Sample records for logistics demand model

  1. EIA model documentation: World oil refining logistics demand model,``WORLD`` reference manual. Version 1.1

    SciTech Connect (OSTI)

    Not Available

    1994-04-11T23:59:59.000Z

    This manual is intended primarily for use as a reference by analysts applying the WORLD model to regional studies. It also provides overview information on WORLD features of potential interest to managers and analysts. Broadly, the manual covers WORLD model features in progressively increasing detail. Section 2 provides an overview of the WORLD model, how it has evolved, what its design goals are, what it produces, and where it can be taken with further enhancements. Section 3 reviews model management covering data sources, managing over-optimization, calibration and seasonality, check-points for case construction and common errors. Section 4 describes in detail the WORLD system, including: data and program systems in overview; details of mainframe and PC program control and files;model generation, size management, debugging and error analysis; use with different optimizers; and reporting and results analysis. Section 5 provides a detailed description of every WORLD model data table, covering model controls, case and technology data. Section 6 goes into the details of WORLD matrix structure. It provides an overview, describes how regional definitions are controlled and defines the naming conventions for-all model rows, columns, right-hand sides, and bounds. It also includes a discussion of the formulation of product blending and specifications in WORLD. Several Appendices supplement the main sections.

  2. Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Logistics Logistics The review will be held at the Hyatt Regency Bethesda for all of April 29 and in the morning of April 30, finishing with lunch from 12-1pm. MAKING RESERVATIONS...

  3. Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickrinformationPostdocsCenterCentera A B C D E FLogging inLogistics

  4. Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickrinformationPostdocsCenterCentera A B C D E FLoggingLogistics User

  5. Reducing Logistics Footprints and Replenishment Demands: Nano-engineered Silica Aerogels a Proven Method for Water Treatment

    SciTech Connect (OSTI)

    Daily, W; Coleman, S; Love, A; Reynolds, J; O'Brien, K; Gammon, S

    2004-09-22T23:59:59.000Z

    Rapid deployment and the use of objective force aggressively reduce logistic footprints and replenishment demands. Maneuver Sustainment requires that Future Combat Systems be equipped with water systems that are lightweight, have small footprints, and are highly adaptable to a variety of environments. Technologies employed in these settings must be able to meet these demands. Lawrence Livermore National Laboratory has designed and previously field tested nano-engineered materials for the treatment of water. These materials have been either based on silica aerogel materials or consist of composites of these aerogels with granular activated carbon (GAC). Recent tests have proven successful for the removal of contaminants including uranium, hexavalent chromium, and arsenic. Silica aerogels were evaluated for their ability to purify water that had been spiked with the nerve agent VX (O-ethyl S-(2-diisopropylaminoethyl) methylphosphonothiolate). These results demonstrated that silica aerogels were able to remove the VX from the supply water and were nearly 30 times more adsorbent than GAC. This performance could result in REDUCING CHANGEOUT FREQUENCY BY A FACTOR OF 30 or DECREASING the VOLUME of adsorbent BY A FACTOR OF 30; thereby significantly reducing logistic footprints and replenishment demands. The use of the nano-engineered Silica Aerogel/GAC composites would provide a water purification technology that meets the needs of Future Combat Systems.

  6. Modeling Energy Demand Aggregators for Residential Consumers

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Modeling Energy Demand Aggregators for Residential Consumers G. Di Bella, L. Giarr`e, M. Ippolito, A. Jean-Marie, G. Neglia and I. Tinnirello § January 2, 2014 Abstract Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand

  7. Construction Logistics Improvements using the SCOR model Tornet Case

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Construction Logistics Improvements using the SCOR model ­Tornet Case Fredrik Persson1 , Jonas over the last decades. Initiatives such as Lean Construction and Prefabrication have emerged in the construction industry to reduce the cost of house production and thereby the cost of the house itself

  8. A flexible, modular approach to integrated space exploration campaign logistics modeling, simulation, and analysis

    E-Print Network [OSTI]

    Grogan, Paul Thomas, 1985-

    2010-01-01T23:59:59.000Z

    A space logistics modeling framework to support space exploration to remote environments is the target of research within the MIT Space Logistics Project. This thesis presents a revised and expanded framework providing ...

  9. Market Response ModelsMarket Response Models Demand CreationDemand Creation

    E-Print Network [OSTI]

    Brock, David

    Market Response ModelsMarket Response Models andand Demand CreationDemand Creation Dominique MImportance of Marketing Investments Need for a Market Response focusNeed for a Market Response focus Digital data enriched acquisition and retention costsasymmetry between acquisition and retention costs In both cases, longIn both

  10. Univariate Modeling and Forecasting of Monthly Energy Demand Time Series

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural demand time series based only on data for six years to forecast the demand for the seventh year. Both networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system

  11. CE 469 / 569 TRAVEL DEMAND MODELING Spring 2006 Course Syllabus

    E-Print Network [OSTI]

    Hickman, Mark

    of travel demand data, and should apply these methods to estimating and to forecasting travel demand these to practical modeling scenarios. The student should also use existing computer tools to forecast travel demand1 CE 469 / 569 TRAVEL DEMAND MODELING Spring 2006 Course Syllabus Catalog Detailed investigation

  12. A Logistic Branching Process Alternative to the Wright-Fisher Model R. B. Campbell

    E-Print Network [OSTI]

    Campbell, Russell Bruce

    A Logistic Branching Process Alternative to the Wright-Fisher Model R. B. Campbell Department, Population Regulation Introduction Most of the theoretical work in population genetics is based on the Wright approximation to the Wright-Fisher model. A logistic branching process is introduced in order to limit

  13. Modeling supermarket refrigeration energy use and demand

    SciTech Connect (OSTI)

    Blatt, M.H.; Khattar, M.K. (Electric Power Research Inst., Palo Alto, CA (US)); Walker, D.H. (Foster Miller Inc., Waltham, MA (US))

    1991-07-01T23:59:59.000Z

    A computer model has been developed that can predict the performance of supermarket refrigeration equipment to within 3% of field test measurements. The Supermarket Refrigeration Energy Use and Demand Model has been used to simulate currently available refrigerants R-12, R-502 and R-22, and is being further developed to address alternative refrigerants. This paper reports that the model is expected to be important in the design, selection and operation of cost-effective, high-efficiency refrigeration systems. It can profile the operation and performance of different types of compressors, condensors, refrigerants and display cases. It can also simulate the effects of store humidity and temperature on display cases; the efficiency of various floating head pressure setpoints, defrost alternatives and subcooling methods; the efficiency and amount of heat reclaim from refrigeration systems; and the influence of other variables such as store lighting and building design. It can also be used to evaluate operational strategies such as variable-speed drive or cylinder unloading for capacity control. Development of the model began in 1986 as part of a major effort, sponsored by the U.S. electric utility industry, to evaluate energy performance of then conventional single compressor and state-of-the-art multiplex refrigeration systems, and to characterize the contribution of a variety of technology enhancement features on system energy use and demand.

  14. Two Market Models for Demand Response in Power Networks

    E-Print Network [OSTI]

    Low, Steven H.

    Two Market Models for Demand Response in Power Networks Lijun Chen, Na Li, Steven H. Low and John C-- In this paper, we consider two abstract market models for designing demand response to match power supply as oligopolistic markets, and propose distributed demand response algorithms to achieve the equilibria. The models

  15. Mining customer credit by using neural network model with logistic regression approach

    E-Print Network [OSTI]

    Kao, Ling-Jing

    2001-01-01T23:59:59.000Z

    . The objective of this research was to investigate the methodologies to mine customer credit history for the bank industry. Particularly, combination of logistic regression model and neural network technique are proposed to determine if the predictive capability...

  16. Logistic regression models for predicting trip reporting accuracy in GPS-enhanced household travel surveys

    E-Print Network [OSTI]

    Forrest, Timothy Lee

    2007-04-25T23:59:59.000Z

    This thesis presents a methodology for conducting logistic regression modeling of trip and household information obtained from household travel surveys and vehicle trip information obtained from global positioning systems (GPS) to better understand...

  17. Independent Demand Models Non Linear (Chemical Industry -take or pay)

    E-Print Network [OSTI]

    Brock, David

    casesshippedperweek #12;High Variability Between Forecast and Actual · Demand in relation to the forecast means almostIndependent Demand Models · Non Linear (Chemical Industry - take or pay) · Deterministic Simulation (make to stock - lumpy demand) · Mathematical Programming (family structure - near optimum) · Heuristic

  18. An Introduction to Semantic Modeling for Logistical Systems

    E-Print Network [OSTI]

    Brock, David

    Infrastructure ­ A Method for Networking Physical Objects," MIT Smart World Conference. · BROCK, D.L. 2003. "The. "Developing and Implementing a Production Planning DSS for CTI Using Structured Modeling." Interfaces 31 models may exist in different host systems and organizations. #12;A Visualization of M #12;Grid Computing

  19. COMBINING DIVERSE DATA SOURCES FOR CEDSS, AN AGENT-BASED MODEL OF DOMESTIC ENERGY DEMAND

    E-Print Network [OSTI]

    Gotts, Nicholas Mark; Polhill, Gary; Craig, Tony; Galan-Diaz, Carlos

    2014-01-01T23:59:59.000Z

    Model CEDSS (Community Energy Demand Social Simulator) wasthe determinants of domestic energy demand and covering fivescenarios of domestic energy demand to 2050, and for its

  20. Letter to the Editor Underestimation of Disease Progress Rates with the Logistic, Monomolecular, and Gompertz Models

    E-Print Network [OSTI]

    Neher, Deborah A.

