Reddy, K. Srikanth; Panwar, Lokesh Kumar; Kumar, Rajesh; Panigrahi, B. K.

2017-08-01

Technological breakthroughs in renewable energy technologies (RETs) enabled them to attain grid parity thereby making them potential contenders for existing conventional resources. To examine the market participation of RETs, this paper formulates a scheduling problem accommodating energy market participation of wind- and solar-independent power producers (IPPs) treating both conventional and RETs as identical entities. Furthermore, constraints pertaining to penetration and curtailments of RETs are restructured. Additionally, an appropriate objective function for profit incurred by conventional resource IPPs through reserve market participation as a function of renewable energy curtailment is also proposed. The proposed concept is simulated with a test system comprising 10 conventional generation units in conjunction with solar photovoltaic (SPV) and wind energy generators (WEG). The simulation results indicate that renewable energy integration and its curtailment limits influence the market participation or scheduling strategies of conventional resources in both energy and reserve markets. Furthermore, load and reliability parameters are also affected.

Multi-time Scale Joint Scheduling Method Considering the Grid of Renewable Energy

NASA Astrophysics Data System (ADS)

Zhijun, E.; Wang, Weichen; Cao, Jin; Wang, Xin; Kong, Xiangyu; Quan, Shuping

2018-01-01

Renewable new energy power generation prediction error like wind and light, brings difficulties to dispatch the power system. In this paper, a multi-time scale robust scheduling method is set to solve this problem. It reduces the impact of clean energy prediction bias to the power grid by using multi-time scale (day-ahead, intraday, real time) and coordinating the dispatching power output of various power supplies such as hydropower, thermal power, wind power, gas power and. The method adopts the robust scheduling method to ensure the robustness of the scheduling scheme. By calculating the cost of the abandon wind and the load, it transforms the robustness into the risk cost and optimizes the optimal uncertainty set for the smallest integrative costs. The validity of the method is verified by simulation.

Compressed-air energy-storage preliminary design and site-development program in an aquifer. Volume 9: Cost estimate and schedule

NASA Astrophysics Data System (ADS)

1982-12-01

The behavior and suitability of aquifers as compressed-air energy-storage sites is discussed. The engineering and construction schedule, facilities capital-cost estimate, and corresponding cash-flow requirements are given.

Short-term hydro generation and interchange contract scheduling for Swiss Rail

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

Christoforidis, M.; Awobamise, B.; Tong, S.

This paper describes the Short-Term Resource Scheduling (STRS) function that has been developed by Siemens-Empros as part of the new SBB/Direktion Kraftwerk (Swiss Rail) Energy Management System. Optimal scheduling of the single-phase hydro plants, single-phase and three-phase energy accounts, and purchase and sale of three phase energy subject to a multitude of physical and contractual constraints (including spinning and regulating reserve requirements), is the main objective of the STRS function. The operations planning horizon of STRS is one day to one week using an hourly time increment.

System and method for optimal load and source scheduling in context aware homes

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

Shetty, Pradeep; Foslien Graber, Wendy; Mangsuli, Purnaprajna R.

A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

Flight-Deck Strategies and Outcomes When Flying Schedule-Matching Descents

NASA Technical Reports Server (NTRS)

Kaneshige, John T.; Sharma, Shivanjli; Martin Lynne; Lozito, Sandra; Dulchinos, Victoria

2013-01-01

Recent studies at NASA Ames Research Center have investigated the development and use of ground-based (air traffic controller) tools to manage and schedule air traffic in future terminal airspace. An exploratory study was undertaken to investigate the impacts that such tools (and concepts) could have on the flight-deck. Ten Boeing 747-400 crews flew eight optimized profile descents in the Los Angeles terminal airspace, while receiving scripted current day and futuristic speed clearances, to ascertain their ability to fly schedulematching descents without prior training. Although the study was exploratory in nature, four variables were manipulated: route constraints, winds, speed changes, and clearance phraseology. Despite flying the same scenarios with the same events and timing, there were significant differences in the time it took crews to fly the approaches. This variation is the product of a number of factors but highlights potential difficulties for scheduling tools that would have to accommodate this amount of natural variation in descent times. The focus of this paper is the examination of the crews' aircraft management strategies and outcomes. This includes potentially problematic human-automation interaction issues that may negatively impact arrival times, speed and altitude constraint compliance, and energy management efficiency.

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

PubMed Central

Dinh, Thanh; Kim, Younghan

2016-01-01

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. PMID:27367689

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud.

PubMed

Dinh, Thanh; Kim, Younghan

2016-06-28

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

A criterion autoscheduler for long range planning

NASA Technical Reports Server (NTRS)

Sponsler, Jeffrey L.

1994-01-01

A constraint-based scheduling system called SPIKE is used to create long-term schedules for the Hubble Space Telescope. A meta-level scheduler called the Criterion Autoscheduler for Long range planning (CASL) was created to guide SPIKE's schedule generation according to the agenda of the planning scientists. It is proposed that sufficient flexibility exists in a schedule to allow high level planning heuristics to be applied without adversely affected crucial constraints such as spacecraft efficiency. This hypothesis is supported by test data which is described.

Dynamic I/O Power Management for Hard Real-Time Systems

DTIC Science & Technology

2005-01-01

recently emerged as an attractive alternative to inflexible hardware solutions. DPM for hard real - time systems has received relatively little attention...In particular, energy-driven I/O device scheduling for real - time systems has not been considered before. We present the first online DPM algorithm...which we call Low Energy Device Scheduler (LEDES), for hard real - time systems . LEDES takes as inputs a predetermined task schedule and a device-usage

10 CFR 2.332 - General case scheduling and management.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false General case scheduling and management. 2.332 Section 2... Management for NRC Adjudicatory Hearings § 2.332 General case scheduling and management. (a) Scheduling order... the issues presented, relevant considerations which a party may bring to the attention of the...

An Energy Saver Called NECAP

NASA Technical Reports Server (NTRS)

1979-01-01

One of the most comprehensive and most effective programs is NECAP, an acronym for NASA Energy Cost Analysis Program. Developed by Langley Research Center, NECAP operates according to heating/cooling calculation procedures formulated by the American Society of Heating, Refrigeration and Air Conditioning Engineers (ASHRAE). The program enables examination of a multitude of influences on heat flow into and out of buildings. For example, NECAP considers traditional weather patterns for a given locale and predicts the effects on a particular building design of sun, rain, wind, even shadows from other buildings. It takes into account the mass of structural materials, insulating values, the type of equipment the building will house, equipment operating schedules, heat by people and machinery, heat loss or gain through windows and other openings and a variety of additional details. NECAP ascertains how much energy the building should require ideally, aids selection of the most economical and most efficient energy systems and suggests design and operational measures for reducing the building's energy needs. Most importantly, NECAP determines cost effectiveness- whether an energy-saving measure will pay back its installation cost through monetary savings in energy bills. thrown off

The R-Shell approach - Using scheduling agents in complex distributed real-time systems

NASA Technical Reports Server (NTRS)

Natarajan, Swaminathan; Zhao, Wei; Goforth, Andre

1993-01-01

Large, complex real-time systems such as space and avionics systems are extremely demanding in their scheduling requirements. The current OS design approaches are quite limited in the capabilities they provide for task scheduling. Typically, they simply implement a particular uniprocessor scheduling strategy and do not provide any special support for network scheduling, overload handling, fault tolerance, distributed processing, etc. Our design of the R-Shell real-time environment fcilitates the implementation of a variety of sophisticated but efficient scheduling strategies, including incorporation of all these capabilities. This is accomplished by the use of scheduling agents which reside in the application run-time environment and are responsible for coordinating the scheduling of the application.

Where-Fi: a dynamic energy-efficient multimedia distribution framework for MANETs

NASA Astrophysics Data System (ADS)

Mohapatra, Shivajit; Carbunar, Bogdan; Pearce, Michael; Chaudhri, Rohit; Vasudevan, Venu

2008-01-01

Next generation mobile ad-hoc applications will revolve around users' need for sharing content/presence information with co-located devices. However, keeping such information fresh requires frequent meta-data exchanges, which could result in significant energy overheads. To address this issue, we propose distributed algorithms for energy efficient dissemination of presence and content usage information between nodes in mobile ad-hoc networks. First, we introduce a content dissemination protocol (called CPMP) for effectively distributing frequent small meta-data updates between co-located devices using multicast. We then develop two distributed algorithms that use the CPMP protocol to achieve "phase locked" wake up cycles for all the participating nodes in the network. The first algorithm is designed for fully-connected networks and then extended in the second to handle hidden terminals. The "phase locked" schedules are then exploited to adaptively transition the network interface to a deep sleep state for energy savings. We have implemented a prototype system (called "Where-Fi") on several Motorola Linux-based cell phone models. Our experimental results show that for all network topologies our algorithms were able to achieve "phase locking" between nodes even in the presence of hidden terminals. Moreover, we achieved battery lifetime extensions of as much as 28% for fully connected networks and about 20% for partially connected networks.

10 CFR 474.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

...; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION § 474.2 Definitions. For the purposes of this part, the term: Combined energy consumption value means the weighted average of the Urban Dynamometer Driving Schedule and the Highway Fuel Economy Driving Schedule energy consumption values (weighted 55/45 percent...

10 CFR 474.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

...; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION § 474.2 Definitions. For the purposes of this part, the term: Combined energy consumption value means the weighted average of the Urban Dynamometer Driving Schedule and the Highway Fuel Economy Driving Schedule energy consumption values (weighted 55/45 percent...

10 CFR 474.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

...; PETROLEUM-EQUIVALENT FUEL ECONOMY CALCULATION § 474.2 Definitions. For the purposes of this part, the term: Combined energy consumption value means the weighted average of the Urban Dynamometer Driving Schedule and the Highway Fuel Economy Driving Schedule energy consumption values (weighted 55/45 percent...

Population Annealing Monte Carlo for Frustrated Systems

NASA Astrophysics Data System (ADS)

Amey, Christopher; Machta, Jonathan

Population annealing is a sequential Monte Carlo algorithm that efficiently simulates equilibrium systems with rough free energy landscapes such as spin glasses and glassy fluids. A large population of configurations is initially thermalized at high temperature and then cooled to low temperature according to an annealing schedule. The population is kept in thermal equilibrium at every annealing step via resampling configurations according to their Boltzmann weights. Population annealing is comparable to parallel tempering in terms of efficiency, but has several distinct and useful features. In this talk I will give an introduction to population annealing and present recent progress in understanding its equilibration properties and optimizing it for spin glasses. Results from large-scale population annealing simulations for the Ising spin glass in 3D and 4D will be presented. NSF Grant DMR-1507506.

Multi-core processing and scheduling performance in CMS

NASA Astrophysics Data System (ADS)

Hernández, J. M.; Evans, D.; Foulkes, S.

2012-12-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resulting in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.

Computer Applications in Class and Transportation Scheduling. Educational Management Review Series Number 1.

ERIC Educational Resources Information Center

Piele, Philip K.

This document shows how computer technology can aid educators in meeting demands for improved class scheduling and more efficient use of transportation resources. The first section surveys literature on operational systems that provide individualized scheduling for students, varied class structures, and maximum use of space and staff skills.…

A Market-Based Approach to Multi-factory Scheduling

NASA Astrophysics Data System (ADS)

Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

Centralized mission planning and scheduling system for the Landsat Data Continuity Mission

USGS Publications Warehouse

Kavelaars, Alicia; Barnoy, Assaf M.; Gregory, Shawna; Garcia, Gonzalo; Talon, Cesar; Greer, Gregory; Williams, Jason; Dulski, Vicki

2014-01-01

Satellites in Low Earth Orbit provide missions with closer range for studying aspects such as geography and topography, but often require efficient utilization of space and ground assets. Optimizing schedules for these satellites amounts to a complex planning puzzle since it requires operators to face issues such as discontinuous ground contacts, limited onboard memory storage, constrained downlink margin, and shared ground antenna resources. To solve this issue for the Landsat Data Continuity Mission (LDCM, Landsat 8), all the scheduling exchanges for science data request, ground/space station contact, and spacecraft maintenance and control will be coordinated through a centralized Mission Planning and Scheduling (MPS) engine, based upon GMV’s scheduling system flexplan9 . The synchronization between all operational functions must be strictly maintained to ensure efficient mission utilization of ground and spacecraft activities while working within the bounds of the space and ground resources, such as Solid State Recorder (SSR) and available antennas. This paper outlines the functionalities that the centralized planning and scheduling system has in its operational control and management of the Landsat 8 spacecraft.

Energy efficient sensor scheduling with a mobile sink node for the target tracking application.

PubMed

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance.

Energy Efficient Sensor Scheduling with a Mobile Sink Node for the Target Tracking Application

PubMed Central

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance PMID:22399934

Comparison between solar utilization of a closed microalgae-based bio-loop and that of a stand-alone photovoltaic system.

PubMed

Jin, Qiang; Chen, Lei; Li, Aimin; Liu, Fuqiang; Long, Chao; Shan, Aidang; Borthwick, Alistair G L

2015-05-01

This study compared the solar energy utilization of a closed microalgae-based bio-loop for energy efficient production of biogas with fertilizer recovery against that of a stand-alone photovoltaic (PV) system. The comparison was made from the perspective of broad life cycle assessment, simultaneously taking exergy to be the functional unit. The results indicated that the bio-loop was more environmentally competitive than an equivalent stand-alone PV system, but had higher economic cost due to high energy consumption during the operational phase. To fix the problem, a patented, interior pressurization scheduling method was used to operate the bio-loop, with microalgae and aerobic bacterial placed together in the same reactor. As a result, the overall environmental impact and total investment were respectively reduced by more than 75% and 84%, a vast improvement on the bio-loop. Copyright © 2014 Elsevier Ltd. All rights reserved.

U. S. fusion programs: Struggling to stay in the game

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

Crawford, M.

Funding for the US fusion energy program has suffered and will probably continue to suffer major cuts. A committee hand-picked by Energy Secretary James Watkins urged the Department of Energy to mount an aggressive program to develop fusion power, but congress cut funding from $323 million in 1990 to $275 million in 1991. This portends dire conditions for fusion research and development. Projects to receive top priority are concerned with the tokamaks and to keep the next big machine, the Burning Plasma Experiment, scheduled for beginning of construction in 1993 on schedule. Secretary Watkins is said to want to keepmore » the International Thermonuclear Energy Reactor (ITER) on schedule. ITER would follow the Burning Plasma Experiment.« less

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

Torcellini, P.; Pless, S.; Lobato, C.

Until recently, large-scale, cost-effective net-zero energy buildings (NZEBs) were thought to lie decades in the future. However, ongoing work at the National Renewable Energy Laboratory (NREL) indicates that NZEB status is both achievable and repeatable today. This paper presents a definition framework for classifying NZEBs and a real-life example that demonstrates how a large-scale office building can cost-effectively achieve net-zero energy. The vision of NZEBs is compelling. In theory, these highly energy-efficient buildings will produce, during a typical year, enough renewable energy to offset the energy they consume from the grid. The NREL NZEB definition framework classifies NZEBs according tomore » the criteria being used to judge net-zero status and the way renewable energy is supplied to achieve that status. We use the new U.S. Department of Energy/NREL 220,000-ft{sub 2} Research Support Facilities (RSF) building to illustrate why a clear picture of NZEB definitions is important and how the framework provides a methodology for creating a cost-effective NZEB. The RSF, scheduled to open in June 2010, includes contractual commitments to deliver a Leadership in Energy Efficiency and Design (LEED) Platinum Rating, an energy use intensity of 25 kBtu/ft{sub 2} (half that of a typical LEED Platinum office building), and net-zero energy status. We will discuss the analysis method and cost tradeoffs that were performed throughout the design and build phases to meet these commitments and maintain construction costs at $259/ft{sub 2}. We will discuss ways to achieve large-scale, replicable NZEB performance. Many passive and renewable energy strategies are utilized, including full daylighting, high-performance lighting, natural ventilation through operable windows, thermal mass, transpired solar collectors, radiant heating and cooling, and workstation configurations allow for maximum daylighting.« less

Mission and science activity scheduling language

NASA Technical Reports Server (NTRS)

Hull, Larry G.

1993-01-01

To support the distributed and complex operational scheduling required for future National Aeronautics and Space Administration (NASA) missions, a formal, textual language, the Scheduling Applications Interface Language (SAIL), has been developed. Increased geographic dispersion of investigators is leading to distributed mission and science activity planning, scheduling, and operations. SAIL is an innovation which supports the effective and efficient communication of scheduling information among physically dispersed applications in distributed scheduling environments. SAIL offers a clear, concise, unambiguous expression of scheduling information in a readable, hardware independent format. The language concept, syntax, and semantics incorporate language features found useful during five years of research and prototyping with scheduling languages in physically distributed environments. SAIL allows concise specification of mission and science activity plans in a format which promotes repetition and reuse.

Investigations of fluid-strain interaction using Plate Boundary Observatory borehole data

NASA Astrophysics Data System (ADS)

Boyd, Jeffrey Michael

Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense and encompasses sensors, feature calculations, activity classification algorithms, sleep schedules, and transmission protocols. Design choices in each of these areas impact energy use, overall accuracy, and usefulness of the system. This thesis explores methods software can influence the trade-off between energy consumption and system accuracy. In general the more energy a system consumes the more accurate will be. We explore how finding the transitions between human activities is able to reduce the energy consumption of such systems without reducing much accuracy. We introduce the Log-likelihood Ratio Test as a method to detect transitions, and explore how choices of sensor, feature calculations, and parameters concerning time segmentation affect the accuracy of this method. We discovered an approximate 5X increase in energy efficiency could be achieved with only a 5% decrease in accuracy. We also address how a system's sleep mode, in which the processor enters a low-power state and sensors are turned off, affects a wearable computing platform that does activity recognition. We discuss the energy trade-offs in each stage of the activity recognition process. We find that careful analysis of these parameters can result in great increases in energy efficiency if small compromises in overall accuracy can be tolerated. We call this the ``Great Compromise.'' We found a 6X increase in efficiency with a 7% decrease in accuracy. We then consider how wireless transmission of data affects the overall energy efficiency of a wearable computing platform. We find that design decisions such as feature calculations and grouping size have a great impact on the energy consumption of the system because of the amount of data that is stored and transmitted. For example, storing and transmitting vector-based features such as FFT or DCT do not compress the signal and would use more energy than storing and transmitting the raw signal. The effect of grouping size on energy consumption depends on the feature. For scalar features energy consumption is proportional in the inverse of grouping size, so it's reduced as grouping size goes up. For features that depend on the grouping size, such as FFT, energy increases with the logarithm of grouping size, so energy consumption increases slowly as grouping size increases. We find that compressing data through activity classification and transition detection significantly reduces energy consumption and that the energy consumed for the classification overhead is negligible compared to the energy savings from data compression. We provide mathematical models of energy usage and data generation, and test our ideas using a mobile computing platform, the Texas Instruments Chronos watch.

Research on scheduling of robotic transient survey for Antarctic Survey Telescopes (AST3)

NASA Astrophysics Data System (ADS)

Liu, Qiang; Wei, Peng; Shang, Zhao-Hui; Ma, Bin; Hu, Yi

2018-01-01

Antarctic Survey Telescopes (AST3) are designed to be fully robotic telescopes at Dome A, Antarctica, which aim for highly efficient time-domain sky surveys as well as rapid response to special transient events (e.g., gamma-ray bursts, near-Earth asteroids, supernovae, etc.). Unlike traditional observations, a well-designed real-time survey scheduler is needed in order to implement an automatic survey in a very efficient, reliable and flexible way for the unattended telescopes. We present a study of the survey strategy for AST3 and implementation of its survey scheduler, which is also useful for other survey projects.

Production scheduling and rescheduling with genetic algorithms.

PubMed

Bierwirth, C; Mattfeld, D C

1999-01-01

A general model for job shop scheduling is described which applies to static, dynamic and non-deterministic production environments. Next, a Genetic Algorithm is presented which solves the job shop scheduling problem. This algorithm is tested in a dynamic environment under different workload situations. Thereby, a highly efficient decoding procedure is proposed which strongly improves the quality of schedules. Finally, this technique is tested for scheduling and rescheduling in a non-deterministic environment. It is shown by experiment that conventional methods of production control are clearly outperformed at reasonable run-time costs.

Optimization of the computational load of a hypercube supercomputer onboard a mobile robot.

PubMed

Barhen, J; Toomarian, N; Protopopescu, V

1987-12-01

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of singleneuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as prec xdence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Optimization of the computational load of a hypercube supercomputer onboard a mobile robot

NASA Technical Reports Server (NTRS)

Barhen, Jacob; Toomarian, N.; Protopopescu, V.

1987-01-01

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of single-neuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as precedence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Cost-efficient scheduling of FAST observations

NASA Astrophysics Data System (ADS)

Luo, Qi; Zhao, Laiping; Yu, Ce; Xiao, Jian; Sun, Jizhou; Zhu, Ming; Zhong, Yi

2018-03-01

A cost-efficient schedule for the Five-hundred-meter Aperture Spherical radio Telescope (FAST) requires to maximize the number of observable proposals and the overall scientific priority, and minimize the overall slew-cost generated by telescope shifting, while taking into account the constraints including the astronomical objects visibility, user-defined observable times, avoiding Radio Frequency Interference (RFI). In this contribution, first we solve the problem of maximizing the number of observable proposals and scientific priority by modeling it as a Minimum Cost Maximum Flow (MCMF) problem. The optimal schedule can be found by any MCMF solution algorithm. Then, for minimizing the slew-cost of the generated schedule, we devise a maximally-matchable edges detection-based method to reduce the problem size, and propose a backtracking algorithm to find the perfect matching with minimum slew-cost. Experiments on a real dataset from NASA/IPAC Extragalactic Database (NED) show that, the proposed scheduler can increase the usage of available times with high scientific priority and reduce the slew-cost significantly in a very short time.

An Efficient Randomized Algorithm for Real-Time Process Scheduling in PicOS Operating System

NASA Astrophysics Data System (ADS)

Helmy*, Tarek; Fatai, Anifowose; Sallam, El-Sayed

PicOS is an event-driven operating environment designed for use with embedded networked sensors. More specifically, it is designed to support the concurrency in intensive operations required by networked sensors with minimal hardware requirements. Existing process scheduling algorithms of PicOS; a commercial tiny, low-footprint, real-time operating system; have their associated drawbacks. An efficient, alternative algorithm, based on a randomized selection policy, has been proposed, demonstrated, confirmed for efficiency and fairness, on the average, and has been recommended for implementation in PicOS. Simulations were carried out and performance measures such as Average Waiting Time (AWT) and Average Turn-around Time (ATT) were used to assess the efficiency of the proposed randomized version over the existing ones. The results prove that Randomized algorithm is the best and most attractive for implementation in PicOS, since it is most fair and has the least AWT and ATT on average over the other non-preemptive scheduling algorithms implemented in this paper.

Idle efficiency and pollution results for two-row swirl-can combustors having 72 modules

NASA Technical Reports Server (NTRS)

Biaglow, J. A.; Trout, A. M.

1975-01-01

Two 72-swirl-can-module combustors were investigated in a full annular combustor test facility at engine idle conditions typical of a 30:1 pressure-ratio engine. The effects of radial and circumferential fuel scheduling on combustion efficiency and gaseous pollutants levels were determined. Test conditions were inlet-air temperature, 452 K; inlet total pressure, 34.45 newtons per square centimeter; and reference velocity, 19.5 meters per second. A maximum combustion efficiency of 98.1 percent was achieved by radial scheduling of fuel to the inner row of swirl-can modules. Emission index values were 6.9 for unburned hydrocarbons and 50.6 for carbon monoxide at a fuel-air ratio of 0.0119. Circumferential fuel scheduling of two 90 degree sectors of the swirl-can arrays produced a maximum combustion efficiency of 97.3 percent. The emission index values were 12.0 for unburned hydrocarbons and 69.2 for carbon monoxide at a fuel-air ratio of 0.0130.

Design and Scheduling of Microgrids using Benders Decomposition

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

Nagarajan, Adarsh; Ayyanar, Raja

2016-11-21

The distribution feeder laterals in a distribution feeder with relatively high PV generation as compared to the load can be operated as microgrids to achieve reliability, power quality and economic benefits. However, renewable resources are intermittent and stochastic in nature. A novel approach for sizing and scheduling an energy storage system and microturbine for reliable operation of microgrids is proposed. The size and schedule of an energy storage system and microturbine are determined using Benders' decomposition, considering PV generation as a stochastic resource.

The role of nuclear energy in mitigating greenhouse warming

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

Krakowski, R.A.

1997-12-31

A behavioral, top-down, forced-equilibrium market model of long-term ({approximately} 2,100) global energy-economics interactions has been modified with a bottom-up nuclear energy model and used to construct consistent scenarios describing future impacts of civil nuclear materials flows in an expanding, multi-regional (13) world economy. The relative measures and tradeoffs between economic (GNP, tax impacts, productivity, etc.), environmental (greenhouse gas accumulations, waste accumulation, proliferation risk), and energy (resources, energy mixes, supply-side versus demand-side attributes) interactions that emerge from these analyses are focused herein on advancing understanding of the role that nuclear energy (and other non-carbon energy sources) might play in mitigating greenhousemore » warming. Two ostensibly opposing scenario drivers are investigated: (a) demand-side improvements in (non-price-induced) autonomous energy efficiency improvements; and (b) supply-side carbon-tax inducements to shift energy mixes towards reduced- or non-carbon forms. In terms of stemming greenhouse warming for minimal cost of greenhouse-gas abatement, and with the limitations of the simplified taxing schedule used, a symbiotic combination of these two approaches may offer advantages not found if each is applied separately.« less

A Distributed Middleware Architecture for Attack-Resilient Communications in Smart Grids

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

Hodge, Brian S; Wu, Yifu; Wei, Jin

Distributed Energy Resources (DERs) are being increasingly accepted as an excellent complement to traditional energy sources in smart grids. As most of these generators are geographically dispersed, dedicated communications investments for every generator are capital cost prohibitive. Real-time distributed communications middleware, which supervises, organizes and schedules tremendous amounts of data traffic in smart grids with high penetrations of DERs, allows for the use of existing network infrastructure. In this paper, we propose a distributed attack-resilient middleware architecture that detects and mitigates the congestion attacks by exploiting the Quality of Experience (QoE) measures to complement the conventional Quality of Service (QoS)more » information to detect and mitigate the congestion attacks effectively. The simulation results illustrate the efficiency of our proposed communications middleware architecture.« less

A Distributed Middleware Architecture for Attack-Resilient Communications in Smart Grids: Preprint

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

Wu, Yifu; Wei, Jin; Hodge, Bri-Mathias

Distributed energy resources (DERs) are being increasingly accepted as an excellent complement to traditional energy sources in smart grids. Because most of these generators are geographically dispersed, dedicated communications investments for every generator are capital-cost prohibitive. Real-time distributed communications middleware - which supervises, organizes, and schedules tremendous amounts of data traffic in smart grids with high penetrations of DERs - allows for the use of existing network infrastructure. In this paper, we propose a distributed attack-resilient middleware architecture that detects and mitigates the congestion attacks by exploiting the quality of experience measures to complement the conventional quality of service informationmore » to effectively detect and mitigate congestion attacks. The simulation results illustrate the efficiency of our proposed communications middleware architecture.« less

NASA's Exploration Technology Development Program Energy Storage Project Battery Technology Development

NASA Technical Reports Server (NTRS)

Reid, Concha M.; Miller, Thomas B.; Mercer, Carolyn R.; Jankovsky, Amy L.

2010-01-01

Technical Interchange Meeting was held at Saft America s Research and Development facility in Cockeysville, Maryland on Sept 28th-29th, 2010. The meeting was attended by Saft, contractors who are developing battery component materials under contracts awarded through a NASA Research Announcement (NRA), and NASA. This briefing presents an overview of the components being developed by the contractor attendees for the NASA s High Energy (HE) and Ultra High Energy (UHE) cells. The transition of the advanced lithium-ion cell development project at NASA from the Exploration Technology Development Program Energy Storage Project to the Enabling Technology Development and Demonstration High Efficiency Space Power Systems Project, changes to deliverable hardware and schedule due to a reduced budget, and our roadmap to develop cells and provide periodic off-ramps for cell technology for demonstrations are discussed. This meeting gave the materials and cell developers the opportunity to discuss the intricacies of their materials and determine strategies to address any particulars of the technology.

Task Scheduling in Desktop Grids: Open Problems

NASA Astrophysics Data System (ADS)

Chernov, Ilya; Nikitina, Natalia; Ivashko, Evgeny

2017-12-01

We survey the areas of Desktop Grid task scheduling that seem to be insufficiently studied so far and are promising for efficiency, reliability, and quality of Desktop Grid computing. These topics include optimal task grouping, "needle in a haystack" paradigm, game-theoretical scheduling, domain-imposed approaches, special optimization of the final stage of the batch computation, and Enterprise Desktop Grids.

78 FR 63176 - Notice Announcing Workshop; Zero Rate Reactive Power Rate Schedules

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-23

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. AD14-1-000] Notice Announcing Workshop; Zero Rate Reactive Power Rate Schedules Concurrent with this notice, the Commission is issuing an order in Chehalis Power Generating, L.P., Docket No. ER05-1056-007 clarifying its policy...

18 CFR 2.52 - Suspension of rate schedules.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Suspension of rate schedules. 2.52 Section 2.52 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

18 CFR 2.4 - Suspension of rate schedules.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Suspension of rate schedules. 2.4 Section 2.4 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

18 CFR 2.52 - Suspension of rate schedules.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Suspension of rate schedules. 2.52 Section 2.52 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

18 CFR 2.4 - Suspension of rate schedules.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Suspension of rate schedules. 2.4 Section 2.4 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

18 CFR 2.4 - Suspension of rate schedules.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Suspension of rate schedules. 2.4 Section 2.4 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

18 CFR 2.52 - Suspension of rate schedules.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Suspension of rate schedules. 2.52 Section 2.52 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

18 CFR 2.52 - Suspension of rate schedules.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Suspension of rate schedules. 2.52 Section 2.52 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

18 CFR 2.4 - Suspension of rate schedules.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Suspension of rate schedules. 2.4 Section 2.4 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES GENERAL POLICY AND INTERPRETATIONS Statements of General Policy and...

How should periods without social interaction be scheduled? Children's preference for practical schedules of positive reinforcement.

PubMed

Luczynski, Kevin C; Hanley, Gregory P

2014-01-01

Several studies have shown that children prefer contingent reinforcement (CR) rather than yoked noncontingent reinforcement (NCR) when continuous reinforcement is programmed in the CR schedule. Preference has not, however, been evaluated for practical schedules that involve CR. In Study 1, we assessed 5 children's preference for obtaining social interaction via a multiple schedule (periods of fixed-ratio 1 reinforcement alternating with periods of extinction), a briefly signaled delayed reinforcement schedule, and an NCR schedule. The multiple schedule promoted the most efficient level of responding. In general, children chose to experience the multiple schedule and avoided the delay and NCR schedules, indicating that they preferred multiple schedules as the means to arrange practical schedules of social interaction. In Study 2, we evaluated potential controlling variables that influenced 1 child's preference for the multiple schedule and found that the strong positive contingency was the primary variable. © Society for the Experimental Analysis of Behavior.

Capability of the Maximax&Maximin selection operator in the evolutionary algorithm for a nurse scheduling problem

NASA Astrophysics Data System (ADS)

Ramli, Razamin; Tein, Lim Huai

2016-08-01

A good work schedule can improve hospital operations by providing better coverage with appropriate staffing levels in managing nurse personnel. Hence, constructing the best nurse work schedule is the appropriate effort. In doing so, an improved selection operator in the Evolutionary Algorithm (EA) strategy for a nurse scheduling problem (NSP) is proposed. The smart and efficient scheduling procedures were considered. Computation of the performance of each potential solution or schedule was done through fitness evaluation. The best so far solution was obtained via special Maximax&Maximin (MM) parent selection operator embedded in the EA, which fulfilled all constraints considered in the NSP.

Scheduling from the perspective of the application

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

Berman, F.; Wolski, R.

1996-12-31

Metacomputing is the aggregation of distributed and high-performance resources on coordinated networks. With careful scheduling, resource-intensive applications can be implemented efficiently on metacomputing systems at the sizes of interest to developers and users. In this paper we focus on the problem of scheduling applications on metacomputing systems. We introduce the concept of application-centric scheduling in which everything about the system is evaluated in terms of its impact on the application. Application-centric scheduling is used by virtually all metacomputer programmers to achieve performance on metacomputing systems. We describe two successful metacomputing applications to illustrate this approach, and describe AppLeS scheduling agentsmore » which generalize the application-centric scheduling approach. Finally, we show preliminary results which compare AppLeS-derived schedules with conventional strip and blocked schedules for a two-dimensional Jacobi code.« less

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.

A Dynamic Scheduling Method of Earth-Observing Satellites by Employing Rolling Horizon Strategy

PubMed Central

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

2013-01-01

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments. PMID:23690742

A dynamic scheduling method of Earth-observing satellites by employing rolling horizon strategy.

PubMed

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

2013-01-01

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments.

Matrix Algebra for GPU and Multicore Architectures (MAGMA) for Large Petascale Systems

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

Dongarra, Jack J.; Tomov, Stanimire

2014-03-24

The goal of the MAGMA project is to create a new generation of linear algebra libraries that achieve the fastest possible time to an accurate solution on hybrid Multicore+GPU-based systems, using all the processing power that future high-end systems can make available within given energy constraints. Our efforts at the University of Tennessee achieved the goals set in all of the five areas identified in the proposal: 1. Communication optimal algorithms; 2. Autotuning for GPU and hybrid processors; 3. Scheduling and memory management techniques for heterogeneity and scale; 4. Fault tolerance and robustness for large scale systems; 5. Building energymore » efficiency into software foundations. The University of Tennessee’s main contributions, as proposed, were the research and software development of new algorithms for hybrid multi/many-core CPUs and GPUs, as related to two-sided factorizations and complete eigenproblem solvers, hybrid BLAS, and energy efficiency for dense, as well as sparse, operations. Furthermore, as proposed, we investigated and experimented with various techniques targeting the five main areas outlined.« less

Artificial intelligence for the CTA Observatory scheduler

NASA Astrophysics Data System (ADS)

Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro

2014-08-01

The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint Propagation techniques. A simulation platform, an analysis tool and different test case scenarios for CTA were developed to test the performance of the scheduler and are also described.

Pricing for scarcity? An efficiency analysis of increasing block tariffs

NASA Astrophysics Data System (ADS)

Monteiro, Henrique; Roseta-Palma, Catarina

2011-06-01

Water pricing schedules often contain significant nonlinearities, such as the increasing block tariff (IBT) structure that is abundantly applied for residential users. The IBT is frequently supported as a good tool for achieving the goals of equity, water conservation, and revenue neutrality but seldom has been grounded on efficiency justifications. In particular, existing literature on water pricing establishes that although efficient schedules will depend on demand and supply characteristics, IBT cannot usually be recommended. In this paper, we consider whether the explicit inclusion of scarcity considerations can strengthen the appeal of IBT. Results show that when both demand and costs react to climate factors, increasing marginal prices may come about as a response to a combination of water scarcity and customer heterogeneity. We derive testable conditions and then illustrate their application through an estimation of Portuguese residential water demand. We show that the recommended tariff schedule hinges crucially on the choice of functional form for demand.

Decompression from He-N2-O2 (TRIMIX) Bounce Dives Is Not More Efficient Than From He-O2 (HELIOX) Bounce Dives

DTIC Science & Technology

2015-05-28

Diver Characteristics Appendix E Diving Schedule Appendix F Medical Incidents Appendix G UBA Gas Compositions iv ACKNOWLEDGEMENTS The...experimental dives (median = 3). The schedule of each diver’s participation in experimental dives is given in Appendix E . Divers were required to avoid any...divers’ participation on each test schedule is given in Appendix E . The numbers of completed man-dives on the two schedules are not multiples of the

78 FR 68833 - Combined Notice of Filings #1

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-15

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission Combined Notice of Filings 1 Take notice... Wallingford--CONVEX Services CL&P Electric Rate Schedule FERC No. 583 to be effective 1/1/2014. Filed Date: 11... Company submits CMEEC--CONVEX Services First Revised Rate Schedule FERC No. 576 to be effective 1/1/2014...

10 CFR 2.1322 - Participation and schedule for submissions in an oral hearing.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false Participation and schedule for submissions in an oral hearing. 2.1322 Section 2.1322 Energy NUCLEAR REGULATORY COMMISSION RULES OF PRACTICE FOR DOMESTIC LICENSING PROCEEDINGS AND ISSUANCE OF ORDERS Procedures for Hearings on License Transfer Applications § 2...

10 CFR 2.1322 - Participation and schedule for submissions in an oral hearing.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 1 2011-01-01 2011-01-01 false Participation and schedule for submissions in an oral hearing. 2.1322 Section 2.1322 Energy NUCLEAR REGULATORY COMMISSION RULES OF PRACTICE FOR DOMESTIC LICENSING PROCEEDINGS AND ISSUANCE OF ORDERS Procedures for Hearings on License Transfer Applications § 2...

78 FR 72673 - Zero Rate Reactive Power Rate Schedules; Notice of Staff Workshop

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-03

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. AD14-1-000] Zero Rate Reactive Power Rate Schedules; Notice of Staff Workshop This notice establishes the location and date for... located at: https://www.ferc.gov/whats-new/registration/zero-rate-12-11-13-form.asp . The workshop will...

Daytime bright light exposure, metabolism, and individual differences in wake and sleep energy expenditure during circadian entrainment and misalignment

PubMed Central

Melanson, Edward L.; Ritchie, Hannah K.; Dear, Tristan B.; Catenacci, Victoria; Shea, Karen; Connick, Elizabeth; Moehlman, Thomas M.; Stothard, Ellen R.; Higgins, Janine; McHill, Andrew W.; Wright, Kenneth P.

2018-01-01

Daytime light exposure has been reported to impact or have no influence on energy metabolism in humans. Further, whether inter-individual differences in wake, sleep, 24 h energy expenditure, and RQ during circadian entrainment and circadian misalignment are stable across repeated 24 h assessments is largely unknown. We present data from two studies: Study 1 of 15 participants (7 females) exposed to three light exposure conditions: continuous typical room ~100 lx warm white light, continuous ~750 lx warm white light, and alternating hourly ~750 lx warm white and blue-enriched white light on three separate days in a randomized order; and Study 2 of 14 participants (8 females) during circadian misalignment induced by a simulated night shift protocol. Participants were healthy, free of medical disorders, medications, and illicit drugs. Participants maintained a consistent 8 h per night sleep schedule for one week as an outpatient prior to the study verified by wrist actigraphy, sleep diaries, and call-ins to a time stamped recorder. Participants consumed an outpatient energy balance research diet for three days prior to the study. The inpatient protocol for both studies consisted of an initial sleep disorder screening night. For study 1, this was followed by three standard days with 16 h scheduled wakefulness and 8 h scheduled nighttime sleep. For Study 2, it was followed by 16 h scheduled wake and 8 h scheduled sleep at habitual bedtime followed by three night shifts with 8 h scheduled daytime sleep. Energy expenditure was measured using whole-room indirect calorimetry. Constant posture bedrest conditions were maintained to control for energy expenditure associated with activity and the baseline energy balance diet was continued with the same exact meals across days to control for thermic effects of food. No significant impact of light exposure was observed on metabolic outcomes in response to daytime light exposure. Inter-individual variability in energy expenditure was systematic and ranged from substantial to almost perfect consistency during both nighttime sleep and circadian misalignment. Findings show robust and stable trait-like individual differences in whole body 24 h, waking, and sleep energy expenditure, 24 h respiratory quotient—an index of a fat and carbohydrate oxidation—during repeated assessments under entrained conditions, and also in 24 h and sleep energy expenditure during repeated days of circadian misalignment. PMID:29876528

Daytime bright light exposure, metabolism, and individual differences in wake and sleep energy expenditure during circadian entrainment and misalignment.

PubMed

Melanson, Edward L; Ritchie, Hannah K; Dear, Tristan B; Catenacci, Victoria; Shea, Karen; Connick, Elizabeth; Moehlman, Thomas M; Stothard, Ellen R; Higgins, Janine; McHill, Andrew W; Wright, Kenneth P

2018-01-01

Daytime light exposure has been reported to impact or have no influence on energy metabolism in humans. Further, whether inter-individual differences in wake, sleep, 24 h energy expenditure, and RQ during circadian entrainment and circadian misalignment are stable across repeated 24 h assessments is largely unknown. We present data from two studies: Study 1 of 15 participants (7 females) exposed to three light exposure conditions: continuous typical room ~100 lx warm white light, continuous ~750 lx warm white light, and alternating hourly ~750 lx warm white and blue-enriched white light on three separate days in a randomized order; and Study 2 of 14 participants (8 females) during circadian misalignment induced by a simulated night shift protocol. Participants were healthy, free of medical disorders, medications, and illicit drugs. Participants maintained a consistent 8 h per night sleep schedule for one week as an outpatient prior to the study verified by wrist actigraphy, sleep diaries, and call-ins to a time stamped recorder. Participants consumed an outpatient energy balance research diet for three days prior to the study. The inpatient protocol for both studies consisted of an initial sleep disorder screening night. For study 1, this was followed by three standard days with 16 h scheduled wakefulness and 8 h scheduled nighttime sleep. For Study 2, it was followed by 16 h scheduled wake and 8 h scheduled sleep at habitual bedtime followed by three night shifts with 8 h scheduled daytime sleep. Energy expenditure was measured using whole-room indirect calorimetry. Constant posture bedrest conditions were maintained to control for energy expenditure associated with activity and the baseline energy balance diet was continued with the same exact meals across days to control for thermic effects of food. No significant impact of light exposure was observed on metabolic outcomes in response to daytime light exposure. Inter-individual variability in energy expenditure was systematic and ranged from substantial to almost perfect consistency during both nighttime sleep and circadian misalignment. Findings show robust and stable trait-like individual differences in whole body 24 h, waking, and sleep energy expenditure, 24 h respiratory quotient-an index of a fat and carbohydrate oxidation-during repeated assessments under entrained conditions, and also in 24 h and sleep energy expenditure during repeated days of circadian misalignment.

Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms.

PubMed

Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

2014-01-01

With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies.

Power management of remote microgrids considering battery lifetime

NASA Astrophysics Data System (ADS)

Chalise, Santosh

Currently, 20% (1.3 billion) of the world's population still lacks access to electricity and many live in remote areas where connection to the grid is not economical or practical. Remote microgrids could be the solution to the problem because they are designed to provide power for small communities within clearly defined electrical boundaries. Reducing the cost of electricity for remote microgrids can help to increase access to electricity for populations in remote areas and developing countries. The integration of renewable energy and batteries in diesel based microgrids has shown to be effective in reducing fuel consumption. However, the operational cost remains high due to the low lifetime of batteries, which are heavily used to improve the system's efficiency. In microgrid operation, a battery can act as a source to augment the generator or a load to ensure full load operation. In addition, a battery increases the utilization of PV by storing extra energy. However, the battery has a limited energy throughput. Therefore, it is required to provide balance between fuel consumption and battery lifetime throughput in order to lower the cost of operation. This work presents a two-layer power management system for remote microgrids. First layer is day ahead scheduling, where power set points of dispatchable resources were calculated. Second layer is real time dispatch, where schedule set points from the first layer are accepted and resources are dispatched accordingly. A novel scheduling algorithm is proposed for a dispatch layer, which considers the battery lifetime in optimization and is expected to reduce the operational cost of the microgrid. This method is based on a goal programming approach which has the fuel and the battery wear cost as two objectives to achieve. The effectiveness of this method was evaluated through a simulation study of a PV-diesel hybrid microgrid using deterministic and stochastic approach of optimization.