    , with m as the parameter of shape for infected (or diseased). A corollary to this assumption is that all of underestimation (eq. 4). tissue can expand into healthy tissue. Both of these factors can change with time (24 logistic models (Fig. 1). The effect is examined from both ....09 theoretical and empirical perspectives

  1. MODELING THE DEMAND FOR E85 IN THE UNITED STATES

    SciTech Connect (OSTI)

    Liu, Changzheng [ORNL; Greene, David L [ORNL

    2013-10-01T23:59:59.000Z

    How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

  2. Development of the Integrated Biomass Supply Analysis and Logistics Model (IBSAL)

    SciTech Connect (OSTI)

    Sokhansanj, Shahabaddine [ORNL; Webb, Erin [ORNL; Turhollow Jr, Anthony F [ORNL

    2008-06-01T23:59:59.000Z

    The Integrated Biomass Supply & Logistics (IBSAL) model is a dynamic (time dependent) model of operations that involve collection, harvest, storage, preprocessing, and transportation of feedstock for use at a biorefinery. The model uses mathematical equations to represent individual unit operations. These unit operations can be assembled by the user to represent the working rate of equipment and queues to represent storage at facilities. The model calculates itemized costs, energy input, and carbon emissions. It estimates resource requirements and operational characteristics of the entire supply infrastructure. Weather plays an important role in biomass management and thus in IBSAL, dictating the moisture content of biomass and whether or not it can be harvested on a given day. The model calculates net biomass yield based on a soil conservation allowance (for crop residue) and dry matter losses during harvest and storage. This publication outlines the development of the model and provides examples of corn stover harvest and logistics.

  3. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect (OSTI)

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14T23:59:59.000Z

    Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demand response enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demand response signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

  4. A dynamic model of industrial energy demand in Kenya

    SciTech Connect (OSTI)

    Haji, S.H.H. [Gothenburg Univ. (Sweden)

    1994-12-31T23:59:59.000Z

    This paper analyses the effects of input price movements, technology changes, capacity utilization and dynamic mechanisms on energy demand structures in the Kenyan industry. This is done with the help of a variant of the second generation dynamic factor demand (econometric) model. This interrelated disequilibrium dynamic input demand econometric model is based on a long-term cost function representing production function possibilities and takes into account the asymmetry between variable inputs (electricity, other-fuels and Tabour) and quasi-fixed input (capital) by imposing restrictions on the adjustment process. Variations in capacity utilization and slow substitution process invoked by the relative input price movement justifies the nature of input demand disequilibrium. The model is estimated on two ISIS digit Kenyan industry time series data (1961 - 1988) using the Iterative Zellner generalized least square method. 31 refs., 8 tabs.

  5. Aggregate Model for Heterogeneous Thermostatically Controlled Loads with Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Kalsi, Karanjit; Fuller, Jason C.; Elizondo, Marcelo A.; Chassin, David P.

    2012-07-22T23:59:59.000Z

    Due to the potentially large number of Distributed Energy Resources (DERs) – demand response, distributed generation, distributed storage - that are expected to be deployed, it is impractical to use detailed models of these resources when integrated with the transmission system. Being able to accurately estimate the fast transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies. On the other hand, a less complex model is more amenable to design feedback control strategies for the population of devices to provide ancillary services. The main contribution of this paper is to develop aggregated models for a heterogeneous population of Thermostatic Controlled Loads (TCLs) to accurately capture their collective behavior under demand response and other time varying effects of the system. The aggregated model efficiently includes statistical information of the population and accounts for a second order effect necessary to accurately capture the collective dynamic behavior. The developed aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D (an open source distribution simulation software) under both steady state and severe dynamic conditions caused due to temperature set point changes.

  6. Energy Demand Modelling Introduction to the PhD project

    E-Print Network [OSTI]

    Energy Demand Modelling Introduction to the PhD project Erika Zvingilaite Risø DTU System Analysis for optimization of energy systems Environmental effects Global externalities cost of CO2 Future scenarios for the Nordic energy systems 2010, 2020, 2030, 2040, 2050 (energy-production, consumption, emissions, net costs

  7. Using Utility Information to Calibrate Customer Demand Management Behavior Models

    E-Print Network [OSTI]

    Using Utility Information to Calibrate Customer Demand Management Behavior Models Murat Fahrio ­ Madison Report PSerc 99­06 June 10, 1999 Abstract In times of stress customers can help a utility by means be optimized if the utility can estimate the outage or substitution costs of its customers. This report

  8. Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    Automated Demand Response in a Large Office Building”, CECBuilding Control Strategies and Techniques for Demand Response”,Demand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Buildings

  9. Electric Water Heater Modeling and Control Strategies for Demand Response

    SciTech Connect (OSTI)

    Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

    2012-07-22T23:59:59.000Z

    Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid

  10. Value of Demand Response: Quantities from Production Cost Modeling (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01T23:59:59.000Z

    Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind and solar power generation. However, managed loads in grid models are limited by data availability and modeling complexity. This presentation focuses on the value of co-optimized DR resources to provide energy and ancillary services in a production cost model. There are significant variations in the availabilities of different types of DR resources, which affect both the operational savings as well as the revenue for each DR resource. The results presented include the system-wide avoided fuel and generator start-up costs as well as the composite revenue for each DR resource by energy and operating reserves. In addition, the revenue is characterized by the capacity, energy, and units of DR enabled.

  11. A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS

    E-Print Network [OSTI]

    Dessouky, Maged

    A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS Marco a demand responsive transit service with a predetermined quality for the user in terms of waiting time models; Continuous approximation models; Paratransit services; Demand responsive transit systems. #12;3 1

  12. Supply Chain Logistics Post Recovery Landscape

    E-Print Network [OSTI]

    Minnesota, University of

    .S. Logistics · Land Bridges, Inland ports, Import Warehouses, Plant Locations · Domestic Logistics · Retail / Consumer Demands, Geographic "Mega Regions," Land Prices Impacts, Freight Security / Theft, Network Design Changes · Green Logistics · Green measures, Certifications, Urban Heat Island, Stormwater, Energy

  13. An Operational Model for Optimal NonDispatchable Demand Response

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    FACTS, $ Demand Response Energy Storage HVDC Industrial Customer PEV Renewable Energy Source: U.S.-Canada Power

  14. Space Logistics Modeling and Simulation Analysis using SpaceNet: Four Application Cases

    E-Print Network [OSTI]

    Grogan, Paul Thomas

    The future of space exploration will not be limited to sortie-style missions to single destinations. Even in present exploration taking place at the International Space Station in low-Earth orbit, logistics is complicated ...

  15. A Hierarchical Task Model for Dispatching in Computer-Assisted Demand-Responsive Paratransit Operation

    E-Print Network [OSTI]

    Dessouky, Maged

    A Hierarchical Task Model for Dispatching in Computer- Assisted Demand-Responsive Paratransit Model for Dispatching in Computer-Assisted Demand-Responsive Paratransit Operation ABSTRACT, Dispatch Training #12;1 INTRODUCTION Demand-responsive paratransit service is on the rise. For example

  16. A critical review of single fuel and interfuel substitution residential energy demand models

    E-Print Network [OSTI]

    Hartman, Raymond Steve

    1978-01-01T23:59:59.000Z

    The overall purpose of this paper is to formulate a model of residential energy demand that adequately analyzes all aspects of residential consumer energy demand behavior and properly treats the penetration of new technologies, ...

  17. An Econometric Model of the Demand for Food and Nutrition

    E-Print Network [OSTI]

    LaFrance, Jeffrey T.

    1999-01-01T23:59:59.000Z

    Holland, 1978. Blundell, R. “Econometric Approaches to theDemand Behavior. ” Econometric Reviews 5(1986): 89-146. . “Harvey, A. C. The Econometric Analysis of Time Series,

  18. Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response

    E-Print Network [OSTI]

    Zhang, Wei

    Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response Wei Zhang, Jianming Lian, Chin-Yao Chang, Karanjit Kalsi and Yannan Sun Abstract-- Demand Response is playing population of appliances under demand response is especially important to evaluate the effec- tiveness

  19. Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

    E-Print Network [OSTI]

    Zhang, Wei

    1 Aggregated Modeling and Control of Air Conditioning Loads for Demand Response Wei Zhang, Member, IEEE Abstract--Demand response is playing an increasingly impor- tant role in the efficient loads is especially important to evaluate the effec- tiveness of various demand response strategies

  20. Pseudo Dynamic Transitional Modeling of Building Heating Energy Demand Using Artificial1 Neural Network2

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Transitional Modeling of Building Heating Energy Demand Using Artificial1 Neural Network2 Subodh Paudel a, it is39 essential to know energy flows and energy demand of the buildings for the control of heating and40 cooling energy production from plant systems. The energy demand of the building system, thus,41

  1. Cooling energy demand evaluation by means of regression models obtained from dynamic simulations

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Cooling energy demand evaluation by means of regression models obtained from dynamic simulations Ph, Université Lyon1, FRANCE ABSTRACT The forecast of the energy heating/cooling demand would be a good indicator between simple and complex methods of evaluating the cooling energy demand we have proposed to use energy

  2. Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

    SciTech Connect (OSTI)

    NONE

    1998-01-01T23:59:59.000Z

    This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

  3. Electrical ship demand modeling for future generation warships

    E-Print Network [OSTI]

    Sievenpiper, Bartholomew J. (Bartholomew Jay)

    2013-01-01T23:59:59.000Z

    The design of future warships will require increased reliance on accurate prediction of electrical demand as the shipboard consumption continues to rise. Current US Navy policy, codified in design standards, dictates methods ...

  4. A Single-Product Inventory Model for Multiple Demand Classes

    E-Print Network [OSTI]

    Arslan, Hasan

    2005-05-27T23:59:59.000Z

    We consider a single-product inventory system that serves multiple demand classes, which differ in their shortage costs or service level requirements. We assume a critical-level control policy, and show the equivalence ...

  5. Demand models for U.S. domestic air passenger markets

    E-Print Network [OSTI]

    Eriksen, Steven Edward

    1978-01-01T23:59:59.000Z

    The airline industry in recent years has suffered from the adverse effects of top level planning decisions based upon inaccurate demand forecasts. The air carriers have recognized the immediate need to develop their ...

  6. Market-based airport demand management : theory, model and applications

    E-Print Network [OSTI]

    Fan, Terence P

    2004-01-01T23:59:59.000Z

    The ever-increasing demand for access to the world's major commercial airports combined with capacity constraints at many of these airports have led to increasing air traffic congestion. In particular, the scarcity of ...