How to Compute a Slot Marker - Calculation of Controller Managed Spacing Tools for Efficient Descents with Precision Scheduling

NASA Technical Reports Server (NTRS)

Prevot, Thomas

2012-01-01

This paper describes the underlying principles and algorithms for computing the primary controller managed spacing (CMS) tools developed at NASA for precisely spacing aircraft along efficient descent paths. The trajectory-based CMS tools include slot markers, delay indications and speed advisories. These tools are one of three core NASA technologies integrated in NASAs ATM technology demonstration-1 (ATD-1) that will operationally demonstrate the feasibility of fuel-efficient, high throughput arrival operations using Automatic Dependent Surveillance Broadcast (ADS-B) and ground-based and airborne NASA technologies for precision scheduling and spacing.

Multi-core processing and scheduling performance in CMS

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

Hernandez, J. M.; Evans, D.; Foulkes, S.

2012-01-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resultingmore » in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.« less

Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks.

PubMed

Zhong, Ping; Li, Ya-Ting; Liu, Wei-Rong; Duan, Gui-Hua; Chen, Ying-Wen; Xiong, Neal

2017-08-16

In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs' movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs.

Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks

PubMed Central

Li, Ya-Ting; Liu, Wei-Rong; Duan, Gui-Hua; Chen, Ying-Wen

2017-01-01

In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs’ movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs. PMID:28813029

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.

Operations mission planner beyond the baseline

NASA Technical Reports Server (NTRS)

Biefeld, Eric; Cooper, Lynne

1991-01-01

The scheduling of Space Station Freedom must satisfy four major requirements. It must ensure efficient housekeeping operations, maximize the collection of science, respond to changes in tasking and available resources, and accommodate the above changes in a manner that minimizes disruption of the ongoing operations of the station. While meeting these requirements the scheduler must cope with the complexity, scope, and flexibility of SSF operations. This requires the scheduler to deal with an astronomical number of possible schedules. The Operations Mission Planner (OMP) is centered around minimally disruptive replanning and the use of heuristics limit search in scheduling. OMP has already shown several artificial intelligence based scheduling techniques such as Interleaved Iterative Refinement and Bottleneck Identification using Process Chronologies.

Production scheduling with ant colony optimization

NASA Astrophysics Data System (ADS)

Chernigovskiy, A. S.; Kapulin, D. V.; Noskova, E. E.; Yamskikh, T. N.; Tsarev, R. Yu

2017-10-01

The optimum solution of the production scheduling problem for manufacturing processes at an enterprise is crucial as it allows one to obtain the required amount of production within a specified time frame. Optimum production schedule can be found using a variety of optimization algorithms or scheduling algorithms. Ant colony optimization is one of well-known techniques to solve the global multi-objective optimization problem. In the article, the authors present a solution of the production scheduling problem by means of an ant colony optimization algorithm. A case study of the algorithm efficiency estimated against some others production scheduling algorithms is presented. Advantages of the ant colony optimization algorithm and its beneficial effect on the manufacturing process are provided.

Life cycle environmental implications of residential swimming pools.

PubMed

Forrest, Nigel; Williams, Eric

2010-07-15

Ownership of private swimming pools in the U.S. grew 2 to 4% per annum from 1997 to 2007. The environmental implications of pool ownership are analyzed by hybrid life cycle assessment (LCA) for nine U.S. cities. An operational model is constructed estimating consumption of chemicals, water, and energy for a typical residential pool. The model incorporates geographical climatic variations and upstream water and energy use from electricity and water supply networks. Results vary considerably by city: a factor of 5-6 for both water and energy use. Water use is driven by aridness and length of the swimming season, while energy use is mainly driven by length of the swimming season. Water and energy impacts of pools are significant, particularly in arid climates. In Phoenix for example pools account for 22% and 13% of a household's electricity and water use, respectively. Measures to reduce water and energy use in pools such as optimizing the pump schedule and covering the pool in winter can realize greater savings than many common household efficiency improvements. Private versus community pools are also compared. Community pools in Phoenix use 60% less swimming pool water and energy per household than subdivisions without community pools.

Comparing Book- and Tablet-Based Picture Activity Schedules: Acquisition and Preference.

PubMed

Giles, Aimee; Markham, Victoria

2017-09-01

Picture activity schedules consist of a sequence of images representing the order of tasks for a person to complete. Although, picture activity schedules have traditionally been presented in a book format, recently picture activity schedules have been evaluated on technological devices such as an iPod™ touch. The present study compared the efficiency of picture activity schedule acquisition on book- and tablet-based modalities. In addition, participant preference for each modality was assessed. Three boys aged below 5 years with a diagnosis of autism participated. Participants were taught to follow the schedules using both modalities. Following mastery of each modality of picture activity schedule, a concurrent-chains preference assessment was conducted to evaluate participant preference for each modality. Differences in acquisition rates across the two modalities were marginal. Preference for book- or tablet-based schedules was idiosyncratic across participants.

Cooperative network clustering and task allocation for heterogeneous small satellite network

NASA Astrophysics Data System (ADS)

Qin, Jing

The research of small satellite has emerged as a hot topic in recent years because of its economical prospects and convenience in launching and design. Due to the size and energy constraints of small satellites, forming a small satellite network(SSN) in which all the satellites cooperate with each other to finish tasks is an efficient and effective way to utilize them. In this dissertation, I designed and evaluated a weight based dominating set clustering algorithm, which efficiently organizes the satellites into stable clusters. The traditional clustering algorithms of large monolithic satellite networks, such as formation flying and satellite swarm, are often limited on automatic formation of clusters. Therefore, a novel Distributed Weight based Dominating Set(DWDS) clustering algorithm is designed to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to form the clusters efficiently and stably. In this algorithm, satellites are separated into different groups according to their spatial characteristics. A minimum dominating set is chosen as the candidate cluster head set based on their weights, which is a weighted combination of residual energy and connection degree. Then the cluster heads admit new neighbors that accept their invitations into the cluster, until the maximum cluster size is reached. Evaluated by the simulation results, in a SSN with 200 to 800 nodes, the algorithm is able to efficiently cluster more than 90% of nodes in 3 seconds. The Deadline Based Resource Balancing (DBRB) task allocation algorithm is designed for efficient task allocations in heterogeneous LEO small satellite networks. In the task allocation process, the dispatcher needs to consider the deadlines of the tasks as well as the residue energy of different resources for best energy utilization. We assume the tasks adopt a Map-Reduce framework, in which a task can consist of multiple subtasks. The DBRB algorithm is deployed on the head node of a cluster. It gathers the status from each cluster member and calculates their Node Importance Factors (NIFs) from the carried resources, residue power and compute capacity. The algorithm calculates the number of concurrent subtasks based on the deadlines, and allocates the subtasks to the nodes according to their NIF values. The simulation results show that when cluster members carry multiple resources, resource are more balanced and rare resources serve longer in DBRB than in the Earliest Deadline First algorithm. We also show that the algorithm performs well in service isolation by serving multiple tasks with different deadlines. Moreover, the average task response time with various cluster size settings is well controlled within deadlines as well. Except non-realtime tasks, small satellites may execute realtime tasks as well. The location-dependent tasks, such as image capturing, data transmission and remote sensing tasks are realtime tasks that are required to be started / finished on specific time. The resource energy balancing algorithm for realtime and non-realtime mixed workload is developed to efficiently schedule the tasks for best system performance. It calculates the residue energy for each resource type and tries to preserve resources and node availability when distributing tasks. Non-realtime tasks can be preempted by realtime tasks to provide better QoS to realtime tasks. I compared the performance of proposed algorithm with a random-priority scheduling algorithm, with only realtime tasks, non-realtime tasks and mixed tasks. It shows the resource energy reservation algorithm outperforms the latter one with both balanced and imbalanced workloads. Although the resource energy balancing task allocation algorithm for mixed workload provides preemption mechanism for realtime tasks, realtime tasks can still fail due to resource exhaustion. For LEO small satellite flies around the earth on stable orbits, the location-dependent realtime tasks can be considered as periodical tasks. Therefore, it is possible to reserve energy for these realtime tasks. The resource energy reservation algorithm preserves energy for the realtime tasks when the execution routine of periodical realtime tasks is known. In order to reserve energy for tasks starting very early in each period that the node does not have enough energy charged, an energy wrapping mechanism is also designed to calculate the residue energy from the previous period. The simulation results show that without energy reservation, realtime task failure rate can reach more than 60% when the workload is highly imbalanced. In contrast, the resource energy reservation produces zero RT task failures and leads to equal or better aggregate system throughput than the non-reservation algorithm. The proposed algorithm also preserves more energy because it avoids task preemption. (Abstract shortened by ProQuest.).

The successful oral and maxillofacial surgery practice.

PubMed

Bell, Colin S

2008-02-01

Oral and maxillofacial surgery has been and will continue to be one of the premiere health care specialties in the United States. Incomes of oral and maxillofacial surgeons are among the highest of any profession in the country. With efficient scheduling, organized business systems, efficient fee schedules, and appropriate use of consultants, oral and maxillofacial surgery can lead to a lifestyle that is relatively stress free, allows a direct route to financial independence, and provides a great public service.

Automated observation scheduling for the VLT

NASA Technical Reports Server (NTRS)

Johnston, Mark D.

1988-01-01

It is becoming increasingly evident that, in order to optimize the observing efficiency of large telescopes, some changes will be required in the way observations are planned and executed. Not all observing programs require the presence of the astronomer at the telescope: for those programs which permit service observing it is possible to better match planned observations to conditions at the telescope. This concept of flexible scheduling has been proposed for the VLT: based on current and predicted environmental and instrumental observations which make the most efficient possible use of valuable time. A similar kind of observation scheduling is already necessary for some space observatories, such as Hubble Space Telescope (HST). Space Telescope Science Institute is presently developing scheduling tools for HST, based on the use of artificial intelligence software development techniques. These tools could be readily adapted for ground-based telescope scheduling since they address many of the same issues. The concept are described on which the HST tools are based, their implementation, and what would be required to adapt them for use with the VLT and other ground-based observatories.

A DAG Scheduling Scheme on Heterogeneous Computing Systems Using Tuple-Based Chemical Reaction Optimization

PubMed Central

Jiang, Yuyi; Shao, Zhiqing; Guo, Yi

2014-01-01

A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems. PMID:25143977

A DAG scheduling scheme on heterogeneous computing systems using tuple-based chemical reaction optimization.

PubMed

Jiang, Yuyi; Shao, Zhiqing; Guo, Yi

2014-01-01

A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems.

Static Schedulers for Embedded Real-Time Systems

DTIC Science & Technology

1989-12-01

Because of the need for having efficient scheduling algorithms in large scale real time systems , software engineers put a lot of effort on developing...provide static schedulers for he Embedded Real Time Systems with single processor using Ada programming language. The independent nonpreemptable...support the Computer Aided Rapid Prototyping for Embedded Real Time Systems so that we determine whether the system, as designed, meets the required

Uplink Packet-Data Scheduling in DS-CDMA Systems

NASA Astrophysics Data System (ADS)

Choi, Young Woo; Kim, Seong-Lyun

In this letter, we consider the uplink packet scheduling for non-real-time data users in a DS-CDMA system. As an effort to jointly optimize throughput and fairness, we formulate a time-span minimization problem incorporating the time-multiplexing of different simultaneous transmission schemes. Based on simple rules, we propose efficient scheduling algorithms and compare them with the optimal solution obtained by linear programming.

Human reliability and plant operating efficiency: Are 12-hour work schedules cause for concern

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

Baker, T.L.

1992-01-01

Since the introduction of 12-h shifts to the US nuclear power industry only 8 yr ago, compressed workweek schedules have proliferated among operations departments at a phenomenal rate. Many plants that continue to use 8-h shifts during normal operations routinely change to scheduled 12-h shifts during refueling or maintenance outages. The most critical issue in the use of extended work shifts is whether alertness, physical stamina, or mental performance are compromised to the point of reducing safety or efficiency of nuclear power plant operation. Laboratory and field research sponsored by the National Institute of Occupational Safety and Health suggests thatmore » alertness, measured by self-ratings, and mental performance, measured by computer-based performance tests, are impaired on 12-h shifts compared with 8-h shifts. In contrast to these findings, plant operating efficiency and operator performance have been rated as improved in two field studies conducted in operating nuclear power plants (Fast Flux Test Facility, Washington and Ontario Hydro, Canada). A recent Electric Power Research Institute review of nuclear industry experience with 12-h shifts also suggests an overwhelmingly positive rating of 12-h schedules from both control room operators and management.« less

Pruning-Based, Energy-Optimal, Deterministic I/O Device Scheduling for Hard Real-Time Systems

DTIC Science & Technology

2005-02-01

However, DPM via I/O device scheduling for hard real - time systems has received relatively little attention. In this paper,we present an offline I/O...polynomial time. We present experimental results to show that EDS and MDO reduce the energy consumption of I/O devices significantly for hard real - time systems .

18 CFR 154.204 - Changes in rate schedules, forms of service agreements, or the general terms and conditions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Changes in rate... Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER NATURAL GAS ACT RATE SCHEDULES AND TARIFFS Procedures for Changing Tariffs § 154.204 Changes...

18 CFR 154.204 - Changes in rate schedules, forms of service agreements, or the general terms and conditions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Changes in rate... Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER NATURAL GAS ACT RATE SCHEDULES AND TARIFFS Procedures for Changing Tariffs § 154.204 Changes...

18 CFR 154.204 - Changes in rate schedules, forms of service agreements, or the general terms and conditions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Changes in rate... Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER NATURAL GAS ACT RATE SCHEDULES AND TARIFFS Procedures for Changing Tariffs § 154.204 Changes...

18 CFR 154.204 - Changes in rate schedules, forms of service agreements, or the general terms and conditions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Changes in rate... Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER NATURAL GAS ACT RATE SCHEDULES AND TARIFFS Procedures for Changing Tariffs § 154.204 Changes...

18 CFR 154.204 - Changes in rate schedules, forms of service agreements, or the general terms and conditions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Changes in rate... Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER NATURAL GAS ACT RATE SCHEDULES AND TARIFFS Procedures for Changing Tariffs § 154.204 Changes...

77 FR 55202 - Oliver Hydro LLC; Notice of Application Accepted for Filing and Soliciting Motions To Intervene...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-07

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Project No. 13005-003] Oliver Hydro LLC... filed: December 14, 2011. d. Applicant: Oliver Hydro LLC. e. Name of Project: William Bacon Oliver Lock... according to the following Hydro Licensing Schedule. Revisions to the schedule will be made as appropriate...

10 CFR 2.1321 - Participation and schedule for submission in a hearing consisting of written comments.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 1 2011-01-01 2011-01-01 false Participation and schedule for submission in a hearing consisting of written comments. 2.1321 Section 2.1321 Energy NUCLEAR REGULATORY COMMISSION RULES OF PRACTICE FOR DOMESTIC LICENSING PROCEEDINGS AND ISSUANCE OF ORDERS Procedures for Hearings on License Transfer...

10 CFR 2.1321 - Participation and schedule for submission in a hearing consisting of written comments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false Participation and schedule for submission in a hearing consisting of written comments. 2.1321 Section 2.1321 Energy NUCLEAR REGULATORY COMMISSION RULES OF PRACTICE FOR DOMESTIC LICENSING PROCEEDINGS AND ISSUANCE OF ORDERS Procedures for Hearings on License Transfer...

10 CFR 32.102 - Schedule C-prototype tests for calibration or reference sources containing americium-241 or...

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 1 2011-01-01 2011-01-01 false Schedule C-prototype tests for calibration or reference sources containing americium-241 or radium-226. 32.102 Section 32.102 Energy NUCLEAR REGULATORY COMMISSION SPECIFIC DOMESTIC LICENSES TO MANUFACTURE OR TRANSFER CERTAIN ITEMS CONTAINING BYPRODUCT MATERIAL Generally...

Efficient Double Auction Mechanisms in the Energy Grid with Connected and Islanded Microgrids

NASA Astrophysics Data System (ADS)

Faqiry, Mohammad Nazif

The future energy grid is expected to operate in a decentralized fashion as a network of autonomous microgrids that are coordinated by a Distribution System Operator (DSO), which should allocate energy to them in an efficient manner. Each microgrid operating in either islanded or grid-connected mode may be considered to manage its own resources. This can take place through auctions with individual units of the microgrid as the agents. This research proposes efficient auction mechanisms for the energy grid, with is-landed and connected microgrids. The microgrid level auction is carried out by means of an intermediate agent called an aggregator. The individual consumer and producer units are modeled as selfish agents. With the microgrid in islanded mode, two aggregator-level auction classes are analyzed: (i) price-heterogeneous, and (ii) price homogeneous. Under the price heterogeneity paradigm, this research extends earlier work on the well-known, single-sided Kelly mechanism to double auctions. As in Kelly auctions, the proposed algorithm implements the bidding without using any agent level private infor-mation (i.e. generation capacity and utility functions). The proposed auction is shown to be an efficient mechanism that maximizes the social welfare, i.e. the sum of the utilities of all the agents. Furthermore, the research considers the situation where a subset of agents act as a coalition to redistribute the allocated energy and price using any other specific fairness criterion. The price homogeneous double auction algorithm proposed in this research ad-dresses the problem of price-anticipation, where each agent tries to influence the equilibri-um price of energy by placing strategic bids. As a result of this behavior, the auction's efficiency is lowered. This research proposes a novel approach that is implemented by the aggregator, called virtual bidding, where the efficiency can be asymptotically maximized, even in the presence of price anticipatory bidders. Next, an auction mechanism for the energy grid, with multiple connected mi-crogrids is considered. A globally efficient bi-level auction algorithm is proposed. At the upper-level, the algorithm takes into account physical grid constraints in allocating energy to the microgrids. It is implemented by the DSO as a linear objective quadratic constraint problem that allows price heterogeneity across the aggregators. In parallel, each aggrega-tor implements its own lower-level price homogeneous auction with virtual bidding. The research concludes with a preliminary study on extending the DSO level auc-tion to multi-period day-ahead scheduling. It takes into account storage units and conven-tional generators that are present in the grid by formulating the auction as a mixed inte-ger linear programming problem.

Utilizing GIS to evaluate base schedules in paratransit operations

DOT National Transportation Integrated Search

1999-02-02

With ready access to street file names and inexpensive GIS software, paratransit systems can take advantage of GIS technology to evaluate base schedules on a regular basis in order to maintain system efficiency at consistently high levels. This proje...

Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

NASA Astrophysics Data System (ADS)

Li, Ze

2017-09-01

In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans

NASA Astrophysics Data System (ADS)

Wang, Song; Gupta, Chetan; Mehta, Abhay

There are data streams all around us that can be harnessed for tremendous business and personal advantage. For an enterprise-level stream processing system such as CHAOS [1] (Continuous, Heterogeneous Analytic Over Streams), handling of complex query plans with resource constraints is challenging. While several scheduling strategies exist for stream processing, efficient scheduling of complex DAG query plans is still largely unsolved. In this paper, we propose a novel execution scheme for scheduling complex directed acyclic graph (DAG) query plans with meta-data enriched stream tuples. Our solution, called Virtual Pipelined Chain (or VPipe Chain for short), effectively extends the "Chain" pipelining scheduling approach to complex DAG query plans.

The Traffic Management Advisor

NASA Technical Reports Server (NTRS)

Nedell, William; Erzberger, Heinz; Neuman, Frank

1990-01-01

The traffic management advisor (TMA) is comprised of algorithms, a graphical interface, and interactive tools for controlling the flow of air traffic into the terminal area. The primary algorithm incorporated in it is a real-time scheduler which generates efficient landing sequences and landing times for arrivals within about 200 n.m. from touchdown. A unique feature of the TMA is its graphical interface that allows the traffic manager to modify the computer-generated schedules for specific aircraft while allowing the automatic scheduler to continue generating schedules for all other aircraft. The graphical interface also provides convenient methods for monitoring the traffic flow and changing scheduling parameters during real-time operation.

Wireless Sensor Network Metrics for Real-Time Systems

DTIC Science & Technology

2009-05-20

to compute the probability of end-to-end packet delivery as a function of latency, the expected radio energy consumption on the nodes from relaying... schedules for WSNs. Particularly, we focus on the impact scheduling has on path diversity, using short repeating schedules and Greedy Maximal Matching...a greedy algorithm for constructing a mesh routing topology. Finally, we study the implications of using distributed scheduling schemes to generate

Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms

PubMed Central

Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

2017-01-01

With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies. PMID:29399237

Space communications scheduler: A rule-based approach to adaptive deadline scheduling

NASA Technical Reports Server (NTRS)

Straguzzi, Nicholas

1990-01-01

Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.

A Novel Particle Swarm Optimization Approach for Grid Job Scheduling

NASA Astrophysics Data System (ADS)

Izakian, Hesam; Tork Ladani, Behrouz; Zamanifar, Kamran; Abraham, Ajith

This paper represents a Particle Swarm Optimization (PSO) algorithm, for grid job scheduling. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. In this paper we used a PSO approach for grid job scheduling. The scheduler aims at minimizing makespan and flowtime simultaneously. Experimental studies show that the proposed novel approach is more efficient than the PSO approach reported in the literature.

Seamless transitions from early prototypes to mature operational software - A technology that enables the process for planning and scheduling applications

NASA Technical Reports Server (NTRS)

Hornstein, Rhoda S.; Wunderlich, Dana A.; Willoughby, John K.

1992-01-01

New and innovative software technology is presented that provides a cost effective bridge for smoothly transitioning prototype software, in the field of planning and scheduling, into an operational environment. Specifically, this technology mixes the flexibility and human design efficiency of dynamic data typing with the rigor and run-time efficiencies of static data typing. This new technology provides a very valuable tool for conducting the extensive, up-front system prototyping that leads to specifying the correct system and producing a reliable, efficient version that will be operationally effective and will be accepted by the intended users.

Maximizing Energy Savings Reliability in BC Hydro Industrial Demand-side Management Programs: An Assessment of Performance Incentive Models

NASA Astrophysics Data System (ADS)

Gosman, Nathaniel

For energy utilities faced with expanded jurisdictional energy efficiency requirements and pursuing demand-side management (DSM) incentive programs in the large industrial sector, performance incentive programs can be an effective means to maximize the reliability of planned energy savings. Performance incentive programs balance the objectives of high participation rates with persistent energy savings by: (1) providing financial incentives and resources to minimize constraints to investment in energy efficiency, and (2) requiring that incentive payments be dependent on measured energy savings over time. As BC Hydro increases its DSM initiatives to meet the Clean Energy Act objective to reduce at least 66 per cent of new electricity demand with DSM by 2020, the utility is faced with a higher level of DSM risk, or uncertainties that impact the costeffective acquisition of planned energy savings. For industrial DSM incentive programs, DSM risk can be broken down into project development and project performance risks. Development risk represents the project ramp-up phase and is the risk that planned energy savings do not materialize due to low customer response to program incentives. Performance risk represents the operational phase and is the risk that planned energy savings do not persist over the effective measure life. DSM project development and performance risks are, in turn, a result of industrial economic, technological and organizational conditions, or DSM risk factors. In the BC large industrial sector, and characteristic of large industrial sectors in general, these DSM risk factors include: (1) capital constraints to investment in energy efficiency, (2) commodity price volatility, (3) limited internal staffing resources to deploy towards energy efficiency, (4) variable load, process-based energy saving potential, and (5) a lack of organizational awareness of an operation's energy efficiency over time (energy performance). This research assessed the capacity of alternative performance incentive program models to manage DSM risk in BC. Three performance incentive program models were assessed and compared to BC Hydro's current large industrial DSM incentive program, Power Smart Partners -- Transmission Project Incentives, itself a performance incentive-based program. Together, the selected program models represent a continuum of program design and implementation in terms of the schedule and level of incentives provided, the duration and rigour of measurement and verification (M&V), energy efficiency measures targeted and involvement of the private sector. A multi criteria assessment framework was developed to rank the capacity of each program model to manage BC large industrial DSM risk factors. DSM risk management rankings were then compared to program costeffectiveness, targeted energy savings potential in BC and survey results from BC industrial firms on the program models. The findings indicate that the reliability of DSM energy savings in the BC large industrial sector can be maximized through performance incentive program models that: (1) offer incentives jointly for capital and low-cost operations and maintenance (O&M) measures, (2) allow flexible lead times for project development, (3) utilize rigorous M&V methods capable of measuring variable load, process-based energy savings, (4) use moderate contract lengths that align with effective measure life, and (5) integrate energy management software tools capable of providing energy performance feedback to customers to maximize the persistence of energy savings. While this study focuses exclusively on the BC large industrial sector, the findings of this research have applicability to all energy utilities serving large, energy intensive industrial sectors.

Astronaut Office Scheduling System Software

NASA Technical Reports Server (NTRS)

Brown, Estevancio

2010-01-01

AOSS is a highly efficient scheduling application that uses various tools to schedule astronauts weekly appointment information. This program represents an integration of many technologies into a single application to facilitate schedule sharing and management. It is a Windows-based application developed in Visual Basic. Because the NASA standard office automation load environment is Microsoft-based, Visual Basic provides AO SS developers with the ability to interact with Windows collaboration components by accessing objects models from applications like Outlook and Excel. This also gives developers the ability to create newly customizable components that perform specialized tasks pertaining to scheduling reporting inside the application. With this capability, AOSS can perform various asynchronous tasks, such as gathering/ sending/ managing astronauts schedule information directly to their Outlook calendars at any time.

Scheduling multicore workload on shared multipurpose clusters

NASA Astrophysics Data System (ADS)

Templon, J. A.; Acosta-Silva, C.; Flix Molina, J.; Forti, A. C.; Pérez-Calero Yzquierdo, A.; Starink, R.

2015-12-01

With the advent of workloads containing explicit requests for multiple cores in a single grid job, grid sites faced a new set of challenges in workload scheduling. The most common batch schedulers deployed at HEP computing sites do a poor job at multicore scheduling when using only the native capabilities of those schedulers. This paper describes how efficient multicore scheduling was achieved at the sites the authors represent, by implementing dynamically-sized multicore partitions via a minimalistic addition to the Torque/Maui batch system already in use at those sites. The paper further includes example results from use of the system in production, as well as measurements on the dependence of performance (especially the ramp-up in throughput for multicore jobs) on node size and job size.

Optimal Scheduling of Time-Shiftable Electric Loads in Expeditionary Power Grids

DTIC Science & Technology

2015-09-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDITIONARY POWER GRIDS by John G...to 09-25-2015 4. TITLE AND SUBTITLE OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDI- TIONARY POWER GRIDS 5. FUNDING NUMBERS 6. AUTHOR(S...eliminate unmanaged peak demand, reduce generator peak-to-average power ratios, and facilitate a persistent shift to higher fuel efficiency. Using

Application of the Software as a Service Model to the Control of Complex Building Systems

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

Stadler, Michael; Donadee, Jonathan; Marnay, Chris

2011-03-17

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.« less

Application of the Software as a Service Model to the Control of Complex Building Systems

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

Stadler, Michael; Donadee, Jon; Marnay, Chris

2011-03-18

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.« less

A bicriteria heuristic for an elective surgery scheduling problem.

PubMed

Marques, Inês; Captivo, M Eugénia; Vaz Pato, Margarida

2015-09-01

Resource rationalization and reduction of waiting lists for surgery are two main guidelines for hospital units outlined in the Portuguese National Health Plan. This work is dedicated to an elective surgery scheduling problem arising in a Lisbon public hospital. In order to increase the surgical suite's efficiency and to reduce the waiting lists for surgery, two objectives are considered: maximize surgical suite occupation and maximize the number of surgeries scheduled. This elective surgery scheduling problem consists of assigning an intervention date, an operating room and a starting time for elective surgeries selected from the hospital waiting list. Accordingly, a bicriteria surgery scheduling problem arising in the hospital under study is presented. To search for efficient solutions of the bicriteria optimization problem, the minimization of a weighted Chebyshev distance to a reference point is used. A constructive and improvement heuristic procedure specially designed to address the objectives of the problem is developed and results of computational experiments obtained with empirical data from the hospital are presented. This study shows that by using the bicriteria approach presented here it is possible to build surgical plans with very good performance levels. This method can be used within an interactive approach with the decision maker. It can also be easily adapted to other hospitals with similar scheduling conditions.

Algorithm of composing the schedule of construction and installation works

NASA Astrophysics Data System (ADS)

Nehaj, Rustam; Molotkov, Georgij; Rudchenko, Ivan; Grinev, Anatolij; Sekisov, Aleksandr

2017-10-01

An algorithm for scheduling works is developed, in which the priority of the work corresponds to the total weight of the subordinate works, the vertices of the graph, and it is proved that for graphs of the tree type the algorithm is optimal. An algorithm is synthesized to reduce the search for solutions when drawing up schedules of construction and installation works, allocating a subset with the optimal solution of the problem of the minimum power, which is determined by the structure of its initial data and numerical values. An algorithm for scheduling construction and installation work is developed, taking into account the schedule for the movement of brigades, which is characterized by the possibility to efficiently calculate the values of minimizing the time of work performance by the parameters of organizational and technological reliability through the use of the branch and boundary method. The program of the computational algorithm was compiled in the MatLAB-2008 program. For the initial data of the matrix, random numbers were taken, uniformly distributed in the range from 1 to 100. It takes 0.5; 2.5; 7.5; 27 minutes to solve the problem. Thus, the proposed method for estimating the lower boundary of the solution is sufficiently accurate and allows efficient solution of the minimax task of scheduling construction and installation works.

Auction-based distributed efficient economic operations of microgrid systems

NASA Astrophysics Data System (ADS)

Zou, Suli; Ma, Zhongjing; Liu, Xiangdong

2014-12-01

This paper studies the economic operations of the microgrid in a distributed way such that the operational schedule of each of the units, like generators, load units, storage units, etc., in a microgrid system, is implemented by autonomous agents. We apply and generalise the progressive second price (PSP) auction mechanism which was proposed by Lazar and Semret to efficiently allocate the divisible network resources. Considering the economic operation for the microgrid systems, the generators play as sellers to supply energy and the load units play as the buyers to consume energy, while a storage unit, like battery, super capacitor, etc., may transit between buyer and seller, such that it is a buyer when it charges and becomes a seller when it discharges. Furthermore in a connected mode, each individual unit competes against not only the other individual units in the microgrid but also the exogenous main grid possessing fixed electricity price and infinite trade capacity; that is to say, the auctioneer assigns the electricity among all individual units and the main grid with respect to the submitted bid strategies of all individual units in the microgrid in an economic way. Due to these distinct characteristics, the underlying auction games are distinct from those studied in the literature. We show that under mild conditions, the efficient economic operation strategy is a Nash equilibrium (NE) for the PSP auction games, and propose a distributed algorithm under which the system can converge to an NE. We also show that the performance of worst NE can be bounded with respect to the system parameters, say the energy trading price with the main grid, and based upon that, the implemented NE is unique and efficient under some conditions.

Energy-efficient boarder node medium access control protocol for wireless sensor networks.

PubMed

Razaque, Abdul; Elleithy, Khaled M

2014-03-12

This paper introduces the design, implementation, and performance analysis of the scalable and mobility-aware hybrid protocol named boarder node medium access control (BN-MAC) for wireless sensor networks (WSNs), which leverages the characteristics of scheduled and contention-based MAC protocols. Like contention-based MAC protocols, BN-MAC achieves high channel utilization, network adaptability under heavy traffic and mobility, and low latency and overhead. Like schedule-based MAC protocols, BN-MAC reduces idle listening time, emissions, and collision handling at low cost at one-hop neighbor nodes and achieves high channel utilization under heavy network loads. BN-MAC is particularly designed for region-wise WSNs. Each region is controlled by a boarder node (BN), which is of paramount importance. The BN coordinates with the remaining nodes within and beyond the region. Unlike other hybrid MAC protocols, BN-MAC incorporates three promising models that further reduce the energy consumption, idle listening time, overhearing, and congestion to improve the throughput and reduce the latency. One of the models used with BN-MAC is automatic active and sleep (AAS), which reduces the ideal listening time. When nodes finish their monitoring process, AAS lets them automatically go into the sleep state to avoid the idle listening state. Another model used in BN-MAC is the intelligent decision-making (IDM) model, which helps the nodes sense the nature of the environment. Based on the nature of the environment, the nodes decide whether to use the active or passive mode. This decision power of the nodes further reduces energy consumption because the nodes turn off the radio of the transceiver in the passive mode. The third model is the least-distance smart neighboring search (LDSNS), which determines the shortest efficient path to the one-hop neighbor and also provides cross-layering support to handle the mobility of the nodes. The BN-MAC also incorporates a semi-synchronous feature with a low duty cycle, which is advantageous for reducing the latency and energy consumption for several WSN application areas to improve the throughput. BN-MAC uses a unique window slot size to enhance the contention resolution issue for improved throughput. BN-MAC also prefers to communicate within a one-hop destination using Anycast, which maintains load balancing to maintain network reliability. BN-MAC is introduced with the goal of supporting four major application areas: monitoring and behavioral areas, controlling natural disasters, human-centric applications, and tracking mobility and static home automation devices from remote places. These application areas require a congestion-free mobility-supported MAC protocol to guarantee reliable data delivery. BN-MAC was evaluated using network simulator-2 (ns2) and compared with other hybrid MAC protocols, such as Zebra medium access control (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, adaptive duty cycle SMAC (ADC-SMAC), and low-power real-time medium access control (LPR-MAC). The simulation results indicate that BN-MAC is a robust and energy-efficient protocol that outperforms other hybrid MAC protocols in the context of quality of service (QoS) parameters, such as energy consumption, latency, throughput, channel access time, successful delivery rate, coverage efficiency, and average duty cycle.

Energy-Efficient Boarder Node Medium Access Control Protocol for Wireless Sensor Networks

PubMed Central

Razaque, Abdul; Elleithy, Khaled M.

2014-01-01

This paper introduces the design, implementation, and performance analysis of the scalable and mobility-aware hybrid protocol named boarder node medium access control (BN-MAC) for wireless sensor networks (WSNs), which leverages the characteristics of scheduled and contention-based MAC protocols. Like contention-based MAC protocols, BN-MAC achieves high channel utilization, network adaptability under heavy traffic and mobility, and low latency and overhead. Like schedule-based MAC protocols, BN-MAC reduces idle listening time, emissions, and collision handling at low cost at one-hop neighbor nodes and achieves high channel utilization under heavy network loads. BN-MAC is particularly designed for region-wise WSNs. Each region is controlled by a boarder node (BN), which is of paramount importance. The BN coordinates with the remaining nodes within and beyond the region. Unlike other hybrid MAC protocols, BN-MAC incorporates three promising models that further reduce the energy consumption, idle listening time, overhearing, and congestion to improve the throughput and reduce the latency. One of the models used with BN-MAC is automatic active and sleep (AAS), which reduces the ideal listening time. When nodes finish their monitoring process, AAS lets them automatically go into the sleep state to avoid the idle listening state. Another model used in BN-MAC is the intelligent decision-making (IDM) model, which helps the nodes sense the nature of the environment. Based on the nature of the environment, the nodes decide whether to use the active or passive mode. This decision power of the nodes further reduces energy consumption because the nodes turn off the radio of the transceiver in the passive mode. The third model is the least-distance smart neighboring search (LDSNS), which determines the shortest efficient path to the one-hop neighbor and also provides cross-layering support to handle the mobility of the nodes. The BN-MAC also incorporates a semi-synchronous feature with a low duty cycle, which is advantageous for reducing the latency and energy consumption for several WSN application areas to improve the throughput. BN-MAC uses a unique window slot size to enhance the contention resolution issue for improved throughput. BN-MAC also prefers to communicate within a one-hop destination using Anycast, which maintains load balancing to maintain network reliability. BN-MAC is introduced with the goal of supporting four major application areas: monitoring and behavioral areas, controlling natural disasters, human-centric applications, and tracking mobility and static home automation devices from remote places. These application areas require a congestion-free mobility-supported MAC protocol to guarantee reliable data delivery. BN-MAC was evaluated using network simulator-2 (ns2) and compared with other hybrid MAC protocols, such as Zebra medium access control (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, adaptive duty cycle SMAC (ADC-SMAC), and low-power real-time medium access control (LPR-MAC). The simulation results indicate that BN-MAC is a robust and energy-efficient protocol that outperforms other hybrid MAC protocols in the context of quality of service (QoS) parameters, such as energy consumption, latency, throughput, channel access time, successful delivery rate, coverage efficiency, and average duty cycle. PMID:24625737

Manufacturing Technology Support (MATES). Delivery Order 0002: Business Practices Assessment (BPA) Development

DTIC Science & Technology

2008-03-01

order fulfillment visibility, Kanban deployment, inventory count can be made visually, machines and tool labeling, costs, preventive maintenance...order fulfillment, computer scheduling versus Kanban , pull versus push systems, flow time efficiencies, back room costs of scheduling, MRP costs

18 CFR 375.307 - Delegations to the Director of the Office of Energy Market Regulation.

Code of Federal Regulations, 2010 CFR

2010-04-01

.... (i) Accept for filing all uncontested tariffs or rate schedules and uncontested tariff or rate... Commission, if the filings comply with the terms of the waivers; (ii) Reject a tariff or rate schedule filing... section 1275(b) of the Energy Policy Act of 2005 and/or the Federal Power Act to allocate service company...

Energy management system optimization for on-site facility staff - a case history of the New York State Office of Mental Health

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

Bagdon, M.J.; Martin, P.J.

1997-06-01

In 1994, Novus Engineering and EME Group began a project for the New York State Office of Mental Health (OMH) to maximize the use and benefit of energy management systems (EMS) installed at various large psychiatric hospitals throughout New York State. The project, which was funded and managed by the Dormitory Authority of the State of New York (DASNY), had three major objectives: (1) Maximize Energy Savings - Novus staff quickly learned that EMS systems as set up by contractors are far from optimal for generating energy savings. This part of the program revealed numerous opportunities for increased energy savings,more » such as: fine tuning proportional/integral/derivative (PID) loops to eliminate valve and damper hunting; adjusting temperature reset schedules to reduce energy consumption and provide more uniform temperature conditions throughout the facilities; and modifying equipment schedules. (2) Develop Monitoring Protocols - Large EMS systems are so complex that they require a systematic approach to daily, monthly and seasonal monitoring of building system conditions in order to locate system problems before they turn into trouble calls or equipment failures. In order to assist local facility staff in their monitoring efforts, Novus prepared user-friendly handbooks on each EMS. These included monitoring protocols tailored to each facility. (3) Provide Staff Training - When a new EMS is installed at a facility, it is frequently the maintenance staffs first exposure to a complex computerized system. Without proper training in what to look for, staff use of the EMS is generally very limited. With proper training, staff can be taught to take a pro-active approach to identify and solve problems before they get out of hand. The staff then realize that the EMS is a powerful preventative maintenance tool that can be used to make their work more effective and efficient. Case histories are presented.« less

18 CFR 154.313 - Schedules for minor rate changes.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Schedules for minor rate changes. 154.313 Section 154.313 Conservation of Power and Water Resources FEDERAL ENERGY... Material To Be Filed With Changes § 154.313 Schedules for minor rate changes. (a) A change in a rate or...

18 CFR 154.313 - Schedules for minor rate changes.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Schedules for minor rate changes. 154.313 Section 154.313 Conservation of Power and Water Resources FEDERAL ENERGY... Material To Be Filed With Changes § 154.313 Schedules for minor rate changes. (a) A change in a rate or...

18 CFR 154.313 - Schedules for minor rate changes.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Schedules for minor rate changes. 154.313 Section 154.313 Conservation of Power and Water Resources FEDERAL ENERGY... Material To Be Filed With Changes § 154.313 Schedules for minor rate changes. (a) A change in a rate or...

18 CFR 154.313 - Schedules for minor rate changes.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Schedules for minor rate changes. 154.313 Section 154.313 Conservation of Power and Water Resources FEDERAL ENERGY... Material To Be Filed With Changes § 154.313 Schedules for minor rate changes. (a) A change in a rate or...

18 CFR 154.313 - Schedules for minor rate changes.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Schedules for minor rate changes. 154.313 Section 154.313 Conservation of Power and Water Resources FEDERAL ENERGY... Material To Be Filed With Changes § 154.313 Schedules for minor rate changes. (a) A change in a rate or...

Detailed Calibration of SphinX instrument at the Palermo XACT facility of INAF-OAPA

NASA Astrophysics Data System (ADS)

Szymon, Gburek; Collura, Alfonso; Barbera, Marco; Reale, Fabio; Sylwester, Janusz; Kowalinski, Miroslaw; Bakala, Jaroslaw; Kordylewski, Zbigniew; Plocieniak, Stefan; Podgorski, Piotr; Trzebinski, Witold; Varisco, Salvatore

The Solar photometer in X-rays (SphinX) experiment is scheduled for launch late summer 2008 on-board the Russian CORONAS-Photon satellite. SphinX will use three silicon PIN diode detectors with selected effective areas in order to record solar spectra in the X-ray energy range 0.3-15 keV with unprecedented temporal and medium energy resolution. High sensitivity and large dynamic range of the SphinX instrument will give for the first time possibility of observing solar soft X-ray variability from the weakest levels, ten times below present thresholds, to the largest X20+ flares. We present the results of the ground X-ray calibrations of the SphinX instrument performed at the X-ray Astronomy Calibration and Testing (XACT) facility of INAF-OAPA. The calibrations were essential for determination of SphinX detector energy resolution and efficiency. We describe the ground tests instrumental set-up, adopted measurement techniques and present results of the calibration data analysis.

Planning and Scheduling for Environmental Sensor Networks

NASA Astrophysics Data System (ADS)

Frank, J. D.

2005-12-01

Environmental Sensor Networks are a new way of monitoring the environment. They comprise autonomous sensor nodes in the environment that record real-time data, which is retrieved, analyzed, integrated with other data sets (e.g. satellite images, GIS, process models) and ultimately lead to scientific discoveries. Sensor networks must operate within time and resource constraints. Sensors have limited onboard memory, energy, computational power, communications windows and communications bandwidth. The value of data will depend on when, where and how it was collected, how detailed the data is, how long it takes to integrate the data, and how important the data was to the original scientific question. Planning and scheduling of sensor networks is necessary for effective, safe operations in the face of these constraints. For example, power bus limitations may preclude sensors from simultaneously collecting data and communicating without damaging the sensor; planners and schedulers can ensure these operations are ordered so that they do not happen simultaneously. Planning and scheduling can also ensure best use of the sensor network to maximize the value of collected science data. For example, if data is best recorded using a particular camera angle but it is costly in time and energy to achieve this, planners and schedulers can search for times when time and energy are available to achieve the optimal camera angle. Planning and scheduling can handle uncertainty in the problem specification; planners can be re-run when new information is made available, or can generate plans that include contingencies. For example, if bad weather may prevent the collection of data, a contingent plan can check lighting conditions and turn off data collection to save resources if lighting is not ideal. Both mobile and immobile sensors can benefit from planning and scheduling. For example, data collection on otherwise passive sensors can be halted to preserve limited power and memory resources and to reduce the costs of communication. Planning and scheduling is generally a heavy consumer of time, memory and energy resources. This means careful thought must be given to how much planning and scheduling should be done on the sensors themselves, and how much to do elsewhere. The difficulty of planning and scheduling is exacerbated when reasoning about uncertainty. More time, memory and energy is needed to solve such problems, leading either to more expensive sensors, or suboptimal plans. For example, scientifically interesting events may happen at random times, making it difficult to ensure that sufficient resources are availanble. Since uncertainty is usually lowest in proximity to the sensors themselves, this argues for planning and scheduling onboard the sensors. However, cost minimization dictates sensors be kept as simple as possible, reducing the amount of planning and scheduling they can do themselves. Furthermore, coordinating each sensor's independent plans can be difficult. In the full presentation, we will critically review the planning and scheduling systems used by previously fielded sensor networks. We do so primarily from the perspective of the computational sciences, with a focus on taming computational complexity when operating sensor networks. The case studies are derived from sensor networks based on UAVs, satellites, and planetary rovers. Planning and scheduling considerations include multi-sensor coordination, optimizing science value, onboard power management, onboard memory, planning movement actions to acquire data, and managing communications.These case studies offer lessons for future designs of environmental sensor networks.