  7. Model documentation report: Industrial sector demand module of the National Energy Modeling System

    SciTech Connect (OSTI)

    NONE

    1997-01-01T23:59:59.000Z

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

  8. Model documentation report: Industrial sector demand module of the national energy modeling system

    SciTech Connect (OSTI)

    NONE

    1998-01-01T23:59:59.000Z

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its model. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

  9. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    E-Print Network [OSTI]

    Dudley, Junqiao Han

    2010-01-01T23:59:59.000Z

    of Automated Demand Response in a Large Office Building”, inBuilding Control Strategies and Techniques for Demand Response.Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

  10. Cogeneration System Size Optimization Constant Capacity and Constant Demand Models

    E-Print Network [OSTI]

    Wong-Kcomt, J. B.; Turner, W. C.

    known to the observer. Hence, the elements of W consists of the totality of outcomes that we associate with the states of nature Wj' Four basic outcomes are defined by the following relations: 1) Pc > Pd 2) Pc Hd 4) Hc Hd Where... and heat demand-there exist the following states of nature Wj: WI Hc > Hd and Pc > Pd w2 Hc > Hd and Pc Hd and Pc > Pd w4 Hc Hd and Pc < Pd where heat and electricity demands are expressed in power unit, i.e kWt and kWe, respectively...

  11. A Supply-Demand Model Based Scalable Energy Management System for Improved Energy

    E-Print Network [OSTI]

    Bhunia, Swarup

    the dependency of an electronic system to primary energy sources (i.e. AC power or battery). For reliable energy generation and consumption parameters. The system uses economics inspired supply-demand modelA Supply-Demand Model Based Scalable Energy Management System for Improved Energy Utilization

  12. The use of logistic regression to model the probability of oak wilt occurrence in the Texas hill country using forest stand and site characteristics

    E-Print Network [OSTI]

    Dignum, David Rory

    2012-06-07T23:59:59.000Z

    THE USE OF LOGISTIC REGRESSION TO MODEL THE PROBABILITY OF OAK MILT OCCURRENCE IN THE TEXAS HILL COUNTRY USING FOREST STAND AND SITE CHARACTERISTICS A Thesis by DAVID RORY DIGNUM Submitted to the Graduate College of Texas Afdi University... in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May 1988 Maj or Subj cot: Forestry THE USE OF LOGISTIC REGRESSION TO MODEL THE PROBABILITY OF OAK WILT OCCURRENCE IN THE TEXAS HILL COUNTRY USING FOREST STAND AND SITE...

  13. A Full Demand Response Model in Co-Optimized Energy and

    SciTech Connect (OSTI)

    Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

    2014-01-01T23:59:59.000Z

    It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

  14. A Hierarchical Bayesian Model for Improving Short-Term Forecasting of Hospital Demand by Including Meteorological

    E-Print Network [OSTI]

    Sahu, Sujit K

    A Hierarchical Bayesian Model for Improving Short-Term Forecasting of Hospital Demand by Including Sarran4 Abstract The effect of weather on health has been widely researched, and the ability to forecast, better predictions of hospital demand that are more sensitive to fluctuations in weather can allow

  15. Hydrogen Demand and Resource Analysis (HyDRA) Model

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Year in3.pdfEnergy Health and ProductivityEnergyEnergyHybridAnalysisContaminationDemand and

  16. Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles

    SciTech Connect (OSTI)

    Yamaguchi, Nobuyuki; Han, Junqiao; Ghatikar, Girish; Piette, Mary Ann; Asano, Hiroshi; Kiliccote, Sila

    2009-06-28T23:59:59.000Z

    This paper provides new regression models for demand reduction of Demand Response programs for the purpose of ex ante evaluation of the programs and screening for recruiting customer enrollment into the programs. The proposed regression models employ load sensitivity to outside air temperature and representative load pattern derived from cluster analysis of customer baseline load as explanatory variables. The proposed models examined their performances from the viewpoint of validity of explanatory variables and fitness of regressions, using actual load profile data of Pacific Gas and Electric Company's commercial and industrial customers who participated in the 2008 Critical Peak Pricing program including Manual and Automated Demand Response.

  17. Perspectives for logistics clusters development in Russia

    E-Print Network [OSTI]

    Tantsuyev, Andriy

    2012-01-01T23:59:59.000Z

    This thesis is a normative work aimed at identifying locations in Russia with high, medium and unclear potentials for logistics cluster development. As a framework this work uses four different models of logistics clusters: ...

  18. Residential energy demand modeling and the NIECS data base : an evaluation

    E-Print Network [OSTI]

    Cowing, Thomas G.

    1982-01-01T23:59:59.000Z

    The purpose of this report is to evaluate the 1978-79 National Interim Energy Consumption Survey (NIECS) data base in terms of its usefulness for estimating residential energy demand models based on household appliance ...

  19. Smart finite state devices: A modeling framework for demand response technologies

    E-Print Network [OSTI]

    Turitsyn, Konstantin

    We introduce and analyze Markov Decision Process (MDP) machines to model individual devices which are expected to participate in future demand-response markets on distribution grids. We differentiate devices into the ...

  20. A Model for a Linked System of Multi-Purpose Reservoirs with Stochastic Inflows and Demands

    E-Print Network [OSTI]

    Curry, G. L.; Helm, J. C.; Clark, R. A.

    TR-41 1972 A Model for a Linked System of Mulit-Purpose Reservoirs with Stochastic Inflows and Demands G.L. Curry J.C. Helm R.A. Clark Texas Water Resources Institute Texas A&M University ...

  1. A Dynamic household Alternative-fuel Vehicle Demand Model Using Stated and Revealed Transaction Information

    E-Print Network [OSTI]

    Sheng, Hongyan

    1999-01-01T23:59:59.000Z

    market share for alternative-fuel vehicles drop from thePreferences for Alternative-Fuel Vehicles”, Brownstone DavidA Dynamic Household Alternative-fuel Vehicle Demand Model

  2. Optimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model Predictive Control

    E-Print Network [OSTI]

    Mittelmann, Hans D.

    is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demanding nonlinear and strongly interactive process application. A Model-on-Demand Model Predictive Control (MoD-MPC

  3. Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

    SciTech Connect (OSTI)

    NONE

    1995-02-01T23:59:59.000Z

    This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

  4. Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response

    SciTech Connect (OSTI)

    Kalsi, Karanjit; Elizondo, Marcelo A.; Fuller, Jason C.; Lu, Shuai; Chassin, David P.

    2012-01-04T23:59:59.000Z

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated control models for a population of thermostatically controlled loads. The effects of demand response on the load population dynamics are investigated.

  5. Development of Short-term Demand Forecasting Model Application in Analysis of Resource Adequacy

    E-Print Network [OSTI]

    Development of Short-term Demand Forecasting Model And its Application in Analysis of Resource will present the methodology, testing and results from short-term forecasting model developed by Northwest and applied the short-term forecasting model to Resource Adequacy analysis. These steps are presented below. 1

  6. Production, Manufacturing and Logistics Managing inventories in a two-echelon dual-channel

    E-Print Network [OSTI]

    Chiang, Wei-yu Kevin

    Production, Manufacturing and Logistics Managing inventories in a two-echelon dual-channel supply We present a two-echelon dual-channel inventory model in which stocks are kept in both a manufacturer the Internet-based direct channel. The demand of retail customers is met with the on-hand inventory from

  7. Modeling of Electric Water Heaters for Demand Response: A Baseline PDE Model

    SciTech Connect (OSTI)

    Xu, Zhijie; Diao, Ruisheng; Lu, Shuai; Lian, Jianming; Zhang, Yu

    2014-09-05T23:59:59.000Z

    Demand response (DR)control can effectively relieve balancing and frequency regulation burdens on conventional generators, facilitate integrating more renewable energy, and reduce generation and transmission investments needed to meet peak demands. Electric water heaters (EWHs) have a great potential in implementing DR control strategies because: (a) the EWH power consumption has a high correlation with daily load patterns; (b) they constitute a significant percentage of domestic electrical load; (c) the heating element is a resistor, without reactive power consumption; and (d) they can be used as energy storage devices when needed. Accurately modeling the dynamic behavior of EWHs is essential for designing DR controls. Various water heater models, simplified to different extents, were published in the literature; however, few of them were validated against field measurements, which may result in inaccuracy when implementing DR controls. In this paper, a partial differential equation physics-based model, developed to capture detailed temperature profiles at different tank locations, is validated against field test data for more than 10 days. The developed model shows very good performance in capturing water thermal dynamics for benchmark testing purposes

  8. Model documentation report: Residential sector demand module of the National Energy Modeling System

    SciTech Connect (OSTI)

    NONE

    1995-03-01T23:59:59.000Z

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  9. Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit; Sun, Yannan

    2012-12-12T23:59:59.000Z

    Demand Response is playing an increasingly important role in smart grid control strategies. Modeling the behavior of populations of appliances under demand response is especially important to evaluate the effectiveness of these demand response programs. In this paper, an aggregated model is proposed for a class of Thermostatically Controlled Loads (TCLs). The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. However, an accurate characterization of the collective dynamics however requires the aggregate model to have a high state space dimension. Most of the existing model reduction techniques require the stability of the underlying system which does not hold for the proposed aggregated model. In this work, a novel model reduction approach is developed for the proposed aggregated model, which can significantly reduce its complexity with small performance loss. The original and the reducedorder aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D, which is a realistic open source distribution simulation software. Index Terms – demand response, aggregated model, ancillary

  10. Price and Non-Price Influences on Water Conservation: An Econometric Model of Aggregate Demand under Nonlinear Budget Constraint

    E-Print Network [OSTI]

    Corral, Leonardo; Fisher, Anthony C.; Hatch, Nile W.

    1999-01-01T23:59:59.000Z

    declining-block tarrifs: An econometric study using micro-ON WATER CONSERVATION: ECONOMETRIC AN MODEL OF AGGREGATEWater Conservation: An Econometric Model of Aggregate Demand

  11. A Dynamic Supply-Demand Model for Electricity Prices Manuela Buzoianu

    E-Print Network [OSTI]

    A Dynamic Supply-Demand Model for Electricity Prices Manuela Buzoianu , Anthony E. Brockwell, and Duane J. Seppi Abstract We introduce a new model for electricity prices, based on the principle in a study of Californian wholesale electricity prices over a three-year period including the crisis period

  12. The Future of Food Demand: Understanding Differences in Global Economic Models

    SciTech Connect (OSTI)

    Valin, Hugo; Sands, Ronald; van der Mensbrugghe, Dominique; Nelson, Gerald; Ahammad, Helal; Blanc, Elodie; Bodirsky, Benjamin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Heyhoe, Edwina; Kyle, G. Page; Mason d'Croz, Daniel; Paltsev, S.; Rolinski, Susanne; Tabeau, Andrzej; van Meijl, Hans; von Lampe, Martin; Willenbockel, Dirk

    2014-01-01T23:59:59.000Z

    Understanding the capacity of agricultural systems to feed the world population under climate change requires a good prospective vision on the future development of food demand. This paper reviews modeling approaches from ten global economic models participating to the AgMIP project, in particular the demand function chosen and the set of parameters used. We compare food demand projections at the horizon 2050 for various regions and agricultural products under harmonized scenarios. Depending on models, we find for a business as usual scenario (SSP2) an increase in food demand of 59-98% by 2050, slightly higher than FAO projection (54%). The prospective for animal calories is particularly uncertain with a range of 61-144%, whereas FAO anticipates an increase by 76%. The projections reveal more sensitive to socio-economic assumptions than to climate change conditions or bioenergy development. When considering a higher population lower economic growth world (SSP3), consumption per capita drops by 9% for crops and 18% for livestock. Various assumptions on climate change in this exercise do not lead to world calorie losses greater than 6%. Divergences across models are however notable, due to differences in demand system, income elasticities specification, and response to price change in the baseline.

  13. CONSULTANT REPORT DEMAND FORECAST EXPERT

    E-Print Network [OSTI]

    CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

  14. AMPS, a real-time mesoscale modeling system, has provided a decade of service for scientific and logistical needs and has helped advance polar numerical weather prediction

    E-Print Network [OSTI]

    Howat, Ian M.

    and logistical needs and has helped advance polar numerical weather prediction as well as understanding support for the USAP. The concern at the time was the numerical weather prediction (NWP) guidance-time implementation of the Weather Research and Forecasting model (WRF; Skamarock et al. 2008) to support the U

  15. Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

    SciTech Connect (OSTI)

    Kalsi, Karanjit; Chassin, Forrest S.; Chassin, David P.

    2011-12-12T23:59:59.000Z

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

  16. Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

    SciTech Connect (OSTI)

    Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.; Chassin, David P.; Djilali, Ned

    2014-01-31T23:59:59.000Z

    Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

  17. Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network

    E-Print Network [OSTI]

    Paudel, Subodh; Elmtiri, Mohamed; Kling, Wil L; Corre, Olivier Le; Lacarriere, Bruno

    2014-01-01T23:59:59.000Z

    R. Satake, Prediction of energy demands using neural networkof Building Heating Energy Demand Using Artificial Neuralknow energy flows and energy demand of the buildings for the

  18. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    demand response and energy ef?ciency in commercial buildings,”building control strategies and techniques for demand response,”building electricity use with application to demand response,”

  19. Estimation of a supply and demand model for the hired farm labor market in Texas

    E-Print Network [OSTI]

    Turley, Keith Pool

    1977-01-01T23:59:59.000Z

    ESTIMATION OF A SUPPLY AND DEMAND MODEL FOR THE HIRED FARM LABOR MARKET IN TEXAS A Thesis by KEITH POOL TURLEY Submitted to the Craduate College of Texas ARM University in partial fulfillment of the requirement for the degree of MASTER... Or SCIENCI. December 1977 Major Subject: Agricultural Economics ESTIMATION OF A SUPPLY AND DEMAND NODEL FOR THE HIRED FARM LABOR MARKET IN TEXAS A Thesis by KEITH POOL TURLEY Approved as to style and content by: Ch rman of Comm' tee) Member Mem r...

  20. Smart grid-demand side response model to mitigate prices and peak impact on the electrical system.

    E-Print Network [OSTI]

    Marwan, Marwan

    2013-01-01T23:59:59.000Z

    ??The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator… (more)

  1. Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction

    SciTech Connect (OSTI)

    Fuller, Jason C.; Vyakaranam, Bharat GNVSR; Prakash Kumar, Nirupama; Leistritz, Sean M.; Parker, Graham B.

    2012-04-29T23:59:59.000Z

    The widespread adoption of demand response enabled appliances and thermostats can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. GE has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information from the utility grid, often in the form of price. However due to a number of factors, including the number of demand response enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors can be modeled and simulated in open-source software, GridLAB-D, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. This report is the first in a series of three reports describing the potential of GE's demand response enabled appliances to provide benefits to the utility grid. The first report will describe the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The second and third reports will explore the potential of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation and the effects on volt-var control schemes.

  2. Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit

    2013-06-21T23:59:59.000Z

    Demand response is playing an increasingly important role in the efficient and reliable operation of the electric grid. Modeling the dynamic behavior of a large population of responsive loads is especially important to evaluate the effectiveness of various demand response strategies. In this paper, a highly-accurate aggregated model is developed for a population of air conditioning loads. The model effectively includes statistical information of the population, systematically deals with load heterogeneity, and accounts for second-order dynamics necessary to accurately capture the transient dynamics in the collective response. Based on the model, a novel aggregated control strategy is designed for the load population under realistic conditions. The proposed controller is fully responsive and achieves the control objective without sacrificing end-use performance. The proposed aggregated modeling and control strategies are validated through realistic simulations using GridLAB-D. Extensive simulation results indicate that the proposed approach can effectively manage a large number of air conditioning systems to provide various demand response services, such as frequency regulation and peak load reduction.

  3. 16th Annual Freight and Logistics Symposium

    E-Print Network [OSTI]

    Minnesota, University of

    performance and results, prices and demand for oil, our ability to make acquisitions on economically/7/2012 2 #12;Shale Development ­ "Boom" Shale Development Wind Energy Ethanol 2003 · Logistics and related infrastructure of greater importance in shale development, and therefore a major

  4. New modeling and control solutions for integrated microgrid system with respect to thermodynamics properties of generation and demand

    E-Print Network [OSTI]

    Liu, Fang-Yu, S.M. Massachusetts Institute of Technology

    2014-01-01T23:59:59.000Z

    This thesis investigates microgrid control stability with respect to thermodynamics behaviors of generation and demand. First, a new integrated microgrid model is introduced. This model consists of a combined cycle power ...

  5. Outsourcing Logistics in the Oil and Gas Industry

    E-Print Network [OSTI]

    Herrera, Cristina 1988-

    2012-04-30T23:59:59.000Z

    The supply chain challenges that the Oil and Gas industry faces in material logistics have enlarged in the last few decades owing to an increased hydro-carbon demand. Many reasons justify the challenges, such as exploration activities which have...

  6. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    SciTech Connect (OSTI)

    Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

    2011-08-15T23:59:59.000Z

    Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

  7. FUTURE LOGISTICS LIVING LABORATORY

    E-Print Network [OSTI]

    Heiser, Gernot

    FUTURE LOGISTICS LIVING LABORATORY Delivering Innovation The Future Logistics Living Lab is a collaboration between NICTA, SAP and Fraunhofer. Australia's first Living Lab provides a platform for industry and research to work together, to investigate real-world problems and to demonstrate innovative technology

  8. A double exponential model for biochemical oxygen demand Ian G. Mason a,*, Robert I. McLachlan b

    E-Print Network [OSTI]

    McLachlan, Robert

    A double exponential model for biochemical oxygen demand Ian G. Mason a,*, Robert I. McLachlan b , Daniel T. Ge´rard a a Institute of Technology and Engineering, Massey University, Palmerston North, New 2005 Abstract Biochemical oxygen demand (BOD) exertion patterns in anaerobically treated farm dairy

  9. Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison

    SciTech Connect (OSTI)

    Lotze-Campen, Hermann; von Lampe, Martin; Kyle, G. Page; Fujimori, Shinichiro; Havlik, Petr; van Meijl, Hans; Hasegawa, Tomoko; Popp, Alexander; Schmitz, Christoph; Tabeau, Andrzej; Valin, Hugo; Willenbockel, Dirk; Wise, Marshall A.

    2014-01-01T23:59:59.000Z

    Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Comparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, e.g. from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an RCP2.6-type scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in an RCP8.5-type scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.

  10. Calibration of an EnergyPlus Building Energy Model to Assess the Impact of Demand Response Measures

    E-Print Network [OSTI]

    Lavigne, K.; Sansregret, S.; Daoud, A.; Leclair, L. A.

    2013-01-01T23:59:59.000Z

    1 Karine Lavigne Simon Sansregret Ahmed DaoudLouis-Alexandre Leclaire CALIBRATION OF AN ENERGYPLUS BUILDING ENERGY MODEL TO ASSESS THE IMPACT OF DEMAND RESPONSE MEASURES ICEBO 2013, Montr?al Groupe ? Technologie2 ICEBO-2013 Contextualization... ICEBO-2013 Groupe ? Technologie Calibrated Results 22 ICEBO-2013 12 Groupe ? Technologie Conclusion 23 ICEBO-2013 > Calibrating model for a demand response objective : Challenging and High Effort > Capturing building and human erratic behaviour...

  11. A hybrid inventory management system respondingto regular demand and surge demand

    SciTech Connect (OSTI)

    Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

    2014-06-01T23:59:59.000Z

    This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a given policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.

  12. Smart Finite State Devices: A Modeling Framework for Demand Response Technologies

    E-Print Network [OSTI]

    Turitsyn, Konstantin; Ananyev, Maxim; Chertkov, Michael

    2011-01-01T23:59:59.000Z

    We introduce and analyze Markov Decision Process (MDP) machines to model individual devices which are expected to participate in future demand-response markets on distribution grids. We differentiate devices into the following four types: (a) optional loads that can be shed, e.g. light dimming; (b) deferrable loads that can be delayed, e.g. dishwashers; (c) controllable loads with inertia, e.g. thermostatically-controlled loads, whose task is to maintain an auxiliary characteristic (temperature) within pre-defined margins; and (d) storage devices that can alternate between charging and generating. Our analysis of the devices seeks to find their optimal price-taking control strategy under a given stochastic model of the distribution market.