Interruption of scheduled, automatic feeding and reduction of excess energy intake in toddlers.

PubMed

Ciampolini, Mario; Brenna, J Thomas; Giannellini, Valerio; Bini, Stefania

2013-01-01

Childhood obesity due to the consumption of excess calories is a severe problem in developed countries. In a previous investigation on toddlers, hospital laboratory measurements showed an association of food-demand behavior with constant lower blood glucose before meals than for scheduled meals. We hypothesize that maternal scheduling of meals for toddlers results in excess energy intake compared to feeding only on demand (previously "on request"). We tested the cross-sectional null hypothesis of no difference in energy intake between scheduled (automatic) and demanded meals (administered after evaluation) in 24 mother-toddler (21 months old at entry) pairs with chronic, nonspecific diarrhea presenting at a clinic. We tested the same hypothesis in a subset of 14 toddlers by measuring the resting (sleeping) metabolic rate 4 hours after lunch, as well as the total daily energy expenditure (TEE) in 10 toddlers. We trained mothers to recognize meal demands (as in the previous investigation) and to provide food in response, but required no blood glucose measurements before meals. Energy intake was assessed by a 10-day food diary, resting metabolic rate (RMR) by respiratory analyses (indirect calorimetry) in 14 toddlers, and TEE by doubly labeled water in 10 toddlers. Their blood parameters, anthropometry, and number of days with diarrhea were assessed before training and 50 days after training. RMR decreased from 58.6 ± 7.8 to 49.0 ± 9.1 kcal/kg/d (P < 0.001) and TEE decreased from 80.1 ± 6.9 to 67.8 ± 10.0 kcal/kg/d (P < 0.001). Energy intake decreased from 85.7 ± 15.3 to 70.3 ± 15.8 kcal/kg/d (P < 0.001). The height Z-score increased significantly, while weight growth was normal. Toddlers entering the study over the median RMR decreased their RMR significantly more than those below the median RMR (P < 0.01). Scheduled meal suspension induces meal demand frequency to increase. Demanded meals are associated with significantly lower energy intake, RMR, and TEE than scheduled meals. Feeding on demand may be an effective skill in a strategy for reducing excess energy intake in the long term and in regulating body weight in toddlers and children.

Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

NASA Technical Reports Server (NTRS)

Zelinski, Shannon; Windhorst, Robert

2016-01-01

A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

Automated telescope scheduling

NASA Technical Reports Server (NTRS)

Johnston, Mark D.

1988-01-01

With the ever increasing level of automation of astronomical telescopes the benefits and feasibility of automated planning and scheduling are becoming more apparent. Improved efficiency and increased overall telescope utilization are the most obvious goals. Automated scheduling at some level has been done for several satellite observatories, but the requirements on these systems were much less stringent than on modern ground or satellite observatories. The scheduling problem is particularly acute for Hubble Space Telescope: virtually all observations must be planned in excruciating detail weeks to months in advance. Space Telescope Science Institute has recently made significant progress on the scheduling problem by exploiting state-of-the-art artificial intelligence software technology. What is especially interesting is that this effort has already yielded software that is well suited to scheduling groundbased telescopes, including the problem of optimizing the coordinated scheduling of more than one telescope.

Routing and scheduling of hazardous materials shipments: algorithmic approaches to managing spent nuclear fuel transport

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

Cox, R.G.

Much controversy surrounds government regulation of routing and scheduling of Hazardous Materials Transportation (HMT). Increases in operating costs must be balanced against expected benefits from local HMT bans and curfews when promulgating or preempting HMT regulations. Algorithmic approaches for evaluating HMT routing and scheduling regulatory policy are described. A review of current US HMT regulatory policy is presented to provide a context for the analysis. Next, a multiobjective shortest path algorithm to find the set of efficient routes under conflicting objectives is presented. This algorithm generates all efficient routes under any partial ordering in a single pass through the network.more » Also, scheduling algorithms are presented to estimate the travel time delay due to HMT curfews along a route. Algorithms are presented assuming either deterministic or stochastic travel times between curfew cities and also possible rerouting to avoid such cities. These algorithms are applied to the case study of US highway transport of spent nuclear fuel from reactors to permanent repositories. Two data sets were used. One data set included the US Interstate Highway System (IHS) network with reactor locations, possible repository sites, and 150 heavily populated areas (HPAs). The other data set contained estimates of the population residing with 0.5 miles of the IHS and the Eastern US. Curfew delay is dramatically reduced by optimally scheduling departure times unless inter-HPA travel times are highly uncertain. Rerouting shipments to avoid HPAs is a less efficient approach to reducing delay.« less

Smart EV Energy Management System to Support Grid Services

NASA Astrophysics Data System (ADS)

Wang, Bin

Under smart grid scenarios, the advanced sensing and metering technologies have been applied to the legacy power grid to improve the system observability and the real-time situational awareness. Meanwhile, there is increasing amount of distributed energy resources (DERs), such as renewable generations, electric vehicles (EVs) and battery energy storage system (BESS), etc., being integrated into the power system. However, the integration of EVs, which can be modeled as controllable mobile energy devices, brings both challenges and opportunities to the grid planning and energy management, due to the intermittency of renewable generation, uncertainties of EV driver behaviors, etc. This dissertation aims to solve the real-time EV energy management problem in order to improve the overall grid efficiency, reliability and economics, using online and predictive optimization strategies. Most of the previous research on EV energy management strategies and algorithms are based on simplified models with unrealistic assumptions that the EV charging behaviors are perfectly known or following known distributions, such as the arriving time, leaving time and energy consumption values, etc. These approaches fail to obtain the optimal solutions in real-time because of the system uncertainties. Moreover, there is lack of data-driven strategy that performs online and predictive scheduling for EV charging behaviors under microgrid scenarios. Therefore, we develop an online predictive EV scheduling framework, considering uncertainties of renewable generation, building load and EV driver behaviors, etc., based on real-world data. A kernel-based estimator is developed to predict the charging session parameters in real-time with improved estimation accuracy. The efficacy of various optimization strategies that are supported by this framework, including valley-filling, cost reduction, event-based control, etc., has been demonstrated. In addition, the existing simulation-based approaches do not consider a variety of practical concerns of implementing such a smart EV energy management system, including the driver preferences, communication protocols, data models, and customized integration of existing standards to provide grid services. Therefore, this dissertation also solves these issues by designing and implementing a scalable system architecture to capture the user preferences, enable multi-layer communication and control, and finally improve the system reliability and interoperability.

Energy-saving scheme based on downstream packet scheduling in ethernet passive optical networks

NASA Astrophysics Data System (ADS)

Zhang, Lincong; Liu, Yejun; Guo, Lei; Gong, Xiaoxue

2013-03-01

With increasing network sizes, the energy consumption of Passive Optical Networks (PONs) has grown significantly. Therefore, it is important to design effective energy-saving schemes in PONs. Generally, energy-saving schemes have focused on sleeping the low-loaded Optical Network Units (ONUs), which tends to bring large packet delays. Further, the traditional ONU sleep modes are not capable of sleeping the transmitter and receiver independently, though they are not required to transmit or receive packets. Clearly, this approach contributes to wasted energy. Thus, in this paper, we propose an Energy-Saving scheme that is based on downstream Packet Scheduling (ESPS) in Ethernet PON (EPON). First, we design both an algorithm and a rule for downstream packet scheduling at the inter- and intra-ONU levels, respectively, to reduce the downstream packet delay. After that, we propose a hybrid sleep mode that contains not only ONU deep sleep mode but also independent sleep modes for the transmitter and the receiver. This ensures that the energy consumed by the ONUs is minimal. To realize the hybrid sleep mode, a modified GATE control message is designed that involves 10 time points for sleep processes. In ESPS, the 10 time points are calculated according to the allocated bandwidths in both the upstream and the downstream. The simulation results show that ESPS outperforms traditional Upstream Centric Scheduling (UCS) scheme in terms of energy consumption and the average delay for both real-time and non-real-time packets downstream. The simulation results also show that the average energy consumption of each ONU in larger-sized networks is less than that in smaller-sized networks; hence, our ESPS is better suited for larger-sized networks.

A manpower scheduling heuristic for aircraft maintenance application

NASA Astrophysics Data System (ADS)

Sze, San-Nah; Sze, Jeeu-Fong; Chiew, Kang-Leng

2012-09-01

This research studies a manpower scheduling for aircraft maintenance, focusing on in-flight food loading operation. A group of loading teams with flexible shifts is required to deliver and upload packaged meals from the ground kitchen to aircrafts in multiple trips. All aircrafts must be served within predefined time windows. The scheduling process takes into account of various constraints such as meal break allocation, multi-trip traveling and food exposure time limit. Considering the aircrafts movement and predefined maximum working hours for each loading team, the main objective of this study is to form an efficient roster by assigning a minimum number of loading teams to the aircrafts. We proposed an insertion based heuristic to generate the solutions in a short period of time for large instances. This proposed algorithm is implemented in various stages for constructing trips due to the presence of numerous constraints. The robustness and efficiency of the algorithm is demonstrated in computational results. The results show that the insertion heuristic more efficiently outperforms the company's current practice.

An Improved Scheduling Algorithm for Data Transmission in Ultrasonic Phased Arrays with Multi-Group Ultrasonic Sensors

PubMed Central

Tang, Wenming; Liu, Guixiong; Li, Yuzhong; Tan, Daji

2017-01-01

High data transmission efficiency is a key requirement for an ultrasonic phased array with multi-group ultrasonic sensors. Here, a novel FIFOs scheduling algorithm was proposed and the data transmission efficiency with hardware technology was improved. This algorithm includes FIFOs as caches for the ultrasonic scanning data obtained from the sensors with the output data in a bandwidth-sharing way, on the basis of which an optimal length ratio of all the FIFOs is achieved, allowing the reading operations to be switched among all the FIFOs without time slot waiting. Therefore, this algorithm enhances the utilization ratio of the reading bandwidth resources so as to obtain higher efficiency than the traditional scheduling algorithms. The reliability and validity of the algorithm are substantiated after its implementation in the field programmable gate array (FPGA) technology, and the bandwidth utilization ratio and the real-time performance of the ultrasonic phased array are enhanced. PMID:29035345

Creative Classroom Assignment Through Database Management.

ERIC Educational Resources Information Center

Shah, Vivek; Bryant, Milton

1987-01-01

The Faculty Scheduling System (FSS), a database management system designed to give administrators the ability to schedule faculty in a fast and efficient manner is described. The FSS, developed using dBASE III, requires an IBM compatible microcomputer with a minimum of 256K memory. (MLW)

a Quadtree Organization Construction and Scheduling Method for Urban 3d Model Based on Weight

NASA Astrophysics Data System (ADS)

Yao, C.; Peng, G.; Song, Y.; Duan, M.

2017-09-01

The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.

A novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem

NASA Astrophysics Data System (ADS)

Mirabi, Mohammad; Fatemi Ghomi, S. M. T.; Jolai, F.

2014-04-01

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and setup costs of large permutation flow-shop scheduling problems with sequence-dependent setup times on each machine, this paper develops a novel hybrid genetic algorithm (HGA) with three genetic operators. Proposed HGA applies a modified approach to generate a pool of initial solutions, and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. We consider the make-to-order production approach that some sequences between jobs are assumed as tabu based on maximum allowable setup cost. In addition, the results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

Progress towards Managing Residential Electricity Demand: Impacts of Standards and Labeling for Refrigerators and Air Conditioners in India

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

McNeil, Michael A.; Iyer, Maithili

The development of Energy Efficiency Standards and Labeling (EES&L) began in earnest in India in 2001 with the Energy Conservation Act and the establishment of the Indian Bureau of Energy Efficiency (BEE). The first main residential appliance to be targeted was refrigerators, soon to be followed by room air conditioners. Both of these appliances are of critical importance to India's residential electricity demand. About 15percent of Indian households own a refrigerator, and sales total about 4 million per year, but are growing. At the same time, the Indian refrigerator market has seen a strong trend towards larger and more consumptivemore » frost-free units. Room air conditioners in India have traditionally been sold to commercial sector customers, but an increasing number are going to the residential sector. Room air conditioner sales growth in India peaked in the last few years at 20percent per year. In this paper, we perform an engineering-based analysis using data specific to Indian appliances. We evaluate costs and benefits to residential and commercial sector consumers from increased equipment costs and utility bill savings. The analysis finds that, while the BEE scheme presents net benefits to consumers, there remain opportunities for efficiency improvement that would optimize consumer benefits, according to Life Cycle Cost analysis. Due to the large and growing market for refrigerators and air conditioners in India, we forecast large impacts from the standards and labeling program as scheduled. By 2030, this program, if fully implemented would reduce Indian residential electricity consumption by 55 TWh. Overall savings through 2030 totals 385 TWh. Finally, while efficiency levels have been set for several years for refrigerators, labels and MEPS for these products remain voluntary. We therefore consider the negative impact of this delay of implementation to energy and financial savings achievable by 2030.« less

Design and Evaluation of the Terminal Area Precision Scheduling and Spacing System

NASA Technical Reports Server (NTRS)

Swenson, Harry N.; Thipphavong, Jane; Sadovsky, Alex; Chen, Liang; Sullivan, Chris; Martin, Lynne

2011-01-01

This paper describes the design, development and results from a high fidelity human-in-the-loop simulation of an integrated set of trajectory-based automation tools providing precision scheduling, sequencing and controller merging and spacing functions. These integrated functions are combined into a system called the Terminal Area Precision Scheduling and Spacing (TAPSS) system. It is a strategic and tactical planning tool that provides Traffic Management Coordinators, En Route and Terminal Radar Approach Control air traffic controllers the ability to efficiently optimize the arrival capacity of a demand-impacted airport while simultaneously enabling fuel-efficient descent procedures. The TAPSS system consists of four-dimensional trajectory prediction, arrival runway balancing, aircraft separation constraint-based scheduling, traffic flow visualization and trajectory-based advisories to assist controllers in efficient metering, sequencing and spacing. The TAPSS system was evaluated and compared to today's ATC operation through extensive series of human-in-the-loop simulations for arrival flows into the Los Angeles International Airport. The test conditions included the variation of aircraft demand from a baseline of today's capacity constrained periods through 5%, 10% and 20% increases. Performance data were collected for engineering and human factor analysis and compared with similar operations both with and without the TAPSS system. The engineering data indicate operations with the TAPSS show up to a 10% increase in airport throughput during capacity constrained periods while maintaining fuel-efficient aircraft descent profiles from cruise to landing.

Sustainable IT and IT for Sustainability

NASA Astrophysics Data System (ADS)

Liu, Zhenhua

Energy and sustainability have become one of the most critical issues of our generation. While the abundant potential of renewable energy such as solar and wind provides a real opportunity for sustainability, their intermittency and uncertainty present a daunting operating challenge. This thesis aims to develop analytical models, deployable algorithms, and real systems to enable efficient integration of renewable energy into complex distributed systems with limited information. The first thrust of the thesis is to make IT systems more sustainable by facilitating the integration of renewable energy into these systems. IT represents the fastest growing sectors in energy usage and greenhouse gas pollution. Over the last decade there are dramatic improvements in the energy efficiency of IT systems, but the efficiency improvements do not necessarily lead to reduction in energy consumption because more servers are demanded. Further, little effort has been put in making IT more sustainable, and most of the improvements are from improved "engineering" rather than improved "algorithms". In contrast, my work focuses on developing algorithms with rigorous theoretical analysis that improve the sustainability of IT. In particular, this thesis seeks to exploit the flexibilities of cloud workloads both (i) in time by scheduling delay-tolerant workloads and (ii) in space by routing requests to geographically diverse data centers. These opportunities allow data centers to adaptively respond to renewable availability, varying cooling efficiency, and fluctuating energy prices, while still meeting performance requirements. The design of the enabling algorithms is however very challenging because of limited information, non-smooth objective functions and the need for distributed control. Novel distributed algorithms are developed with theoretically provable guarantees to enable the "follow the renewables" routing. Moving from theory to practice, I helped HP design and implement industry's first Net-zero Energy Data Center. The second thrust of this thesis is to use IT systems to improve the sustainability and efficiency of our energy infrastructure through data center demand response. The main challenges as we integrate more renewable sources to the existing power grid come from the fluctuation and unpredictability of renewable generation. Although energy storage and reserves can potentially solve the issues, they are very costly. One promising alternative is to make the cloud data centers demand responsive. The potential of such an approach is huge. To realize this potential, we need adaptive and distributed control of cloud data centers and new electricity market designs for distributed electricity resources. My work is progressing in both directions. In particular, I have designed online algorithms with theoretically guaranteed performance for data center operators to deal with uncertainties under popular demand response programs. Based on local control rules of customers, I have further designed new pricing schemes for demand response to align the interests of customers, utility companies, and the society to improve social welfare.

A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

PubMed

Hajri, S; Liouane, N; Hammadi, S; Borne, P

2000-01-01

Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.

A task scheduler framework for self-powered wireless sensors.

PubMed

Nordman, Mikael M

2003-10-01

The cost and inconvenience of cabling is a factor limiting widespread use of intelligent sensors. Recent developments in short-range, low-power radio seem to provide an opening to this problem, making development of wireless sensors feasible. However, for these sensors the energy availability is a main concern. The common solution is either to use a battery or to harvest ambient energy. The benefit of harvested ambient energy is that the energy feeder can be considered as lasting a lifetime, thus it saves the user from concerns related to energy management. The problem is, however, the unpredictability and unsteady behavior of ambient energy sources. This becomes a main concern for sensors that run multiple tasks at different priorities. This paper proposes a new scheduler framework that enables the reliable assignment of task priorities and scheduling in sensors powered by ambient energy. The framework being based on environment parameters, virtual queues, and a state machine with transition conditions, dynamically manages task execution according to priorities. The framework is assessed in a test system powered by a solar panel. The results show the functionality of the framework and how task execution reliably is handled without violating the priority scheme that has been assigned to it.

Energy consumption quota management of Wanda commercial buildings in China

NASA Astrophysics Data System (ADS)

Sun, D. B.; Xiao, H.; Wang, X.; Liu, J. J.; Wang, X.; Jin, X. Q.; Wang, J.; Xie, X. K.

2016-08-01

There is limited research of commercial buildings’ energy use data conducted based on practical analysis in China nowadays. Some energy consumption quota tools like Energy Star in U.S or VDI 3807 in Germany have limitation in China's building sector. This study introduces an innovative methodology of applying energy use quota model and empirical management to commercial buildings, which was in accordance of more than one hundred opened shopping centers of a real estate group in China. On the basis of statistical benchmarking, a new concept of “Modified coefficient”, which considers weather, occupancy, business layout, operation schedule and HVAC efficiency, is originally introduced in this paper. Our study shows that the average energy use quota increases from north to south. The average energy use quota of sample buildings is 159 kWh/(m2.a) of severe cold climate zone, 179 kWh/(m2.a) of cold zone, 188 kWh/(m2.a) of hot summer and cold winter zone, and 200 kWh/(m2.a) of hot summer and warm winter zone. The energy use quota model has been validated in the property management for year 2016, providing a new method of commercial building energy management to the industry. As a key result, there is 180 million energy saving potential based on energy quota management in 2016, equals to 6.2% saving rate of actual energy use in 2015.

Open-pit coal mine production sequencing incorporating grade blending and stockpiling options: An application from an Indian mine

NASA Astrophysics Data System (ADS)

Kumar, Ashish; Chatterjee, Snehamoy

2017-05-01

Production scheduling is a crucial aspect of the mining industry. An optimal and efficient production schedule can increase the profits manifold and reduce the amount of waste to be handled. Production scheduling for coal mines is necessary to maintain consistency in the quality and quantity parameters of coal supplied to power plants. Irregularity in the quality parameters of the coal can lead to heavy losses in coal-fired power plants. Moreover, the stockpiling of coal poses environmental and fire problems owing to low incubation periods. This article proposes a production scheduling formulation for open-pit coal mines including stockpiling and blending opportunities, which play a major role in maintaining the quality and quantity of supplied coal. The proposed formulation was applied to a large open-pit coal mine in India. This contribution provides an efficient production scheduling formulation for coal mines after utilizing the stockpile coal within the incubation periods with the maximization of discounted cash flows. At the same time, consistency is maintained in the quality and quantity of coal to power plants through blending and stockpiling options to ensure smooth functioning.

18 CFR 154.202 - Filings to initiate a new rate schedule.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Filings to initiate a new rate schedule. 154.202 Section 154.202 Conservation of Power and Water Resources FEDERAL ENERGY... Procedures for Changing Tariffs § 154.202 Filings to initiate a new rate schedule. (a) When the filing is to...

18 CFR 154.202 - Filings to initiate a new rate schedule.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Filings to initiate a new rate schedule. 154.202 Section 154.202 Conservation of Power and Water Resources FEDERAL ENERGY... Procedures for Changing Tariffs § 154.202 Filings to initiate a new rate schedule. (a) When the filing is to...

18 CFR 154.202 - Filings to initiate a new rate schedule.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Filings to initiate a new rate schedule. 154.202 Section 154.202 Conservation of Power and Water Resources FEDERAL ENERGY... Procedures for Changing Tariffs § 154.202 Filings to initiate a new rate schedule. (a) When the filing is to...

18 CFR 154.202 - Filings to initiate a new rate schedule.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Filings to initiate a new rate schedule. 154.202 Section 154.202 Conservation of Power and Water Resources FEDERAL ENERGY... Procedures for Changing Tariffs § 154.202 Filings to initiate a new rate schedule. (a) When the filing is to...

18 CFR 154.202 - Filings to initiate a new rate schedule.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Filings to initiate a new rate schedule. 154.202 Section 154.202 Conservation of Power and Water Resources FEDERAL ENERGY... Procedures for Changing Tariffs § 154.202 Filings to initiate a new rate schedule. (a) When the filing is to...