  13. Demand Reduction

    Broader source: Energy.gov [DOE]

    Grantees may use funds to coordinate with electricity supply companies and utilities to reduce energy demands on their power systems. These demand reduction programs are usually coordinated through...

  14. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01T23:59:59.000Z

    analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

  15. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01T23:59:59.000Z

    analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

  16. Side-payment profitability and interacting eyeball ISPs under convex demand-response modeling congestion-sensitive applications

    E-Print Network [OSTI]

    Kesidis, George

    2011-01-01T23:59:59.000Z

    This paper is concerned with the issue of side payments between content providers (CPs) and Internet service (access bandwidth) providers (ISPs) in an Internet that is potentially not neutral. We herein generalize past results modeling the ISP and CP interaction as a noncooperative game in two directions. We consider different demand response models (price sensitivities) for different provider types in order to explore when side payments are profitable to the ISP. Also, we consider convex (non-linear) demand response to model demand triggered by traffic which is sensitive to access bandwidth congestion, particularly delay-sensitive interactive real-time applications. Finally, we consider a model with two competing "eyeball" ISPs with transit pricing of net traffic at their peering point to study the effects of caching remote content.

  17. The addition of a US Rare Earth Element (REE) supply-demand model improves the characterization and scope of the United States Department of Energy's effort to forecast US REE Supply and Demand

    E-Print Network [OSTI]

    Mancco, Richard

    2012-01-01T23:59:59.000Z

    This paper presents the development of a new US Rare Earth Element (REE) Supply-Demand Model for the explicit forecast of US REE supply and demand in the 2010 to 2025 time period. In the 2010 Department of Energy (DOE) ...

  18. Project Proposal Project Logistics

    E-Print Network [OSTI]

    Hall, Mary W.

    Project Proposal · Project Logistics: ­ 2-3 person teams ­ Significant implementation, worth 55 and anticipated cost of copying to/from host memory. IV. Intellectual Challenges - Generally, what makes this computation worthy of a project? - Point to any difficulties you anticipate at present in achieving high

  19. Residential-energy-demand modeling and the NIECS data base: an evaluation

    SciTech Connect (OSTI)

    Cowing, T.G.; Dubin, J.A.; McFadden, D.

    1982-01-01T23:59:59.000Z

    The purpose of this report is to evaluate the 1978-1979 National Interim Energy Consumption Survey (NIECS) data base in terms of its usefulness for estimating residential energy demand models based on household appliance choice and utilization decisions. The NIECS contains detailed energy usage information at the household level for 4081 households during the April 1978 to March 1979 period. Among the data included are information on the structural and thermal characteristics of the housing unit, demographic characteristics of the household, fuel usage, appliance characteristics, and actual energy consumption. The survey covers the four primary residential fuels-electricity, natural gas, fuel oil, and liquefied petroleum gas - and includes detailed information on recent household conservation and retrofit activities. Section II contains brief descriptions of the major components of the NIECS data set. Discussions are included on the sample frame and the imputation procedures used in NIECS. There are also two extensive tables, giving detailed statistical and other information on most of the non-vehicle NIECS variables. Section III contains an assessment of the NIECS data, focusing on four areas: measurement error, sample design, imputation problems, and additional data needed to estimate appliance choice/use models. Section IV summarizes and concludes the report.

  20. A Unit Commitment Model with Demand Response for the Integration of Renewable Energies

    E-Print Network [OSTI]

    Ikeda, Yuichi; Kataoka, Kazuto; Ogimoto, Kazuhiko

    2011-01-01T23:59:59.000Z

    The output of renewable energy fluctuates significantly depending on weather conditions. We develop a unit commitment model to analyze requirements of the forecast output and its error for renewable energies. Our model obtains the time series for the operational state of thermal power plants that would maximize the profits of an electric power utility by taking into account both the forecast of output its error for renewable energies and the demand response of consumers. We consider a power system consisting of thermal power plants, photovoltaic systems (PV), and wind farms and analyze the effect of the forecast error on the operation cost and reserves. We confirm that the operation cost was increases with the forecast error. The effect of a sudden decrease in wind power is also analyzed. More thermal power plants need to be operated to generate power to absorb this sudden decrease in wind power. The increase in the number of operating thermal power plants within a short period does not affect the total opera...

  1. A cooperation model and demand-oriented ICT Infrastructure for SME Development and Production Networks in the field of Microsystem

    E-Print Network [OSTI]

    Boyer, Edmond

    A cooperation model and demand-oriented ICT Infrastructure for SME Development and Production of Small Medium Enterprises (SME) in this branch refers to organizational issues, arising from the specific SME´s lack of sufficient human resources and an effective management of cross company knowledge about

  2. Estimating Demand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Buildings in California

    E-Print Network [OSTI]

    Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote, Sila

    2008-01-01T23:59:59.000Z

    commercial buildings participating in a demand?response (buildings participating in an Automated Demand Response buildings  participating  in  an  event?driven  demand?response  (

  3. A Transaction Choice Model for Forecasting Demand for Alternative-Fuel Vehicles

    E-Print Network [OSTI]

    Brownstone, David; Bunch, David S.; Golob, Thomas F.; Ren, Weiping

    1996-01-01T23:59:59.000Z

    Forecasting Demand Alternative-Fuel Vehicles for DavldNG DEMANDFOR ALTERNATIVE-FUEL VEHICLES DavidBrownstone,interested in promoting alternative-fuel vehicles. Tl’us is

  4. A Transactions Choice Model for Forecasting Demand for Alternative-Fuel Vehicles

    E-Print Network [OSTI]

    Brownstone, David; Bunch, David S; Golob, Thomas F; Ren, Weiping

    1996-01-01T23:59:59.000Z

    Forecasting Demand Alternative-Fuel Vehicles for DavldNG DEMANDFOR ALTERNATIVE-FUEL VEHICLES DavidBrownstone,interested in promoting alternative-fuel vehicles. Tl’us is

  5. Cooling Energy Demand Evaluation by Meansof Regression Models Obtained From Dynamic Simulations

    E-Print Network [OSTI]

    Catalina, T.; Virgone, J.

    2011-01-01T23:59:59.000Z

    The forecast of the energy heating/cooling demand would be a good indicator for the choice between different conception solutions according to the building characteristics and the local climate. A previous study (Catalina T. et al 2008...

  6. Incorporating endogenous demand dynamics into long-term capacity expansion power system models for Developing countries

    E-Print Network [OSTI]

    Jordan, Rhonda LeNai

    2013-01-01T23:59:59.000Z

    This research develops a novel approach to long-term power system capacity expansion planning for developing countries by incorporating endogenous demand dynamics resulting from social processes of technology adoption. ...

  7. Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)

    Reports and Publications (EIA)

    1998-01-01T23:59:59.000Z

    The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

  8. Costs and benefits of logistics pooling for urban freight distribution: scenario

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    logistics; resource sharing; freight transport pooling; policy-oriented modelling; simulation is that of logistics pooling, that can be defined analogously to car-pooling as the common usage of logistics resources). We observe several projects dealing with urban logistics resource sharing in the last years, most

  9. Ownership transfer for non-federate object and time management in developing an hla compliant logistics model.

    SciTech Connect (OSTI)

    Li, Z.

    1998-01-12T23:59:59.000Z

    A seaport simulation model, PORTSIM, has been developed for the Department of Defense (DOD) at Argonne National Laboratory. PORTSIM simulates the detailed processes of cargo loading and unloading in a seaport and provides throughput capability, resource utilization, and other important information on the bottlenecks in a seaport operation, which are crucial data in determining troop and equipment deployment capability. There are two key problems to solve in developing the HLA-compliant PORTSIM model. The first is the cargo object ownership transfer problem. In PORTSIM, cargo items, e.g. vehicles, containers, and pallets, are objects having asset attributes. Cargo comes to a seaport for loading or unloading. The ownership of a cargo object transfers from its carrier to the port and then from the port to a new carrier. Each owner of the cargo object is responsible for publishing and updating the attributes of the cargo object when it has the ownership. This creates a unique situation in developing the PORTSIM federate object model, that is, the ownership of the object instead of the attributes needs to be changed in handling the cargo object in the PORTSIM federate. The ownership management service provided by the current RTI does not directly address this issue. The second is the time management issue. PORTSIM is an event-driven simulation that models seaport operations over time. To make PORTSIM HLA compliant, time management must be addressed to allow for synchronization with other simulation models. This paper attempts to address these two issues and methodologies developed for solving these two problems.

  10. Measuring Coordination Demand in Multirobot Teams Conventional models of multirobot control assume independent robots and tasks. This allows an additive model in which the

    E-Print Network [OSTI]

    Lewis, Michael

    independent robots and tasks. This allows an additive model in which the operator controls robots sequentially model to situations in which robots must cooperate to perform dependent tasks. In the first experiment operators controlled 2 robot teams to perform a box pushing task under high coordination demand

  11. Logistic Regression Applied to Seismic Discrimination

    SciTech Connect (OSTI)

    BG Amindan; DN Hagedorn

    1998-10-08T23:59:59.000Z

    The usefulness of logistic discrimination was examined in an effort to learn how it performs in a regional seismic setting. Logistic discrimination provides an easily understood method, works with user-defined models and few assumptions about the population distributions, and handles both continuous and discrete data. Seismic event measurements from a data set compiled by Los Alamos National Laboratory (LANL) of Chinese events recorded at station WMQ were used in this demonstration study. PNNL applied logistic regression techniques to the data. All possible combinations of the Lg and Pg measurements were tried, and a best-fit logistic model was created. The best combination of Lg and Pg frequencies for predicting the source of a seismic event (earthquake or explosion) used Lg{sub 3.0-6.0} and Pg{sub 3.0-6.0} as the predictor variables. A cross-validation test was run, which showed that this model was able to correctly predict 99.7% earthquakes and 98.0% explosions for this given data set. Two other models were identified that used Pg and Lg measurements from the 1.5 to 3.0 Hz frequency range. Although these other models did a good job of correctly predicting the earthquakes, they were not as effective at predicting the explosions. Two possible biases were discovered which affect the predicted probabilities for each outcome. The first bias was due to this being a case-controlled study. The sampling fractions caused a bias in the probabilities that were calculated using the models. The second bias is caused by a change in the proportions for each event. If at a later date the proportions (a priori probabilities) of explosions versus earthquakes change, this would cause a bias in the predicted probability for an event. When using logistic regression, the user needs to be aware of the possible biases and what affect they will have on the predicted probabilities.