10 CFR 32.102 - Schedule C-prototype tests for calibration or reference sources containing americium-241 or...

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false Schedule C-prototype tests for calibration or reference... Licensed Items § 32.102 Schedule C—prototype tests for calibration or reference sources containing..., conduct prototype tests, in the order listed, on each of five prototypes of the source, which contains...

Modeling and Simulation of HVAC Faulty Operations and Performance Degradation due to Maintenance Issues

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

Wang, Liping; Hong, Tianzhen

Almost half of the total energy used in the U.S. buildings is consumed by heating, ventilation and air conditionings (HVAC) according to EIA statistics. Among various driving factors to energy performance of building, operations and maintenance play a significant role. Many researches have been done to look at design efficiencies and operational controls for improving energy performance of buildings, but very few study the impacts of HVAC systems maintenance. Different practices of HVAC system maintenance can result in substantial differences in building energy use. If a piece of HVAC equipment is not well maintained, its performance will degrade. If sensorsmore » used for control purpose are not calibrated, not only building energy usage could be dramatically increased, but also mechanical systems may not be able to satisfy indoor thermal comfort. Properly maintained HVAC systems can operate efficiently, improve occupant comfort, and prolong equipment service life. In the paper, maintenance practices for HVAC systems are presented based on literature reviews and discussions with HVAC engineers, building operators, facility managers, and commissioning agents. We categorize the maintenance practices into three levels depending on the maintenance effort and coverage: 1) proactive, performance-monitored maintenance; 2) preventive, scheduled maintenance; and 3) reactive, unplanned or no maintenance. A sampled list of maintenance issues, including cooling tower fouling, boiler/chiller fouling, refrigerant over or under charge, temperature sensor offset, outdoor air damper leakage, outdoor air screen blockage, outdoor air damper stuck at fully open position, and dirty filters are investigated in this study using field survey data and detailed simulation models. The energy impacts of both individual maintenance issue and combined scenarios for an office building with central VAV systems and central plant were evaluated by EnergyPlus simulations using three approaches: 1) direct modeling with EnergyPlus, 2) using the energy management system feature of EnergyPlus, and 3) modifying EnergyPlus source code. The results demonstrated the importance of maintenance for HVAC systems on energy performance of buildings. The research is intended to provide a guideline to help practitioners and building operators to gain the knowledge of maintaining HVAC systems in efficient operations, and prioritize HVAC maintenance work plan. The paper also discusses challenges of modeling building maintenance issues using energy simulation programs.« less

Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis

PubMed Central

Hemmati, Reza; Saboori, Hedayat

2016-01-01

Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. PMID:27222741

Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis.

PubMed

Hemmati, Reza; Saboori, Hedayat

2016-05-01

Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics.

Efficiency Benefits Using the Terminal Area Precision Scheduling and Spacing System

NASA Technical Reports Server (NTRS)

Thipphavong, Jane; Swenson, Harry N.; Lin, Paul; Seo, Anthony Y.; Bagasol, Leonard N.

2011-01-01

NASA has developed a capability for terminal area precision scheduling and spacing (TAPSS) to increase the use of fuel-efficient arrival procedures during periods of traffic congestion at a high-density airport. Sustained use of fuel-efficient procedures throughout the entire arrival phase of flight reduces overall fuel burn, greenhouse gas emissions and noise pollution. The TAPSS system is a 4D trajectory-based strategic planning and control tool that computes schedules and sequences for arrivals to facilitate optimal profile descents. This paper focuses on quantifying the efficiency benefits associated with using the TAPSS system, measured by reduction of level segments during aircraft descent and flight distance and time savings. The TAPSS system was tested in a series of human-in-the-loop simulations and compared to current procedures. Compared to the current use of the TMA system, simulation results indicate a reduction of total level segment distance by 50% and flight distance and time savings by 7% in the arrival portion of flight (200 nm from the airport). The TAPSS system resulted in aircraft maintaining continuous descent operations longer and with more precision, both achieved under heavy traffic demand levels.

User-Assisted Store Recycling for Dynamic Task Graph Schedulers

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

Kurt, Mehmet Can; Krishnamoorthy, Sriram; Agrawal, Gagan

The emergence of the multi-core era has led to increased interest in designing effective yet practical parallel programming models. Models based on task graphs that operate on single-assignment data are attractive in several ways: they can support dynamic applications and precisely represent the available concurrency. However, they also require nuanced algorithms for scheduling and memory management for efficient execution. In this paper, we consider memory-efficient dynamic scheduling of task graphs. Specifically, we present a novel approach for dynamically recycling the memory locations assigned to data items as they are produced by tasks. We develop algorithms to identify memory-efficient store recyclingmore » functions by systematically evaluating the validity of a set of (user-provided or automatically generated) alternatives. Because recycling function can be input data-dependent, we have also developed support for continued correct execution of a task graph in the presence of a potentially incorrect store recycling function. Experimental evaluation demonstrates that our approach to automatic store recycling incurs little to no overheads, achieves memory usage comparable to the best manually derived solutions, often produces recycling functions valid across problem sizes and input parameters, and efficiently recovers from an incorrect choice of store recycling functions.« less

On scheduling task systems with variable service times

NASA Astrophysics Data System (ADS)

Maset, Richard G.; Banawan, Sayed A.

1993-08-01

Several strategies have been proposed for developing optimal and near-optimal schedules for task systems (jobs consisting of multiple tasks that can be executed in parallel). Most such strategies, however, implicitly assume deterministic task service times. We show that these strategies are much less effective when service times are highly variable. We then evaluate two strategies—one adaptive, one static—that have been proposed for retaining high performance despite such variability. Both strategies are extensions of critical path scheduling, which has been found to be efficient at producing near-optimal schedules. We found the adaptive approach to be quite effective.

Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems

NASA Astrophysics Data System (ADS)

Cruz-Chávez, Marco Antonio

2015-11-01

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.

Automatic generation of efficient orderings of events for scheduling applications

NASA Technical Reports Server (NTRS)

Morris, Robert A.

1994-01-01

In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.

Flexible Residential Smart Grid Simulation Framework

NASA Astrophysics Data System (ADS)

Xiang, Wang

Different scheduling and coordination algorithms controlling household appliances' operations can potentially lead to energy consumption reduction and/or load balancing in conjunction with different electricity pricing methods used in smart grid programs. In order to easily implement different algorithms and evaluate their efficiency against other ideas, a flexible simulation framework is desirable in both research and business fields. However, such a platform is currently lacking or underdeveloped. In this thesis, we provide a simulation framework to focus on demand side residential energy consumption coordination in response to different pricing methods. This simulation framework, equipped with an appliance consumption library using realistic values, aims to closely represent the average usage of different types of appliances. The simulation results of traditional usage yield close matching values compared to surveyed real life consumption records. Several sample coordination algorithms, pricing schemes, and communication scenarios are also implemented to illustrate the use of the simulation framework.

Optimal route scheduling-driven study of a photovoltaic charging-station (parking lot) for electric mini-buses

NASA Astrophysics Data System (ADS)

Zacharaki, V.; Papanikolaou, S.; Voulgaraki, Ch; Karantinos, A.; Sioumpouras, D.; Tsiamitros, D.; Stimoniaris, D.; Maropoulos, S.; Stephanedes, Y.

2016-11-01

The objective of the present study is threefold: To highlight how electro-mobility can: (a) Contribute to the promotion of the environmental conservation of the rural areas (through an integrated solution for reducing the carbon footprint of road facilities and transport), (b) Enhance tourism-based economical development, (c) facilitate students in their daily transport and residents (elderly, disabled, distant-residents) in their daily on-demand transport. The overall goal is to design an energy-efficient, regional intelligent transportation system with innovative solar-energy charging-stations for e-vehicles in municipalities with many geographically scattered small villages and small cities. The innovative character of the study is that it tries to tackle all three specific objectives simultaneously and with the same means, since it utilizes Intelligent Transportation Systems (ITS). The study is adapted and applied to an area with the above characteristics, in order to demonstrate the proof of concept.

Dedicated heterogeneous node scheduling including backfill scheduling

DOEpatents

Wood, Robert R [Livermore, CA; Eckert, Philip D [Livermore, CA; Hommes, Gregg [Pleasanton, CA

2006-07-25

A method and system for job backfill scheduling dedicated heterogeneous nodes in a multi-node computing environment. Heterogeneous nodes are grouped into homogeneous node sub-pools. For each sub-pool, a free node schedule (FNS) is created so that the number of to chart the free nodes over time. For each prioritized job, using the FNS of sub-pools having nodes useable by a particular job, to determine the earliest time range (ETR) capable of running the job. Once determined for a particular job, scheduling the job to run in that ETR. If the ETR determined for a lower priority job (LPJ) has a start time earlier than a higher priority job (HPJ), then the LPJ is scheduled in that ETR if it would not disturb the anticipated start times of any HPJ previously scheduled for a future time. Thus, efficient utilization and throughput of such computing environments may be increased by utilizing resources otherwise remaining idle.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks.

PubMed

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-06-26

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H²RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H²RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

Development of an Irrigation Scheduling Tool for the High Plains Region

NASA Astrophysics Data System (ADS)

Shulski, M.; Hubbard, K. G.; You, J.

2009-12-01

The High Plains Regional Climate Center (HPRCC) at the University of Nebraska is one of NOAA’s six regional climate centers in the U.S. Primary objectives of the HPRCC are to conduct applied climate research, engage in climate education and outreach, and increase the use and availability of climate information by developing value-added products. Scientists at the center are engaged in utilizing regional weather data to develop tools that can be used directly by area stakeholders, particularly for agricultural sectors. A new study is proposed that will combine NOAA products (short-term forecasts and seasonal outlooks of temperature and precipitation) with existing capabilities to construct an irrigation scheduling tool that can be used by producers in the region. This tool will make use of weather observations from the regional mesonet (specifically the AWDN, Automated Weather Data Network) and the nation-wide relational database and web portal (ACIS, Applied Climate Information System). The primary benefit to stakeholders will be a more efficient use of water and energy resources owing to the reduction of uncertainty in the timing of irrigation.

Optimization and Control of Cyber-Physical Vehicle Systems

PubMed Central

Bradley, Justin M.; Atkins, Ella M.

2015-01-01

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541

Optimization and Control of Cyber-Physical Vehicle Systems.

PubMed

Bradley, Justin M; Atkins, Ella M

2015-09-11

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints.

PubMed

Sundharam, Sakthivel Manikandan; Navet, Nicolas; Altmeyer, Sebastian; Havet, Lionel

2018-02-20

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

PubMed Central

Navet, Nicolas; Havet, Lionel

2018-01-01

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system. PMID:29461489

Bandwidth reduction for video-on-demand broadcasting using secondary content insertion

NASA Astrophysics Data System (ADS)

Golynski, Alexander; Lopez-Ortiz, Alejandro; Poirier, Guillaume; Quimper, Claude-Guy

2005-01-01

An optimal broadcasting scheme under the presence of secondary content (i.e. advertisements) is proposed. The proposed scheme works both for movies encoded in a Constant Bit Rate (CBR) or a Variable Bit Rate (VBR) format. It is shown experimentally that secondary content in movies can make Video-on-Demand (VoD) broadcasting systems more efficient. An efficient algorithm is given to compute the optimal broadcasting schedule with secondary content, which in particular significantly improves over the best previously known algorithm for computing the optimal broadcasting schedule without secondary content.

A Form 990 Schedule H conundrum: how much of your bad debt might be charity?

PubMed

Bailey, Shari; Franklin, David; Hearle, Keith

2010-04-01

IRS Form 990 Schedule H requires hospitals to estimate the amount of bad debt expense attributable to patients eligible for charity under the hospital's charity care policy. Responses to Schedule H, Part III.A.3 open up the entire patient collection process to examination by the IRS, state officials, and the public. Using predictive analytics can help hospitals efficiently identify charity-eligible patients when answering Part III.A.3.

Future applications of artificial intelligence to Mission Control Centers

NASA Technical Reports Server (NTRS)

Friedland, Peter

1991-01-01

Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

A transportation-scheduling system for managing silvicultural projects

Treesearch

Jorge F. Valenzuela; H. Hakan Balci; Timothy McDonald

2005-01-01

A silvicultural project encompasses tasks such as sitelevel planning, regeneration, harvestin, and stand-tending treatments. an essential problem in managing silvicultural projects is to efficiently schedule the operations while considering project task due dates and costs of moving scarce resources to specific job locations. Transportation costs represent a...

77 FR 43084 - Multiple Award Schedule (MAS) Program Continuous Open Season-Operational Change

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-23

... Award Schedule (MAS) Program Continuous Open Season- Operational Change AGENCY: Federal Acquisition... proposing this operational change to enhance the performance of and modernize the MAS program in three key program areas: Small business viability, operational efficiency, and cost control. The DBM will realign...

Analysis of Application Power and Schedule Composition in a High Performance Computing Environment

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

Elmore, Ryan; Gruchalla, Kenny; Phillips, Caleb

As the capacity of high performance computing (HPC) systems continues to grow, small changes in energy management have the potential to produce significant energy savings. In this paper, we employ an extensive informatics system for aggregating and analyzing real-time performance and power use data to evaluate energy footprints of jobs running in an HPC data center. We look at the effects of algorithmic choices for a given job on the resulting energy footprints, and analyze application-specific power consumption, and summarize average power use in the aggregate. All of these views reveal meaningful power variance between classes of applications as wellmore » as chosen methods for a given job. Using these data, we discuss energy-aware cost-saving strategies based on reordering the HPC job schedule. Using historical job and power data, we present a hypothetical job schedule reordering that: (1) reduces the facility's peak power draw and (2) manages power in conjunction with a large-scale photovoltaic array. Lastly, we leverage this data to understand the practical limits on predicting key power use metrics at the time of submission.« less

10 CFR Appendix D to Part 2 - Schedule for the Proceeding on Consideration of Construction Authorization for a High-Level Waste...

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false Schedule for the Proceeding on Consideration of Construction Authorization for a High-Level Waste Geologic Repository. D Appendix D to Part 2 Energy NUCLEAR... for a High-Level Waste Geologic Repository. Day Regulation (10 CFR) Action 0 2.101(f)(8), 2.105(a)(5...

A New Distributed Optimization for Community Microgrids Scheduling

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

Starke, Michael R; Tomsovic, Kevin

This paper proposes a distributed optimization model for community microgrids considering the building thermal dynamics and customer comfort preference. The microgrid central controller (MCC) minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost and voluntary load shedding cost based on the customers' consumption, while the building energy management systems (BEMS) minimize their electricity bills as well as the cost associated with customer discomfort due to room temperature deviation from the set point. The BEMSs and the MCC exchange information on energy consumption and prices. When the optimization converges, the distributed generation scheduling,more » energy storage charging/discharging and customers' consumption as well as the energy prices are determined. In particular, we integrate the detailed thermal dynamic characteristics of buildings into the proposed model. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of proposed model.« less

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO 2 capture

DOE PAGES

Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu; ...

2017-11-03

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO 2 capture

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

Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less

10 CFR 32.103 - Schedule D-prototype tests for ice detection devices containing strontium-90.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false Schedule D-prototype tests for ice detection devices... § 32.103 Schedule D—prototype tests for ice detection devices containing strontium-90. An applicant for a license pursuant to § 32.61 shall conduct prototype tests on each of five prototype ice detection...

10 CFR 32.103 - Schedule D-prototype tests for ice detection devices containing strontium-90.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 1 2011-01-01 2011-01-01 false Schedule D-prototype tests for ice detection devices... § 32.103 Schedule D—prototype tests for ice detection devices containing strontium-90. An applicant for a license pursuant to § 32.61 shall conduct prototype tests on each of five prototype ice detection...

10 CFR 32.103 - Schedule D-prototype tests for ice detection devices containing strontium-90.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 1 2012-01-01 2012-01-01 false Schedule D-prototype tests for ice detection devices... § 32.103 Schedule D—prototype tests for ice detection devices containing strontium-90. An applicant for a license pursuant to § 32.61 shall conduct prototype tests on each of five prototype ice detection...

Effects of reinforcer magnitude on responding under differential-reinforcement-of-low-rate schedules of rats and pigeons.

PubMed

Doughty, Adam H; Richards, Jerry B

2002-07-01

Experiment I investigated the effects of reinforcer magnitude on differential-reinforcement-of-low-rate (DRL) schedule performance in three phases. In Phase 1, two groups of rats (n = 6 and 5) responded under a DRI. 72-s schedule with reinforcer magnitudes of either 30 or 300 microl of water. After acquisition, the water amounts were reversed for each rat. In Phase 2, the effects of the same reinforcer magnitudes on DRL 18-s schedule performance were examined across conditions. In Phase 3, each rat responded unider a DR1. 18-s schedule in which the water amotnts alternated between 30 and 300 microl daily. Throughout each phase of Experiment 1, the larger reinforcer magnitude resulted in higher response rates and lower reinforcement rates. The peak of the interresponse-time distributions was at a lower value tinder the larger reinforcer magnitude. In Experiment 2, 3 pigeons responded under a DRL 20-s schedule in which reinforcer magnitude (1-s or 6-s access to grain) varied iron session to session. Higher response rates and lower reinforcement rates occurred tinder the longer hopper duration. These results demonstrate that larger reinforcer magnitudes engender less efficient DRL schedule performance in both rats and pigeons, and when reinforcer magnitude was held constant between sessions or was varied daily. The present results are consistent with previous research demonstrating a decrease in efficiency as a function of increased reinforcer magnituide tinder procedures that require a period of time without a specified response. These findings also support the claim that DRI. schedule performance is not governed solely by a timing process.

Effects of reinforcer magnitude on responding under differential-reinforcement-of-low-rate schedules of rats and pigeons.

PubMed Central

Doughty, Adam H; Richards, Jerry B

2002-01-01

Experiment I investigated the effects of reinforcer magnitude on differential-reinforcement-of-low-rate (DRL) schedule performance in three phases. In Phase 1, two groups of rats (n = 6 and 5) responded under a DRI. 72-s schedule with reinforcer magnitudes of either 30 or 300 microl of water. After acquisition, the water amounts were reversed for each rat. In Phase 2, the effects of the same reinforcer magnitudes on DRL 18-s schedule performance were examined across conditions. In Phase 3, each rat responded unider a DR1. 18-s schedule in which the water amotnts alternated between 30 and 300 microl daily. Throughout each phase of Experiment 1, the larger reinforcer magnitude resulted in higher response rates and lower reinforcement rates. The peak of the interresponse-time distributions was at a lower value tinder the larger reinforcer magnitude. In Experiment 2, 3 pigeons responded under a DRL 20-s schedule in which reinforcer magnitude (1-s or 6-s access to grain) varied iron session to session. Higher response rates and lower reinforcement rates occurred tinder the longer hopper duration. These results demonstrate that larger reinforcer magnitudes engender less efficient DRL schedule performance in both rats and pigeons, and when reinforcer magnitude was held constant between sessions or was varied daily. The present results are consistent with previous research demonstrating a decrease in efficiency as a function of increased reinforcer magnituide tinder procedures that require a period of time without a specified response. These findings also support the claim that DRI. schedule performance is not governed solely by a timing process. PMID:12144310

Separation Assurance and Scheduling Coordination in the Arrival Environment

NASA Technical Reports Server (NTRS)

Aweiss, Arwa S.; Cone, Andrew C.; Holladay, Joshua J.; Munoz, Epifanio; Lewis, Timothy A.

2016-01-01

Separation assurance (SA) automation has been proposed as either a ground-based or airborne paradigm. The arrival environment is complex because aircraft are being sequenced and spaced to the arrival fix. This paper examines the effect of the allocation of the SA and scheduling functions on the performance of the system. Two coordination configurations between an SA and an arrival management system are tested using both ground and airborne implementations. All configurations have a conflict detection and resolution (CD&R) system and either an integrated or separated scheduler. Performance metrics are presented for the ground and airborne systems based on arrival traffic headed to Dallas/ Fort Worth International airport. The total delay, time-spacing conformance, and schedule conformance are used to measure efficiency. The goal of the analysis is to use the metrics to identify performance differences between the configurations that are based on different function allocations. A surveillance range limitation of 100 nmi and a time delay for sharing updated trajectory intent of 30 seconds were implemented for the airborne system. Overall, these results indicate that the surveillance range and the sharing of trajectories and aircraft schedules are important factors in determining the efficiency of an airborne arrival management system. These parameters are not relevant to the ground-based system as modeled for this study because it has instantaneous access to all aircraft trajectories and intent. Creating a schedule external to the CD&R and the scheduling conformance system was seen to reduce total delays for the airborne system, and had a minor effect on the ground-based system. The effect of an external scheduler on other metrics was mixed.

Improving operating room efficiency by applying bin-packing and portfolio techniques to surgical case scheduling.

PubMed

Van Houdenhoven, Mark; van Oostrum, Jeroen M; Hans, Erwin W; Wullink, Gerhard; Kazemier, Geert

2007-09-01

An operating room (OR) department has adopted an efficient business model and subsequently investigated how efficiency could be further improved. The aim of this study is to show the efficiency improvement of lowering organizational barriers and applying advanced mathematical techniques. We applied advanced mathematical algorithms in combination with scenarios that model relaxation of various organizational barriers using prospectively collected data. The setting is the main inpatient OR department of a university hospital, which sets its surgical case schedules 2 wk in advance using a block planning method. The main outcome measures are the number of freed OR blocks and OR utilization. Lowering organizational barriers and applying mathematical algorithms can yield a 4.5% point increase in OR utilization (95% confidence interval 4.0%-5.0%). This is obtained by reducing the total required OR time. Efficient OR departments can further improve their efficiency. The paper shows that a radical cultural change that comprises the use of mathematical algorithms and lowering organizational barriers improves OR utilization.

KSC-01PP1402

NASA Image and Video Library

2001-07-27

KENNEDY SPACE CENTER, Fla. -- On Launch Pad 39A, two Hitchhiker Experiments Advancing Technology (HEAT) payloads are loaded onto Discovery’s port adapter beam in the payload bay. At left is the Space Experiment Module, an educational initiative to increase educational access to space. The canister contains up to 10 small, enclosed modules that contain separate, passive experiments designed and constructed by students. Many of the experiments will study the growing characteristics of plants subjected to the space environment. At right is the Get Away Special canister containing the Alkali Metal Thermal-to-Electric Converter (AMTEC), designed for efficient conversion of heat into electrical energy. The HEAT payloads are flying on mission STS-105, scheduled to launch Aug. 9, 2001

EnergySolution's Clive Disposal Facility Operational Research Model - 13475

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

Nissley, Paul; Berry, Joanne

2013-07-01

EnergySolutions owns and operates a licensed, commercial low-level radioactive waste disposal facility located in Clive, Utah. The Clive site receives low-level radioactive waste from various locations within the United States via bulk truck, containerised truck, enclosed truck, bulk rail-cars, rail boxcars, and rail inter-modals. Waste packages are unloaded, characterized, processed, and disposed of at the Clive site. Examples of low-level radioactive waste arriving at Clive include, but are not limited to, contaminated soil/debris, spent nuclear power plant components, and medical waste. Generators of low-level radioactive waste typically include nuclear power plants, hospitals, national laboratories, and various United States government operatedmore » waste sites. Over the past few years, poor economic conditions have significantly reduced the number of shipments to Clive. With less revenue coming in from processing shipments, Clive needed to keep its expenses down if it was going to maintain past levels of profitability. The Operational Research group of EnergySolutions were asked to develop a simulation model to help identify any improvement opportunities that would increase overall operating efficiency and reduce costs at the Clive Facility. The Clive operations research model simulates the receipt, movement, and processing requirements of shipments arriving at the facility. The model includes shipment schedules, processing times of various waste types, labor requirements, shift schedules, and site equipment availability. The Clive operations research model has been developed using the WITNESS{sup TM} process simulation software, which is developed by the Lanner Group. The major goals of this project were to: - identify processing bottlenecks that could reduce the turnaround time from shipment arrival to disposal; - evaluate the use (or idle time) of labor and equipment; - project future operational requirements under different forecasted scenarios. By identifying processing bottlenecks and unused equipment and/or labor, improvements to operating efficiency could be determined and appropriate cost saving measures implemented. Model runs forecasting various scenarios helped illustrate potential impacts of certain conditions (e.g. 20% decrease in shipments arrived), variables (e.g. 20% decrease in labor), or other possible situations. (authors)« less

Integrated scheduling and resource management. [for Space Station Information System

NASA Technical Reports Server (NTRS)

Ward, M. T.

1987-01-01

This paper examines the problem of integrated scheduling during the Space Station era. Scheduling for Space Station entails coordinating the support of many distributed users who are sharing common resources and pursuing individual and sometimes conflicting objectives. This paper compares the scheduling integration problems of current missions with those anticipated for the Space Station era. It examines the facilities and the proposed operations environment for Space Station. It concludes that the pattern of interdependecies among the users and facilities, which are the source of the integration problem is well structured, allowing a dividing of the larger problem into smaller problems. It proposes an architecture to support integrated scheduling by scheduling efficiently at local facilities as a function of dependencies with other facilities of the program. A prototype is described that is being developed to demonstrate this integration concept.

An Improved Recovery Algorithm for Decayed AES Key Schedule Images

NASA Astrophysics Data System (ADS)

Tsow, Alex

A practical algorithm that recovers AES key schedules from decayed memory images is presented. Halderman et al. [1] established this recovery capability, dubbed the cold-boot attack, as a serious vulnerability for several widespread software-based encryption packages. Our algorithm recovers AES-128 key schedules tens of millions of times faster than the original proof-of-concept release. In practice, it enables reliable recovery of key schedules at 70% decay, well over twice the decay capacity of previous methods. The algorithm is generalized to AES-256 and is empirically shown to recover 256-bit key schedules that have suffered 65% decay. When solutions are unique, the algorithm efficiently validates this property and outputs the solution for memory images decayed up to 60%.

CQPSO scheduling algorithm for heterogeneous multi-core DAG task model

NASA Astrophysics Data System (ADS)

Zhai, Wenzheng; Hu, Yue-Li; Ran, Feng

2017-07-01

Efficient task scheduling is critical to achieve high performance in a heterogeneous multi-core computing environment. The paper focuses on the heterogeneous multi-core directed acyclic graph (DAG) task model and proposes a novel task scheduling method based on an improved chaotic quantum-behaved particle swarm optimization (CQPSO) algorithm. A task priority scheduling list was built. A processor with minimum cumulative earliest finish time (EFT) was acted as the object of the first task assignment. The task precedence relationships were satisfied and the total execution time of all tasks was minimized. The experimental results show that the proposed algorithm has the advantage of optimization abilities, simple and feasible, fast convergence, and can be applied to the task scheduling optimization for other heterogeneous and distributed environment.

An adaptive two-stage energy-efficiency mechanism for the doze mode in EPON

NASA Astrophysics Data System (ADS)

Nikoukar, AliAkbar; Hwang, I.-Shyan; Su, Yu-Min; Liem, Andrew Tanny

2016-07-01

Sleep and doze power-saving modes are the common ways to reduce power consumption of optical network units (ONUs) in Ethernet passive optical network (EPON). The doze mode turns off the ONU transmitter when there is no traffic in the upstream direction while the sleep mode turns off the ONU transmitter and receiver. As the result, the sleep mode is more efficient compared to the doze mode, but it introduces additional complexity of scheduling and signaling, losses the clock synchronization and requires long clock recovery time; furthermore, it requires the cooperation of the optical line terminal (OLT) in the downstream direction to queue frames. To improve the energy-saving in the doze mode, a new two-stage mechanism is introduced that the doze sleep duration is extended for longer time with acceptable quality-of-services (QoS) metrics when ONU is idle in the current cycle. By this way the ONU enters the doze mode even in the high load traffic; moreover, the green dynamic bandwidth allocation (GBA) is proposed to calculate the doze sleep duration based on the ONU queue state and incoming traffic ratio. Simulation results show that the proposed mechanism significantly improves the energy-saving 74% and 54% when traffic load is from the light load to the high load in different traffic situations, and also promises the QoS performance.

Proposal of Heuristic Algorithm for Scheduling of Print Process in Auto Parts Supplier

NASA Astrophysics Data System (ADS)

Matsumoto, Shimpei; Okuhara, Koji; Ueno, Nobuyuki; Ishii, Hiroaki

We are interested in the print process on the manufacturing processes of auto parts supplier as an actual problem. The purpose of this research is to apply our scheduling technique developed in university to the actual print process in mass customization environment. Rationalization of the print process is depending on the lot sizing. The manufacturing lead time of the print process is long, and in the present method, production is done depending on worker’s experience and intuition. The construction of an efficient production system is urgent problem. Therefore, in this paper, in order to shorten the entire manufacturing lead time and to reduce the stock, we reexamine the usual method of the lot sizing rule based on heuristic technique, and we propose the improvement method which can plan a more efficient schedule.

Analysis of sequencing and scheduling methods for arrival traffic

NASA Technical Reports Server (NTRS)

Neuman, Frank; Erzberger, Heinz

1990-01-01

The air traffic control subsystem that performs scheduling is discussed. The function of the scheduling algorithms is to plan automatically the most efficient landing order and to assign optimally spaced landing times to all arrivals. Several important scheduling algorithms are described and the statistical performance of the scheduling algorithms is examined. Scheduling brings order to an arrival sequence for aircraft. First-come-first-served scheduling (FCFS) establishes a fair order, based on estimated times of arrival, and determines proper separations. Because of the randomness of the traffic, gaps will remain in the scheduled sequence of aircraft. These gaps are filled, or partially filled, by time-advancing the leading aircraft after a gap while still preserving the FCFS order. Tightly scheduled groups of aircraft remain with a mix of heavy and large aircraft. Separation requirements differ for different types of aircraft trailing each other. Advantage is taken of this fact through mild reordering of the traffic, thus shortening the groups and reducing average delays. Actual delays for different samples with the same statistical parameters vary widely, especially for heavy traffic.

High Energy Power and Propulsion Capability Roadmap: General Background and Introduction

NASA Technical Reports Server (NTRS)

Bankston, Perry

2005-01-01

Agency objective are: Strategic Planning Transformation. Advanced Planning Organizational Roles. Public Involvement in Strategic Planning. Strategic Roadmaps and Schedule Capability Roadmaps and Schedule. Purpose of NRC Review. Capability Roadmap Development (Progress to Date).

Self-balancing dynamic scheduling of electrical energy for energy-intensive enterprises

NASA Astrophysics Data System (ADS)

Gao, Yunlong; Gao, Feng; Zhai, Qiaozhu; Guan, Xiaohong

2013-06-01

Balancing production and consumption with self-generation capacity in energy-intensive enterprises has huge economic and environmental benefits. However, balancing production and consumption with self-generation capacity is a challenging task since the energy production and consumption must be balanced in real time with the criteria specified by power grid. In this article, a mathematical model for minimising the production cost with exactly realisable energy delivery schedule is formulated. And a dynamic programming (DP)-based self-balancing dynamic scheduling algorithm is developed to obtain the complete solution set for such a multiple optimal solutions problem. For each stage, a set of conditions are established to determine whether a feasible control trajectory exists. The state space under these conditions is partitioned into subsets and each subset is viewed as an aggregate state, the cost-to-go function is then expressed as a function of initial and terminal generation levels of each stage and is proved to be a staircase function with finite steps. This avoids the calculation of the cost-to-go of every state to resolve the issue of dimensionality in DP algorithm. In the backward sweep process of the algorithm, an optimal policy is determined to maximise the realisability of energy delivery schedule across the entire time horizon. And then in the forward sweep process, the feasible region of the optimal policy with the initial and terminal state at each stage is identified. Different feasible control trajectories can be identified based on the region; therefore, optimising for the feasible control trajectory is performed based on the region with economic and reliability objectives taken into account.

Modeling Off-Nominal Recovery in NextGen Terminal-Area Operations

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2011-01-01

Robust schedule-based arrival management requires efficient recovery from off-nominal situations. This paper presents research on modeling off-nominal situations and plans for recovering from them using TRAC, a route/airspace design, fast-time simulation, and analysis tool for studying NextGen trajectory-based operations. The paper provides an overview of a schedule-based arrival-management concept and supporting controller tools, then describes TRAC implementations of methods for constructing off-nominal scenarios, generating trajectory options to meet scheduling constraints, and automatically producing recovery plans.

Decision-theoretic control of EUVE telescope scheduling

NASA Technical Reports Server (NTRS)

Hansson, Othar; Mayer, Andrew

1993-01-01

This paper describes a decision theoretic scheduler (DTS) designed to employ state-of-the-art probabilistic inference technology to speed the search for efficient solutions to constraint-satisfaction problems. Our approach involves assessing the performance of heuristic control strategies that are normally hard-coded into scheduling systems and using probabilistic inference to aggregate this information in light of the features of a given problem. The Bayesian Problem-Solver (BPS) introduced a similar approach to solving single agent and adversarial graph search patterns yielding orders-of-magnitude improvement over traditional techniques. Initial efforts suggest that similar improvements will be realizable when applied to typical constraint-satisfaction scheduling problems.

Experiments with a decision-theoretic scheduler

NASA Technical Reports Server (NTRS)

Hansson, Othar; Holt, Gerhard; Mayer, Andrew

1992-01-01

This paper describes DTS, a decision-theoretic scheduler designed to employ state-of-the-art probabilistic inference technology to speed the search for efficient solutions to constraint-satisfaction problems. Our approach involves assessing the performance of heuristic control strategies that are normally hard-coded into scheduling systems, and using probabilistic inference to aggregate this information in light of features of a given problem. BPS, the Bayesian Problem-Solver, introduced a similar approach to solving single-agent and adversarial graph search problems, yielding orders-of-magnitude improvement over traditional techniques. Initial efforts suggest that similar improvements will be realizable when applied to typical constraint-satisfaction scheduling problems.

Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling

PubMed Central

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220

Discrete bat algorithm for optimal problem of permutation flow shop scheduling.

PubMed

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.

Research on Power System Scheduling Improving Wind Power Accommodation Considering Thermal Energy Storage and Flexible Load

NASA Astrophysics Data System (ADS)

Zou, Chenlu; Cui, Xue; Wang, Heng; Zhou, Bin; Liu, Yang

2018-01-01

In the case of rapid development of wind power and heavy wind curtailment, the study of wind power accommodation of combined heat and power system has become the focus of attention. A two-stage scheduling model contains of wind power, thermal energy storage, CHP unit and flexible load were constructed. This model with the objective function of minimizing wind curtailment and the operation cost of units while taking into account of the total coal consumption of units, constraint of thermal energy storage and electricity-heat characteristic of CHP. This paper uses MICA to solve the problem of too many constraints and make the solution more feasible. A numerical example showed that the two stage decision scheduling model can consume more wind power, and it could provide a reference for combined heat and power system short-term operation

Dynamic Sensor Networks

DTIC Science & Technology

2004-03-01

turned off. SLEEP Set the timer for 30 seconds before scheduled transmit time, then sleep the processor. WAKE When timer trips, power up the processor...slots where none of its neighbors are schedule to transmit. This allows the sensor nodes to perform a simple power man- agement scheme that puts the...routing This simple case study highlights the following crucial observation: optimal traffic scheduling in energy constrained networks requires future

Real-time scheduling faces operational challenges.

PubMed

2005-01-01

Online real-time patient scheduling presents a number of challenges. But a few advanced organizations are rolling out systems slowly, meeting those challenges as they go. And while this application is still too new to provide measurable benefits, anecdotal information seems to point to improvements in efficiency, patient satisfaction, and possibly quality of care.

Time-Decayed User Profile for Second Language Vocabulary Learning System

ERIC Educational Resources Information Center

Li, Li; Wei, Xiao

2014-01-01

Vocabulary learning is the foundation of second language learning. Many E-learning systems have been developed to help learners to learn vocabulary efficiently. Most of these systems employ Ebbinghaus Forgetting Curve to make the review schedule for learners. However, learners are different in learning ability and the review schedule based on…

46 CFR Sec. 3 - Terminal operating contract.

Code of Federal Regulations, 2010 CFR

2010-10-01

... specifically described in Schedule A hereto attached and made a part hereof by reference, and at such other... performed under this agreement in an economical and efficient manner and in accordance with the best... attached and made a part hereof by reference) and such other schedules or writing as may be made by the...

Operational ET remote sensing (RS) program for irrigation scheduling and management: challenges and opportunities

Treesearch

Prasanna Gowda

2016-01-01

Evapotranspiration (ET) is an essential component of the water balance and a major consumptive use of irrigation water and precipitation on cropland. Any attempt to improve water use efficiency must be based on reliable estimates of ET for irrigation scheduling purposes.

One for All: Maintaining a Single Schedule Database for Large Development Projects

NASA Technical Reports Server (NTRS)

Hilscher, R.; Howerton, G.

1999-01-01

Efficiently maintaining and controlling a single schedule database in an Integrated Product Team environment is a significant challenge. It's accomplished effectively with the right combination of tools, skills, strategy, creativity, and teamwork. We'll share our lessons learned maintaining a 20,000 plus task network on a 36 month project.

Automation Improves Schedule Quality and Increases Scheduling Efficiency for Residents.

PubMed

Perelstein, Elizabeth; Rose, Ariella; Hong, Young-Chae; Cohn, Amy; Long, Micah T

2016-02-01

Medical resident scheduling is difficult due to multiple rules, competing educational goals, and ever-evolving graduate medical education requirements. Despite this, schedules are typically created manually, consuming hours of work, producing schedules of varying quality, and yielding negative consequences for resident morale and learning. To determine whether computerized decision support can improve the construction of residency schedules, saving time and improving schedule quality. The Optimized Residency Scheduling Assistant was designed by a team from the University of Michigan Department of Industrial and Operations Engineering. It was implemented in the C.S. Mott Children's Hospital Pediatric Emergency Department in the 2012-2013 academic year. The 4 metrics of schedule quality that were compared between the 2010-2011 and 2012-2013 academic years were the incidence of challenging shift transitions, the incidence of shifts following continuity clinics, the total shift inequity, and the night shift inequity. All scheduling rules were successfully incorporated. Average schedule creation time fell from 22 to 28 hours to 4 to 6 hours per month, and 3 of 4 metrics of schedule quality significantly improved. For the implementation year, the incidence of challenging shift transitions decreased from 83 to 14 (P < .01); the incidence of postclinic shifts decreased from 72 to 32 (P < .01); and the SD of night shifts dropped by 55.6% (P < .01). This automated shift scheduling system improves the current manual scheduling process, reducing time spent and improving schedule quality. Embracing such automated tools can benefit residency programs with shift-based scheduling needs.

Effects of workload preview on task scheduling during simulated instrument flight.

PubMed

Andre, A D; Heers, S T; Cashion, P A

1995-01-01

Our study examined pilot scheduling behavior in the context of simulated instrument flight. Over the course of the flight, pilots flew along specified routes while scheduling and performing several flight-related secondary tasks. The first phase of flight was flown under low-workload conditions, whereas the second phase of flight was flown under high-workload conditions in the form of increased turbulence and a disorganized instrument layout. Six pilots were randomly assigned to each of three workload preview groups. Subjects in the no-preview group were not given preview of the increased-workload conditions. Subjects in the declarative preview group were verbally informed of the nature of the flight workload manipulation but did not receive any practice under the high-workload conditions. Subjects in the procedural preview group received the same instructions as the declarative preview group but also flew half of the practice flight under the high-workload conditions. The results show that workload preview fostered efficient scheduling strategies. Specifically, those pilots with either declarative or procedural preview of future workload demands adopted an efficient strategy of scheduling more of the difficult secondary tasks during the low-workload phase of flight. However, those pilots given a procedural preview showed the greatest benefits in overall flight performance.

Spike: Artificial intelligence scheduling for Hubble space telescope

NASA Technical Reports Server (NTRS)

Johnston, Mark; Miller, Glenn; Sponsler, Jeff; Vick, Shon; Jackson, Robert

1990-01-01

Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains.

The Development of Patient Scheduling Groups for an Effective Appointment System

PubMed Central

2016-01-01

Summary Background Patient access to care and long wait times has been identified as major problems in outpatient delivery systems. These aspects impact medical staff productivity, service quality, clinic efficiency, and health-care cost. Objectives This study proposed to redesign existing patient types into scheduling groups so that the total cost of clinic flow and scheduling flexibility was minimized. The optimal scheduling group aimed to improve clinic efficiency and accessibility. Methods The proposed approach used the simulation optimization technique and was demonstrated in a Primary Care physician clinic. Patient type included, emergency/urgent care (ER/UC), follow-up (FU), new patient (NP), office visit (OV), physical exam (PE), and well child care (WCC). One scheduling group was designed for this physician. The approach steps were to collect physician treatment time data for each patient type, form the possible scheduling groups, simulate daily clinic flow and patient appointment requests, calculate costs of clinic flow as well as appointment flexibility, and find the scheduling group that minimized the total cost. Results The cost of clinic flow was minimized at the scheduling group of four, an 8.3% reduction from the group of one. The four groups were: 1. WCC, 2. OV, 3. FU and ER/UC, and 4. PE and NP. The cost of flexibility was always minimized at the group of one. The total cost was minimized at the group of two. WCC was considered separate and the others were grouped together. The total cost reduction was 1.3% from the group of one. Conclusions This study provided an alternative method of redesigning patient scheduling groups to address the impact on both clinic flow and appointment accessibility. Balance between them ensured the feasibility to the recognized issues of patient service and access to care. The robustness of the proposed method on the changes of clinic conditions was also discussed. PMID:27081406

10 CFR 434.513 - Occupancy.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 3 2011-01-01 2011-01-01 false Occupancy. 434.513 Section 434.513 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY CODE FOR NEW FEDERAL COMMERCIAL AND MULTI-FAMILY HIGH RISE RESIDENTIAL BUILDINGS Building Energy Cost Compliance Alternative § 434.513 Occupancy. 5131Occupancy schedules are...

10 CFR 434.513 - Occupancy.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 3 2014-01-01 2014-01-01 false Occupancy. 434.513 Section 434.513 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY CODE FOR NEW FEDERAL COMMERCIAL AND MULTI-FAMILY HIGH RISE RESIDENTIAL BUILDINGS Building Energy Cost Compliance Alternative § 434.513 Occupancy. 5131 Occupancy schedules are...

10 CFR 434.513 - Occupancy.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 3 2013-01-01 2013-01-01 false Occupancy. 434.513 Section 434.513 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY CODE FOR NEW FEDERAL COMMERCIAL AND MULTI-FAMILY HIGH RISE RESIDENTIAL BUILDINGS Building Energy Cost Compliance Alternative § 434.513 Occupancy. 5131Occupancy schedules are...

10 CFR 434.513 - Occupancy.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 3 2012-01-01 2012-01-01 false Occupancy. 434.513 Section 434.513 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY CODE FOR NEW FEDERAL COMMERCIAL AND MULTI-FAMILY HIGH RISE RESIDENTIAL BUILDINGS Building Energy Cost Compliance Alternative § 434.513 Occupancy. 5131Occupancy schedules are...

Lunar and Artificial Satellite Laser Ranging: The Use of Queue Scheduling and Worth Functions to Maximize Scientific Results

NASA Astrophysics Data System (ADS)

Shelus, P. J.; Ricklefs, R. L.; Wiant, J. R.; Ries, J. G.