  12. Model for Analysis of Energy Demand (MAED-2) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy Resources Jump to:46 -Energieprojekte GmbHMilo, Maine:Energy Information23.Energy Demand (MAED-2)

  13. Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future

    SciTech Connect (OSTI)

    Grenzeback, L. R.; Brown, A.; Fischer, M. J.; Hutson, N.; Lamm, C. R.; Pei, Y. L.; Vimmerstedt, L.; Vyas, A. D.; Winebrake, J. J.

    2013-03-01T23:59:59.000Z

    Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and to nearly 30.2 billion tons in 2050. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand, the trends and 2050 outlook for these factors, and their anticipated effect on freight demand. After describing federal policy actions that could influence future freight demand, the report then summarizes the capabilities of available analytical models for forecasting freight demand. This is one in a series of reports produced as a result of the Transportation Energy Futures project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for reducing GHGs and petroleum dependence related to transportation.

  14. TRAVEL DEMAND AND RELIABLE FORECASTS

    E-Print Network [OSTI]

    Minnesota, University of

    TRAVEL DEMAND AND RELIABLE FORECASTS FOR TRANSIT MARK FILIPI, AICP PTP 23rd Annual Transportation transportation projects § Develop and maintain Regional Travel Demand Model § Develop forecast socio in cooperative review during all phases of travel demand forecasting 4 #12;Cooperative Review Should Include

  15. Analysis of Transportation and Logistics Challenges Affecting...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of Transportation and Logistics Challenges Affecting the Deployment of Larger Wind Turbines: Summary of Results Analysis of Transportation and Logistics Challenges Affecting...

  16. Application of real options to reverse logistics process

    E-Print Network [OSTI]

    Kaga, Akihiro, 1975-

    2004-01-01T23:59:59.000Z

    In this thesis, real options are used to identify the optimal model for the reverse logistics process of a technology company in the circuit board business. Currently, customers return defective boards and the company ...

  17. Modeling the Capacity and Emissions Impacts of Reduced Electricity Demand. Part 1. Methodology and Preliminary Results.

    E-Print Network [OSTI]

    Coughlin, Katie

    2013-01-01T23:59:59.000Z

    2011).pdf. ———. 2012a. “Annual Energy Outlook (AEO) 2012. ”2013. “Annual Energy Outlook - Model Documentation. ”forecast, the Annual Energy Outlook (AEO) (DOE EIA 2012a).

  18. Probabilistic Seismic Demand Model and Fragility Estimates for Symmetric Rigid Blocks Subject to Rocking Motions

    E-Print Network [OSTI]

    Bakhtiary, Esmaeel

    2013-01-15T23:59:59.000Z

    This thesis presents a probability model to predict the maximum rotation of rocking bodies exposed to seismic excitations given specific earthquake intensity measures. After obtaining the nonlinear equations of motion and clarification...

  19. Model of medical supply demand and astronaut health for long-duration human space flight

    E-Print Network [OSTI]

    Assad, Albert

    2009-01-01T23:59:59.000Z

    The medical care of space crews is the primary limiting factor in the achievement of long-duration space missions. (Nicogossian 2003) The goal of this thesis was to develop a model of long-duration human space flight ...

  20. Stochastic Dynamic Demand Inventory Models with Explicit Transportation Costs and Decisions

    E-Print Network [OSTI]

    Zhang, Liqing

    2011-07-01T23:59:59.000Z

    is the policy where several small loads will be dispatched as a single, combined load. From an inventory-modeling perspec- tive, the integrated inventory-transportation problems add dispatch quantities as decision variables to the stochastic dynamic inventory...): The vendor makes the inventory replen- ishment decisions on how much to order from the outside supplier. 2. Pure Outbound Transportation Models (PO): The collection depot makes the delivery schedules of order dispatches to the buyer(s). 3. Integrated...

  1. Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand................................................................................................................................. 1 Demand Forecast Methodology.................................................................................................. 3 New Demand Forecasting Model for the Sixth Plan

  2. A finite difference model for predicting sediment oxygen demand in streams

    E-Print Network [OSTI]

    Charbonnet, Danielle Andrea

    2003-01-01T23:59:59.000Z

    in the representative river system using benthic chambers. A finite difference model was developed based on Fick's Law of Diffusion. Mass transfer principles are used to perform a mass balance on the oxygen concentrations in the sediment in order to determine SOD...

  3. Demand Response and Open Automated Demand Response

    E-Print Network [OSTI]

    LBNL-3047E Demand Response and Open Automated Demand Response Opportunities for Data Centers G described in this report was coordinated by the Demand Response Research Center and funded by the California. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy

  4. Logistical and transportation infrastructure in Asia : potential for growth and development to support increasing trade with Europe

    E-Print Network [OSTI]

    Deonás, Nikolaos, 1978-

    2004-01-01T23:59:59.000Z

    This thesis examines the implications of the rapid growth in demand for trade between Europe and Asia for the existing transportation network and logistical infrastructure. In general terms, technologies need to improve ...

  5. High Temperatures & Electricity Demand

    E-Print Network [OSTI]

    High Temperatures & Electricity Demand An Assessment of Supply Adequacy in California Trends.......................................................................................................1 HIGH TEMPERATURES AND ELECTRICITY DEMAND.....................................................................................................................7 SECTION I: HIGH TEMPERATURES AND ELECTRICITY DEMAND ..........................9 BACKGROUND

  6. CliCrop: a Crop Water-Stress and Irrigation Demand Model for an Integrated Global Assessment Model Approach

    E-Print Network [OSTI]

    Fant, C.A.

    This paper describes the use of the CliCrop model in the context of climate change general assessment

  7. Estimating Demand Response Load Impacts: Evaluation of BaselineLoad Models for Non-Residential Buildings in California

    SciTech Connect (OSTI)

    Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote,Sila

    2008-01-01T23:59:59.000Z

    Both Federal and California state policymakers areincreasingly interested in developing more standardized and consistentapproaches to estimate and verify the load impacts of demand responseprograms and dynamic pricing tariffs. This study describes a statisticalanalysis of the performance of different models used to calculate thebaseline electric load for commercial buildings participating in ademand-response (DR) program, with emphasis onthe importance of weathereffects. During a DR event, a variety of adjustments may be made tobuilding operation, with the goal of reducing the building peak electricload. In order to determine the actual peak load reduction, an estimateof what the load would have been on the day of the event without any DRactions is needed. This baseline load profile (BLP) is key to accuratelyassessing the load impacts from event-based DR programs and may alsoimpact payment settlements for certain types of DR programs. We testedseven baseline models on a sample of 33 buildings located in California.These models can be loosely categorized into two groups: (1) averagingmethods, which use some linear combination of hourly load values fromprevious days to predict the load on the event, and (2) explicit weathermodels, which use a formula based on local hourly temperature to predictthe load. The models were tested both with and without morningadjustments, which use data from the day of the event to adjust theestimated BLP up or down.Key findings from this study are: - The accuracyof the BLP model currently used by California utilities to estimate loadreductions in several DR programs (i.e., hourly usage in highest 3 out of10 previous days) could be improved substantially if a morning adjustmentfactor were applied for weather-sensitive commercial and institutionalbuildings. - Applying a morning adjustment factor significantly reducesthe bias and improves the accuracy of all BLP models examined in oursample of buildings. - For buildings with low load variability, all BLPmodels perform reasonably well in accuracy. - For customer accounts withhighly variable loads, we found that no BLP model produced satisfactoryresults, although averaging methods perform best in accuracy (but notbias). These types of customers are difficult to characterize withstandard BLP models that rely on historic loads and weather data.Implications of these results for DR program administrators andpolicymakersare: - Most DR programs apply similar DR BLP methods tocommercial and industrial sector customers. The results of our study whencombined with other recent studies (Quantum 2004 and 2006, Buege et al.,2006) suggests that DR program administrators should have flexibility andmultiple options for suggesting the most appropriate BLP method forspecific types of customers.

  8. Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Room 253. There is no official hotel or room block. There is no registration fee. LBNL Visitor Info LBNL Map with Building 15 identified PDF Berkeley Lab Guest House Nearby...

  9. Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickrinformationPostdocsCenterCentera A B C D E FLogging in

  10. Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickrinformationPostdocsCenterCentera A B C D E FLogging

  11. Feedstock Logistics | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataCombined Heat & PowerEnergy BlogExchangeSummaryFederalLogistics

  12. Reducing the demand forecast error due to the bullwhip effect in the computer processor industry

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01T23:59:59.000Z

    Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

  13. Demand Response for Ancillary Services

    SciTech Connect (OSTI)

    Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL

    2013-01-01T23:59:59.000Z

    Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

  14. Dr. Dale S. Rogers Professor, Logistics & Supply Chain Management

    E-Print Network [OSTI]

    Lin, Xiaodong

    The Future of Global Logistics #12;The Future of Global Logistics Future of Global Logistics · Introduction Chain #12;The Future of Global Logistics Introduction #12;The Future of Global Logistics Historical Milestones In Conceptualization Shifts in Logistical Thinking · Transportation Efficiency 3000BC · Total Cost

  15. air cargo demand: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Websites Summary: 1 Aggregated Modeling and Control of Air Conditioning Loads for Demand Response Wei Zhang, Member, IEEE Abstract--Demand response is playing an...

  16. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    of integrating demand response and energy efficiencyand D. Kathan (2009), Demand Response in U.S. ElectricityFRAMEWORKS THAT PROMOTE DEMAND RESPONSE 3.1. Demand Response

  17. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    Addressing Energy Demand through Demand Response:both the avoided energy costs (and demand charges) as wellCoordination of Energy Efficiency and Demand Response,

  18. Advanced Demand Responsive Lighting

    E-Print Network [OSTI]

    Advanced Demand Responsive Lighting Host: Francis Rubinstein Demand Response Research Center demand responsive lighting systems ­ Importance of dimming ­ New wireless controls technologies · Advanced Demand Responsive Lighting (commenced March 2007) #12;Objectives · Provide up-to-date information

  19. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

    benefits of Demand Side Management (DSM) are insufficient toefficiency, demand side management (DSM) cost effectivenessResearch Center Demand Side Management Demand Side Resources

  20. New Advances in Logistic Regression for Handling Missing and Mismeasured Data with Applications in Biostatistics

    E-Print Network [OSTI]

    Miao, Jingang

    2014-05-30T23:59:59.000Z

    As a probabilistic statistical classification model, logistic regression (or logit regression) is widely used to model the outcome of a categorical dependent variable based on one or more predictor variables/features. We study two problems related...

  1. Woody Biomass Logistics Robert Keefe1

    E-Print Network [OSTI]

    14 Woody Biomass Logistics Robert Keefe1 , Nathaniel Anderson2 , John Hogland2 , and Ken Muhlenfeld The economics of using woody biomass as a fuel or feedstock for bioenergy applications is often driven by logistical considerations. Depending on the source of the woody biomass, the acquisition cost of the material

  2. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1991-09-01T23:59:59.000Z

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  3. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1992-04-01T23:59:59.000Z

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  4. Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

    SciTech Connect (OSTI)

    Zhou, Yuyu; Clarke, Leon E.; Eom, Jiyong; Kyle, G. Page; Patel, Pralit L.; Kim, Son H.; Dirks, James A.; Jensen, Erik A.; Liu, Ying; Rice, Jennie S.; Schmidt, Laurel C.; Seiple, Timothy E.

    2014-01-01T23:59:59.000Z

    As long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate impact on building energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning. In this study, we presented a detailed building energy model with a U.S. state-level representation, nested in the GCAM integrated assessment framework. We projected state-level building energy demand and its spatial pattern over the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data. The result indicates that climate change has a large impact on heating and cooling building energy and fuel use at the state level, exhibiting large spatial heterogeneity across states (ranges from -10% to +10%). The sensitivity analysis reveals that the building energy demand is subject to multiple key factors, such as the magnitude of climate change, the choice of climate models, and the growth of population and GDP, and that their relative contributions vary greatly across the space. The scale impact in building energy use modeling highlights the importance of constructing a building energy model with the spatially-explicit representation of socioeconomics, energy system development, and climate change. These findings will help the climate-based policy decision and energy system, especially utility planning related to building sector at the U.S. state and regional level facing the potential climate change.

  5. Visualizing the logistic map with a microcontroller

    E-Print Network [OSTI]

    Juan D. Serna; Amitabh Joshi

    2011-12-25T23:59:59.000Z

    The logistic map is one of the simplest nonlinear dynamical systems that clearly exhibit the route to chaos. In this paper, we explored the evolution of the logistic map using an open-source microcontroller connected to an array of light emitting diodes (LEDs). We divided the one-dimensional interval $[0,1]$ into ten equal parts, and associated and LED to each segment. Every time an iteration took place a corresponding LED turned on indicating the value returned by the logistic map. By changing some initial conditions of the system, we observed the transition from order to chaos exhibited by the map.

  6. Visualizing the logistic map with a microcontroller

    E-Print Network [OSTI]

    Serna, Juan D

    2011-01-01T23:59:59.000Z

    The logistic map is one of the simplest nonlinear dynamical systems that clearly exhibit the route to chaos. In this paper, we explored the evolution of the logistic map using an open-source microcontroller connected to an array of light emitting diodes (LEDs). We divided the one-dimensional interval $[0,1]$ into ten equal parts, and associated and LED to each segment. Every time an iteration took place a corresponding LED turned on indicating the value returned by the logistic map. By changing some initial conditions of the system, we observed the transition from order to chaos exhibited by the map.

  7. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    E-Print Network [OSTI]

    Dudley, Junqiao Han

    2010-01-01T23:59:59.000Z

    We have studied a low energy building on a campus of theEnergyPlus Model in a Low Energy Campus Building Junqiao HanEnergyPlus Model in a Low Energy Campus Building Junqiao Han

  8. Cargo revenue management for space logistics

    E-Print Network [OSTI]

    Armar, Nii A

    2009-01-01T23:59:59.000Z

    This thesis covers the development of a framework for the application of revenue management, specifically capacity control, to space logistics for use in the optimization of mission cargo allocations, which in turn affect ...

  9. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    Data for Automated Demand Response in Commercial Buildings,Demand Response Infrastructure for Commercial Buildings",demand response and energy efficiency functions into the design of buildings,

  10. Implementation of Benchmarking Transportation Logistics Practices and Future Benchmarking Organizations

    SciTech Connect (OSTI)

    Thrower, A.W. [U.S. Department of Energy, Office of Civilian Radioactive Waste Management, Washington, DC (United States); Patric, J. [Booz Allen Hamilton, Washington, DC (United States); Keister, M. [Idaho National Laboratory, Idaho Falls, ID (United States)

    2008-07-01T23:59:59.000Z

    The purpose of the Office of Civilian Radioactive Waste Management's (OCRWM) Logistics Benchmarking Project is to identify established government and industry practices for the safe transportation of hazardous materials which can serve as a yardstick for design and operation of OCRWM's national transportation system for shipping spent nuclear fuel and high-level radioactive waste to the proposed repository at Yucca Mountain, Nevada. The project will present logistics and transportation practices and develop implementation recommendations for adaptation by the national transportation system. This paper will describe the process used to perform the initial benchmarking study, highlight interim findings, and explain how these findings are being implemented. It will also provide an overview of the next phase of benchmarking studies. The benchmarking effort will remain a high-priority activity throughout the planning and operational phases of the transportation system. The initial phase of the project focused on government transportation programs to identify those practices which are most clearly applicable to OCRWM. These Federal programs have decades of safe transportation experience, strive for excellence in operations, and implement effective stakeholder involvement, all of which parallel OCRWM's transportation mission and vision. The initial benchmarking project focused on four business processes that are critical to OCRWM's mission success, and can be incorporated into OCRWM planning and preparation in the near term. The processes examined were: transportation business model, contract management/out-sourcing, stakeholder relations, and contingency planning. More recently, OCRWM examined logistics operations of AREVA NC's Business Unit Logistics in France. The next phase of benchmarking will focus on integrated domestic and international commercial radioactive logistic operations. The prospective companies represent large scale shippers and have vast experience in safely and efficiently shipping spent nuclear fuel and other radioactive materials. Additional business processes may be examined in this phase. The findings of these benchmarking efforts will help determine the organizational structure and requirements of the national transportation system. (authors)

  11. Challenge # 2 Logistics and Compatibility with Existing Infrastructure...

    Office of Environmental Management (EM)

    2 Logistics and Compatibility with Existing Infrastructure Throughout Supply Chain Challenge 2 Logistics and Compatibility with Existing Infrastructure Throughout Supply Chain...

  12. Initial Comments of Honeywell, Inc. on Policy and Logistical...

    Office of Environmental Management (EM)

    Initial Comments of Honeywell, Inc. on Policy and Logistical Challenges in Implementing Smart Grid Solutions Initial Comments of Honeywell, Inc. on Policy and Logistical Challenges...

  13. Southern Company: DOE Smart Grid RFI Addressing Policy and Logistical...

    Broader source: Energy.gov (indexed) [DOE]

    Southern Company: DOE Smart Grid RFI Addressing Policy and Logistical Challenges Southern Company: DOE Smart Grid RFI Addressing Policy and Logistical Challenges Southern Company:...

  14. Steffes Corporation Smart Grid RFI: Addressing Policy and Logistical...

    Broader source: Energy.gov (indexed) [DOE]

    Steffes Corporation Smart Grid RFI: Addressing Policy and Logistical Challenges Steffes Corporation Smart Grid RFI: Addressing Policy and Logistical Challenges Steffes Corporation...

  15. Pepco Holdings, Inc. Smart Grid RFI: Addressing Policy and Logistical...

    Broader source: Energy.gov (indexed) [DOE]

    Holdings, Inc. Smart Grid RFI: Addressing Policy and Logistical Challenges Pepco Holdings, Inc. Smart Grid RFI: Addressing Policy and Logistical Challenges Pepco Holdings, Inc....

  16. Real lessons for venture capitalists in multimodal logistics systems : where does profitability come from?

    E-Print Network [OSTI]

    Veniamis, Nikolas Th

    2006-01-01T23:59:59.000Z

    In this thesis we review three case studies in multimodal logistics and transportation systems and analyze the reasons that lead to failure or success. We present the business idea and model of each case study and study ...

  17. Demand Response-Enabled Model Predictive HVAC Load Control in Buildings using Real-Time Electricity Pricing.

    E-Print Network [OSTI]

    Avci, Mesut

    2013-01-01T23:59:59.000Z

    ??A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy… (more)

  18. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01T23:59:59.000Z

    F) Enhanced ACP Date RAA ACP Demand Response – SpinningReserve Demonstration Demand Response – Spinning Reservesupply spinning reserve. Demand Response – Spinning Reserve

  19. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

    2005-01-01T23:59:59.000Z

    Fully-Automated Demand Response Test in Large Facilities14in DR systems. Demand Response using HVAC in Commercialof Fully Automated Demand Response in Large Facilities”

  20. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

    2005-01-01T23:59:59.000Z

    and Demand Response in Commercial Buildings”, Lawrencesystems. Demand Response using HVAC in Commercial BuildingsDemand Response Test in Large Facilities13 National Conference on Building

  1. CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy-2 Demand Forecast Disaggregation......................................................1-4 Statewide

  2. Demand Response | Department of Energy

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) " ,"ClickPipelinesProvedDecember 2005Department ofDOE AccidentWasteZone Modeling |Demand Response Demand

  3. Electricity Demand and Energy Consumption Management System

    E-Print Network [OSTI]

    Sarmiento, Juan Ojeda

    2008-01-01T23:59:59.000Z

    This project describes the electricity demand and energy consumption management system and its application to the Smelter Plant of Southern Peru. It is composted of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks, with backpropagation training algorithm; it is used to predict the electric power demanded every hour, with an error percentage below of 1%. This information allows management the peak demand before this happen, distributing the raise of electric load to other hours or improving those equipments that increase the demand. The simulation module is based in advanced estimation techniques, such as: parametric estimation, neural network modeling, statistic regression and previously developed models, which simulates the electric behavior of the smelter plant. These modules allow the proper planning because it allows knowing the behavior of the hourly demand and the consumption patterns of the plant, in...