2003-08-01

The lunar and artificial satellite laser ranging network, part of the International Laser Ranging Service, monitors a large number of targets. Many scientific disciplines are investigated using these data. These include the realization and maintenance of the International Terrestrial Reference Frame; the 3-dimensional deformation of the solid Earth; Earth orientation; variations in the topography and volume of the liquid Earth, including ocean circulation, mean sea level, ice sheet thickness, and wave heights; tidally generated variations in atmospheric mass distribution; calibration of microwave tracking techniques; picosecond global time transfer; determination of the dynamic equinox, the obliquity of the ecliptic, the precession constant and theories of nutation; gravitational and general relativistic studies, including Einstein's Equivalence Principle, the Robertson-Walker b parameter and time rate of change of the gravitational constant; lunar physics, including the dissipation of rotational energy, shape of the core-mantle boundary (Love Number k2), and free librations and their stimulating mechanisms; Solar System ties to the International Celestial Reference Frame. With shrinking resources, we must not only assess specific data requirements for each target, but also maximize the efficiency of the observing network. Several factors must be considered. First, not only does a result depend critically upon the quality and quantity of the data, it also depends upon the data distribution. Second, as technology improves, the cost of obtaining data can increase. Both require that scientific endeavor pay close attention to the manner in which the data is gathered. We examine the evolution of the laser network, using data analysis requirements and efficient network scheduling to maximize the scientific return. This requires an understanding of the observing equipment, as well as the scientific principles being studied. Queue scheduling and worth functions become important. This work is funded by: NSF AST-0204127, NASA NAG5-10195, NAS5-01096, NAG5-11464.

Spitzer Operations: Scheduling the Out Years

NASA Technical Reports Server (NTRS)

Mahoney, William A.; Effertz, Mark J.; Fisher, Mark E.; Garcia, Lisa J.; Hunt, Joseph C. Jr.; Mannings, Vincent; McElroy, Douglas B.; Scire, Elena

2012-01-01

Spitzer Warm Mission operations have remained robust and exceptionally efficient since the cryogenic mission ended in mid-2009. The distance to the now exceeds 1 AU, making telecommunications increasingly difficult; however, analysis has shown that two-way communication could be maintained through at least 2017 with minimal loss in observing efficiency. The science program continues to emphasize the characterization of exoplanets, time domain studies, and deep surveys, all of which can impose interesting scheduling constraints. Recent changes have significantly improved on-board data compression, which both enables certain high volume observations and reduces Spitzer's demand for competitive Deep Space Network resources.

Scheduling Software for Complex Scenarios

NASA Technical Reports Server (NTRS)

2006-01-01

Preparing a vehicle and its payload for a single launch is a complex process that involves thousands of operations. Because the equipment and facilities required to carry out these operations are extremely expensive and limited in number, optimal assignment and efficient use are critically important. Overlapping missions that compete for the same resources, ground rules, safety requirements, and the unique needs of processing vehicles and payloads destined for space impose numerous constraints that, when combined, require advanced scheduling. Traditional scheduling systems use simple algorithms and criteria when selecting activities and assigning resources and times to each activity. Schedules generated by these simple decision rules are, however, frequently far from optimal. To resolve mission-critical scheduling issues and predict possible problem areas, NASA historically relied upon expert human schedulers who used their judgment and experience to determine where things should happen, whether they will happen on time, and whether the requested resources are truly necessary.

A method of operation scheduling based on video transcoding for cluster equipment

NASA Astrophysics Data System (ADS)

Zhou, Haojie; Yan, Chun

2018-04-01

Because of the cluster technology in real-time video transcoding device, the application of facing the massive growth in the number of video assignments and resolution and bit rate of diversity, task scheduling algorithm, and analyze the current mainstream of cluster for real-time video transcoding equipment characteristics of the cluster, combination with the characteristics of the cluster equipment task delay scheduling algorithm is proposed. This algorithm enables the cluster to get better performance in the generation of the job queue and the lower part of the job queue when receiving the operation instruction. In the end, a small real-time video transcode cluster is constructed to analyze the calculation ability, running time, resource occupation and other aspects of various algorithms in operation scheduling. The experimental results show that compared with traditional clustering task scheduling algorithm, task delay scheduling algorithm has more flexible and efficient characteristics.

Two-machine flow shop scheduling integrated with preventive maintenance planning

NASA Astrophysics Data System (ADS)

Wang, Shijin; Liu, Ming

2016-02-01

This paper investigates an integrated optimisation problem of production scheduling and preventive maintenance (PM) in a two-machine flow shop with time to failure of each machine subject to a Weibull probability distribution. The objective is to find the optimal job sequence and the optimal PM decisions before each job such that the expected makespan is minimised. To investigate the value of integrated scheduling solution, computational experiments on small-scale problems with different configurations are conducted with total enumeration method, and the results are compared with those of scheduling without maintenance but with machine degradation, and individual job scheduling combined with independent PM planning. Then, for large-scale problems, four genetic algorithm (GA) based heuristics are proposed. The numerical results with several large problem sizes and different configurations indicate the potential benefits of integrated scheduling solution and the results also show that proposed GA-based heuristics are efficient for the integrated problem.

Comparison of 2-Dose and 3-Dose 9-Valent Human Papillomavirus Vaccine Schedules in the United States: A Cost-effectiveness Analysis.

PubMed

Laprise, Jean-François; Markowitz, Lauri E; Chesson, Harrell W; Drolet, Mélanie; Brisson, Marc

2016-09-01

A recent clinical trial using the 9-valent human papillomavirus virus (HPV) vaccine has shown that antibody responses after 2 doses are noninferior to those after 3 doses, suggesting that 2 and 3 doses may have comparable vaccine efficacy. We used an individual-based transmission-dynamic model to compare the population-level effectiveness and cost-effectiveness of 2- and 3-dose schedules of 9-valent HPV vaccine in the United States. Our model predicts that if 2 doses of 9-valent vaccine protect for ≥20 years, the additional benefits of a 3-dose schedule are small as compared to those of 2-dose schedules, and 2-dose schedules are likely much more cost-efficient than 3-dose schedules. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Energy intake and energy expenditure of pre-professional female contemporary dancers

PubMed Central

Brown, Meghan A.; Howatson, Glyn; Quin, Edel; Redding, Emma; Stevenson, Emma J.

2017-01-01

Many athletes in aesthetic and weight dependent sports are at risk of energy imbalance. However little is known about the exercise and eating behaviours of highly trained dance populations. This investigation sought to determine the energy intake and energy expenditure of pre-professional female contemporary dancers. Twenty-five female contemporary dance students completed the study. Over a 7-day period, including five week days (with scheduled dance training at a conservatoire) and two weekend days (with no scheduled dance training at the conservatoire), energy intake (self-reported weighed food diary and 24 h dietary recall) and expenditure (tri-axial accelerometry) were recorded. Mean daily energy intake and expenditure were different over the 7-day period (P = 0.014) equating to an energy deficit of -356 ± 668 kcal·day-1 (or -1.5 ± 2.8 MJ·day-1). Energy expenditure was not different when comparing week and weekend days (P = 0.297). However daily energy intake (P = 0.002), energy availability (P = 0.003), and energy balance (P = 0.004) were lower during the week compared to the weekend, where energy balance became positive. The percentage contribution of macronutrients to total energy intake also differed; with higher fat (P = 0.022) and alcohol (P = 0.020), and lower carbohydrate (P = 0.001) and a trend for lower protein (P = 0.051) at the weekend. Energy balance and appropriate macronutrient intake are essential for maintaining the demands of training, performance and recovery. Whilst aesthetics are important, female contemporary dancers may be at risk of the numerous health and performance impairments associated with negative energy balance, particularly during periods of scheduled training. PMID:28212449

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

PubMed Central

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-01-01

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H2RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H2RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller. PMID:28672856

26 CFR 1.48-9 - Definition of energy property.

Code of Federal Regulations, 2011 CFR

2011-04-01

... on Form 3468, Schedule B. The 6 categories of energy property are: (i) Alternative energy property... thermal energy, fossil fuel, or wood, is not considered solar energy property. (2) Passive solar excluded... generate electricity (but not mechanical forms of energy). (f) Specially defined energy property—(1) In...

26 CFR 1.48-9 - Definition of energy property.

Code of Federal Regulations, 2010 CFR

2010-04-01

... on Form 3468, Schedule B. The 6 categories of energy property are: (i) Alternative energy property... thermal energy, fossil fuel, or wood, is not considered solar energy property. (2) Passive solar excluded... generate electricity (but not mechanical forms of energy). (f) Specially defined energy property—(1) In...

26 CFR 1.48-9 - Definition of energy property.

Code of Federal Regulations, 2014 CFR

2014-04-01

... on Form 3468, Schedule B. The 6 categories of energy property are: (i) Alternative energy property... thermal energy, fossil fuel, or wood, is not considered solar energy property. (2) Passive solar excluded... generate electricity (but not mechanical forms of energy). (f) Specially defined energy property—(1) In...

26 CFR 1.48-9 - Definition of energy property.

Code of Federal Regulations, 2012 CFR

2012-04-01

... on Form 3468, Schedule B. The 6 categories of energy property are: (i) Alternative energy property... thermal energy, fossil fuel, or wood, is not considered solar energy property. (2) Passive solar excluded... generate electricity (but not mechanical forms of energy). (f) Specially defined energy property—(1) In...

26 CFR 1.48-9 - Definition of energy property.

Code of Federal Regulations, 2013 CFR

2013-04-01

... on Form 3468, Schedule B. The 6 categories of energy property are: (i) Alternative energy property... thermal energy, fossil fuel, or wood, is not considered solar energy property. (2) Passive solar excluded... generate electricity (but not mechanical forms of energy). (f) Specially defined energy property—(1) In...

A computer method for schedule processing and quick-time updating.

NASA Technical Reports Server (NTRS)

Mccoy, W. H.

1972-01-01

A schedule analysis program is presented which can be used to process any schedule with continuous flow and with no loops. Although generally thought of as a management tool, it has applicability to such extremes as music composition and computer program efficiency analysis. Other possibilities for its use include the determination of electrical power usage during some operation such as spacecraft checkout, and the determination of impact envelopes for the purpose of scheduling payloads in launch processing. At the core of the described computer method is an algorithm which computes the position of each activity bar on the output waterfall chart. The algorithm is basically a maximal-path computation which gives to each node in the schedule network the maximal path from the initial node to the given node.

Short-term scheduling of crude oil operations in refinery with high-fusion-point oil and two transportation pipelines

NASA Astrophysics Data System (ADS)

Wu, NaiQi; Zhu, MengChu; Bai, LiPing; Li, ZhiWu

2016-07-01

In some refineries, storage tanks are located at two different sites, one for low-fusion-point crude oil and the other for high one. Two pipelines are used to transport different oil types. Due to the constraints resulting from the high-fusion-point oil transportation, it is challenging to schedule such a system. This work studies the scheduling problem from a control-theoretic perspective. It proposes to use a hybrid Petri net method to model the system. It then finds the schedulability conditions by analysing the dynamic behaviour of the net model. Next, it proposes an efficient scheduling method to minimize the cost of high-fusion-point oil transportation. Finally, it gives a complex industrial case study to show its application.

The Associate Principal Astronomer for AI Management of Automatic Telescopes

NASA Technical Reports Server (NTRS)

Henry, Gregory W.

1998-01-01

This research program in scheduling and management of automatic telescopes had the following objectives: 1. To field test the 1993 Automatic Telescope Instruction Set (ATIS93) programming language, which was specifically developed to allow real-time control of an automatic telescope via an artificial intelligence scheduler running on a remote computer. 2. To develop and test the procedures for two-way communication between a telescope controller and remote scheduler via the Internet. 3. To test various concepts in Al scheduling being developed at NASA Ames Research Center on an automatic telescope operated by Tennessee State University at the Fairborn Observatory site in southern Arizona. and 4. To develop a prototype software package, dubbed the Associate Principal Astronomer, for the efficient scheduling and management of automatic telescopes.

Development of a fuel cell plug-in hybrid electric vehicle and vehicle simulator for energy management assessment

NASA Astrophysics Data System (ADS)

Meintz, Andrew Lee

This dissertation offers a description of the development of a fuel cell plug-in hybrid electric vehicle focusing on the propulsion architecture selection, propulsion system control, and high-level energy management. Two energy management techniques have been developed and implemented for real-time control of the vehicle. The first method is a heuristic method that relies on a short-term moving average of the vehicle power requirements. The second method utilizes an affine function of the short-term and long-term moving average vehicle power requirements. The development process of these methods has required the creation of a vehicle simulator capable of estimating the effect of changes to the energy management control techniques on the overall vehicle energy efficiency. Furthermore, the simulator has allowed for the refinement of the energy management methods and for the stability of the method to be analyzed prior to on-road testing. This simulator has been verified through on-road testing of a constructed prototype vehicle under both highway and city driving schedules for each energy management method. The results of the finalized vehicle control strategies are compared with the simulator predictions and an assessment of the effectiveness of both strategies is discussed. The methods have been evaluated for energy consumption in the form of both hydrogen fuel and stored electricity from grid charging.

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.

Multiresource allocation and scheduling for periodic soft real-time applications

NASA Astrophysics Data System (ADS)

Gopalan, Kartik; Chiueh, Tzi-cker

2001-12-01

Real-time applications that utilize multiple system resources, such as CPU, disks, and network links, require coordinated scheduling of these resources in order to meet their end-to-end performance requirements. Most state-of-the-art operating systems support independent resource allocation and deadline-driven scheduling but lack coordination among multiple heterogeneous resources. This paper describes the design and implementation of an Integrated Real-time Resource Scheduler (IRS) that performs coordinated allocation and scheduling of multiple heterogeneous resources on the same machine for periodic soft real-time application. The principal feature of IRS is a heuristic multi-resource allocation algorithm that reserves multiple resources for real-time applications in a manner that can maximize the number of applications admitted into the system in the long run. At run-time, a global scheduler dispatches the tasks of the soft real-time application to individual resource schedulers according to the precedence constraints between tasks. The individual resource schedulers, which could be any deadline based schedulers, can make scheduling decisions locally and yet collectively satisfy a real-time application's performance requirements. The tightness of overall timing guarantees is ultimately determined by the properties of individual resource schedulers. However, IRS maximizes overall system resource utilization efficiency by coordinating deadline assignment across multiple tasks in a soft real-time application.

Resource utilization in surgery after the revision of surgical fee schedule in Japan.

PubMed

Nakata, Yoshinori; Yoshimura, Tatsuya; Watanabe, Yuichi; Otake, Hiroshi; Oiso, Giichiro; Sawa, Tomohiro

2015-01-01

The purpose of this paper is to examine whether the current surgical reimbursement system in Japan reflects resource utilization after the revision of fee schedule in 2014. The authors collected data from all the surgical procedures performed at Teikyo University Hospital from April 1 through September 30, 2014. The authors defined the decision-making unit as a surgeon with the highest academic rank in the surgery. Inputs were defined as the number of medical doctors who assisted surgery, and the time of operation from skin incision to closure. An output was defined as the surgical fee. The authors calculated surgeons' efficiency scores using data envelopment analysis. The efficiency scores of each surgical specialty were significantly different (p=0.000). This result demonstrates that the Japanese surgical reimbursement scales still fail to reflect resource utilization despite the revision of surgical fee schedule.

Resource Control in Large-Scale Mobile-Agents Systems

DTIC Science & Technology

2005-07-01

wakeup node schedule , much energy can be conserved. We also designed several protocols for global clock synchronization. The most interesting one is...choice as to which remote hosts to visit and in which order. Scheduling mobile-agent migration in a way that minimizes bandwidth and other resource...use, therefore, is both feasible and attractive. Dartmouth considered several variations of the scheduling problem, and devel- oped an algorithm for

Scheduling Independent Partitions in Integrated Modular Avionics Systems

PubMed Central

Du, Chenglie; Han, Pengcheng

2016-01-01

Recently the integrated modular avionics (IMA) architecture has been widely adopted by the avionics industry due to its strong partition mechanism. Although the IMA architecture can achieve effective cost reduction and reliability enhancement in the development of avionics systems, it results in a complex allocation and scheduling problem. All partitions in an IMA system should be integrated together according to a proper schedule such that their deadlines will be met even under the worst case situations. In order to help provide a proper scheduling table for all partitions in IMA systems, we study the schedulability of independent partitions on a multiprocessor platform in this paper. We firstly present an exact formulation to calculate the maximum scaling factor and determine whether all partitions are schedulable on a limited number of processors. Then with a Game Theory analogy, we design an approximation algorithm to solve the scheduling problem of partitions, by allowing each partition to optimize its own schedule according to the allocations of the others. Finally, simulation experiments are conducted to show the efficiency and reliability of the approach proposed in terms of time consumption and acceptance ratio. PMID:27942013

Scheduling nurses’ shifts at PGI Cikini Hospital

NASA Astrophysics Data System (ADS)

Nainggolan, J. C. T.; Kusumastuti, R. D.

2018-03-01

Hospitals play an essential role in the community by providing medical services to the public. In order to provide high quality medical services, hospitals must manage their resources (including nurses) effectively and efficiently. Scheduling of nurses’ work shifts, in particular, is crucial, and must be conducted carefully to ensure availability and fairness. This research discusses the job scheduling system for nurses in PGI Cikini Hospital, Jakarta with Goal Programming approach. The research objectives are to identify nurse scheduling criteria and find the best schedule that can meet the criteria. The model has hospital regulations (including government regulations) as hard constraints, and nurses’ preferences as soft constraints. We gather primary data (hospital regulations and nurses’ preferences) through interviews with three Head Nurses and distributing questionnaires to fifty nurses. The results show that on the best schedule, all hard constraints can be satisfied. However, only two out of four soft constraints are satisfied. Compared to current scheduling practice, the resulting schedule ensures the availability of nurses as it satisfies all hospital’s regulations and it has a higher level of fairness as it can accommodate some of the nurses’ preferences.

Representations and evolutionary operators for the scheduling of pump operations in water distribution networks.

PubMed

López-Ibáñez, Manuel; Prasad, T Devi; Paechter, Ben

2011-01-01

Reducing the energy consumption of water distribution networks has never had more significance. The greatest energy savings can be obtained by carefully scheduling the operations of pumps. Schedules can be defined either implicitly, in terms of other elements of the network such as tank levels; or explicitly, by specifying the time during which each pump is on/off. The traditional representation of explicit schedules is a string of binary values with each bit representing pump on/off status during a particular time interval. In this paper, we formally define and analyze two new explicit representations based on time-controlled triggers, where the maximum number of pump switches is established beforehand and the schedule may contain fewer than the maximum number of switches. In these representations, a pump schedule is divided into a series of integers with each integer representing the number of hours for which a pump is active/inactive. This reduces the number of potential schedules compared to the binary representation, and allows the algorithm to operate on the feasible region of the search space. We propose evolutionary operators for these two new representations. The new representations and their corresponding operations are compared with the two most-used representations in pump scheduling, namely, binary representation and level-controlled triggers. A detailed statistical analysis of the results indicates which parameters have the greatest effect on the performance of evolutionary algorithms. The empirical results show that an evolutionary algorithm using the proposed representations is an improvement over the results obtained by a recent state of the art hybrid genetic algorithm for pump scheduling using level-controlled triggers.

A Note on Improving Process Efficiency in Panel Surveys with Paradata

ERIC Educational Resources Information Center

Kreuter, Frauke; Müller, Gerrit

2015-01-01

Call scheduling is a challenge for surveys around the world. Unlike cross-sectional surveys, panel surveys can use information from prior waves to enhance call-scheduling algorithms. Past observational studies showed the benefit of calling panel cases at times that had been successful in the past. This article is the first to experimentally assign…

Impacts of Scheduling Recess before Lunch in Elementary Schools: A Case Study Approach of Plate Waste and Perceived Behaviors

ERIC Educational Resources Information Center

Strohbehn, Catherine H.; Strohbehn, Garth W.; Lanningham-Foster, Lorraine; Litchfield, Ruth A.; Scheidel, Carrie; Delger, Patti

2016-01-01

Purpose/Objectives: Recess Before Lunch (RBL) for elementary students is considered a best practice related to increased nutrient intakes at lunch, decreased afternoon behavioral issues, and increased afternoon learning efficiency; however, school characteristics, such as amount of time for lunch, offer vs. serve, and scheduling factors can…

Scenario analysis and path selection of low-carbon transformation in China based on a modified IPAT model.

PubMed

Chen, Liang; Yang, Zhifeng; Chen, Bin

2013-01-01

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40-45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China's low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance.

Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model

PubMed Central

Chen, Liang; Yang, Zhifeng; Chen, Bin

2013-01-01

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40–45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China’s low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance. PMID:24204922

A Shaftless Magnetically Levitated Multifunctional Spacecraft Flywheel Storage System

NASA Technical Reports Server (NTRS)

Stevens, Ken; Thornton, Richard; Clark, Tracy; Beaman, Bob G.; Dennehy, Neil; Day, John H. (Technical Monitor)

2002-01-01

Presently many types of spacecraft use a Spacecraft Attitude Control System (ACS) with momentum wheels for steering and electrochemical batteries to provide electrical power for the eclipse period of the spacecraft orbit. Future spacecraft will use Flywheels for combined use in ACS and Energy Storage. This can be done by using multiple wheels and varying the differential speed for ACS and varying the average speed for energy storage and recovery. Technology in these areas has improved since the 1990s so it is now feasible for flywheel systems to emerge from the laboratory for spacecraft use. This paper describes a new flywheel system that can be used for both ACS and energy storage. Some of the possible advantages of a flywheel system are: lower total mass and volume, higher efficiency, less thermal impact, improved satellite integration schedule and complexity, simplified satellite orbital operations, longer life with lower risk, less pointing jitter, and greater capability for high-rate slews. In short, they have the potential to enable new types of missions and provide lower cost. Two basic types of flywheel configurations are the Flywheel Energy Storage System (FESS) and the Integrated Power and Attitude Control System (IPACS).

Flexible operation of batteries in power system scheduling with renewable energy

DOE PAGES

Li, Nan; Uckun, Canan; Constantinescu, Emil M.; ...

2015-12-17

The fast growing expansion of renewable energy increases the complexities in balancing generation and demand in the power system. The energy-shifting and fast-ramping capability of energy storage has led to increasing interests in batteries to facilitate the integration of renewable resources. In this paper, we present a two-step framework to evaluate the potential value of energy storage in power systems with renewable generation. First, we formulate a stochastic unit commitment approach with wind power forecast uncertainty and energy storage. Second, the solution from the stochastic unit commitment is used to derive a flexible schedule for energy storage in economic dispatchmore » where the look-ahead horizon is limited. Here, analysis is conducted on the IEEE 24-bus system to demonstrate the benefits of battery storage in systems with renewable resources and the effectiveness of the proposed battery operation strategy.« less