  4. AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.

    E-Print Network [OSTI]

    Povinelli, Richard J.

    AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

  5. Industrial Demand Module

    Gasoline and Diesel Fuel Update (EIA)

    Boiler, Steam, and Cogeneration (BSC) Component. The BSC Component satisfies the steam demand from the PA and BLD Components. In some industries, the PA Component produces...

  6. Demand Response In California

    Broader source: Energy.gov [DOE]

    Presentation covers the demand response in California and is given at the FUPWG 2006 Fall meeting, held on November 1-2, 2006 in San Francisco, California.

  7. Individual-level and Population-level Historical Prey Demand of San Francisco Estuary Striped Bass Using a Bioenergetics Model

    E-Print Network [OSTI]

    2012-01-01T23:59:59.000Z

    bounds of error in the bioenerget- MARCH 2012 ics modelanalysis of fish bioenergetics models. Canadian Journal ofDE, Kitchell JF. 1997. Fish bioenergetics 3.0. Madison (WI):

  8. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    E-Print Network [OSTI]

    Dudley, Junqiao Han

    2010-01-01T23:59:59.000Z

    which combines the two cooling supply fans to just one asquantitatively the two cooling supply fans in the EnergyPlussupply fan has a capacity of 25,000 cfm. Model uses district heating and cooling

  9. Projecting Electricity Demand in 2050

    SciTech Connect (OSTI)

    Hostick, Donna J.; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael CW

    2014-07-01T23:59:59.000Z

    This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% ? 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly data for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.

  10. A sustainable urban logistics dashboard from the perspective of a group of logistics managers

    E-Print Network [OSTI]

    Boyer, Edmond

    A sustainable urban logistics dashboard from the perspective of a group of logistics managers standpoints. The aim of this paper is to complete existing literature by proposing a sustainable dashboard for evaluating the sustainable performance of urban delivery systems, from the perspective of operational

  11. Implementing Enterprise Lean A Look at Ogden Air Logistics Center

    E-Print Network [OSTI]

    Rebentisch, Dr. Eric E.

    2004-07-30T23:59:59.000Z

    This paper documents the enterprise-wide lean implementation effort at Ogden Air Logistics Center, Hill

  12. Our MSc in Maritime Logistics and Supply Chain Management is designed to give you state

    E-Print Network [OSTI]

    Painter, Kevin

    Logistics · Green Logistics · Supply Chain Analytics A dissertation is then completed between May - August

  13. Calculating Impacts of Energy Standards on Energy Demand in U.S. Buildings under Uncertainty with an Integrated Assessment Model: Technical Background Data

    SciTech Connect (OSTI)

    Scott, Michael J.; Daly, Don S.; Hathaway, John E.; Lansing, Carina S.; Liu, Ying; McJeon, Haewon C.; Moss, Richard H.; Patel, Pralit L.; Peterson, Marty J.; Rice, Jennie S.; Zhou, Yuyu

    2014-12-06T23:59:59.000Z

    This report presents data and assumptions employed in an application of PNNL’s Global Change Assessment Model with a newly-developed Monte Carlo analysis capability. The model is used to analyze the impacts of more aggressive U.S. residential and commercial building-energy codes and equipment standards on energy consumption and energy service costs at the state level, explicitly recognizing uncertainty in technology effectiveness and cost, socioeconomics, presence or absence of carbon prices, and climate impacts on energy demand. The report provides a summary of how residential and commercial buildings are modeled, together with assumptions made for the distributions of state–level population, Gross Domestic Product (GDP) per worker, efficiency and cost of residential and commercial energy equipment by end use, and efficiency and cost of residential and commercial building shells. The cost and performance of equipment and of building shells are reported separately for current building and equipment efficiency standards and for more aggressive standards. The report also details assumptions concerning future improvements brought about by projected trends in technology.

  14. Center for Excellence in Logistics and Distribution

    E-Print Network [OSTI]

    Noble, James S.

    #12;CELDi Focus Areas Logistics Systems Analysis and Design Material Flow Design & Improvement of in our company." · "I took away 4-5 potential ideas to go forward with to the company." · "I found four Center Designated Projects #12;Member Access to CELDi Products Login Page Project Descriptions

  15. Floating offshore wind farms : demand planning & logistical challenges of electricity generation

    E-Print Network [OSTI]

    Nnadili, Christopher Dozie, 1978-

    2009-01-01T23:59:59.000Z

    Floating offshore wind farms are likely to become the next paradigm in electricity generation from wind energy mainly because of the near constant high wind speeds in an offshore environment as opposed to the erratic wind ...

  16. Floating offshore wind farms : demand planning & logistical challenges of electricity generation .

    E-Print Network [OSTI]

    Nnadili, Christopher Dozie, 1978-

    2009-01-01T23:59:59.000Z

    ??Floating offshore wind farms are likely to become the next paradigm in electricity generation from wind energy mainly because of the near constant high wind… (more)

  17. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01T23:59:59.000Z

    shift in the short-run price elasticity of gasoline demand.A meta-analysis of the price elasticity of gasoline demand.2007. Consumer demand un- der price uncertainty: Empirical

  18. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01T23:59:59.000Z

    H. , and James M. Gri¢ n. 1983. Gasoline demand in the OECDof dynamic demand for gasoline. Journal of Econometrics 77(An empirical analysis of gasoline demand in Denmark using

  19. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01T23:59:59.000Z

    Sterner. 1991. Analysing gasoline demand elasticities: A2011. Measuring global gasoline and diesel price and incomeMutairi. 1995. Demand for gasoline in Kuwait: An empirical

  20. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

    No. ER06-615-000 CAISO Demand Response Resource User Guide -8 2.1. Demand Response Provides a Range of Benefits to8 2.2. Demand Response Benefits can be Quantified in Several

  1. C*-algebras associated with reversible extensions of logistic maps

    SciTech Connect (OSTI)

    Kwasniewski, Bartosz K [Institute of Mathematics, University of Bialystok (Poland)

    2012-10-31T23:59:59.000Z

    The construction of reversible extensions of dynamical systems presented in a previous paper by the author and A.V. Lebedev is enhanced, so that it applies to arbitrary mappings (not necessarily with open range). It is based on calculating the maximal ideal space of C*-algebras that extends endomorphisms to partial automorphisms via partial isometric representations, and involves a new set of 'parameters' (the role of parameters is played by chosen sets or ideals). As model examples, we give a thorough description of reversible extensions of logistic maps and a classification of systems associated with compression of unitaries generating homeomorphisms of the circle. Bibliography: 34 titles.

  2. Physically-based demand modeling

    E-Print Network [OSTI]

    Calloway, Terry Marshall

    1980-01-01T23:59:59.000Z

    )) ] t = E[ J' exp [- F(t -t )] T (~ ) dt1 1 os 1 t exp F ~2 ] T (zZ) dz2 0 t t = exp (- 2Ft) 7 f exp LP(&1 + 2 ] C(~2 - ~1) 0 0 d~) d Let the function g be given by 1 + 2)] ELT ( 1) T 34 t t t g(Tly T2) dT1 dT2 J J' g('Tl, s2) dT) dT2 0 0 0 0... + f J g(~1, ~2) d~2 d~l 0 0 The arguments of g are dummy variables, so t t J g(tl, tZ) dtl dt2 = f I g(t2, tl ) d~2 d~ 0 0 0 0 Since g tl' 2 g t2' tl t t '2 J' J' g(~1, ~2) dvl dt2= 2 J' J' g(xl, v2) deal d 2. 0 0 0 0 Now an assumption is made...

  3. On Demand Guarantees in Iran.

    E-Print Network [OSTI]

    Ahvenainen, Laura

    2009-01-01T23:59:59.000Z

    ??On Demand Guarantees in Iran This thesis examines on demand guarantees in Iran concentrating on bid bonds and performance guarantees. The main guarantee types and… (more)

  4. Automated Transportation Logistics and Analysis System (ATLAS)

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustionImprovement3--Logistical5/08 Attendance List1-02Evaluation Report(AO)

  5. Comparative Usability Study of Two Space Logistics Analysis Tools

    E-Print Network [OSTI]

    Lee, Chairwoo

    Future space exploration missions and campaigns will require sophisticated tools to help plan and analyze logistics. To encourage their use, space logistics tools must be usable: a design concept encompassing terms such ...

  6. Energy Demand Staff Scientist

    E-Print Network [OSTI]

    Eisen, Michael

    Energy Demand in China Lynn Price Staff Scientist February 2, 2010 #12;Founded in 1988 Focused on End-Use Energy Efficiency ~ 40 Current Projects in China Collaborations with ~50 Institutions in China Researcher #12;Talk OutlineTalk Outline · Overview · China's energy use and CO2 emission trends · Energy

  7. Autonomous Demand Response for Primary Frequency Regulation

    SciTech Connect (OSTI)

    Donnelly, Matt; Trudnowski, Daniel J.; Mattix, S.; Dagle, Jeffery E.

    2012-02-28T23:59:59.000Z

    The research documented within this report examines the use of autonomous demand response to provide primary frequency response in an interconnected power grid. The work builds on previous studies in several key areas: it uses a large realistic model (i.e., the interconnection of the western United States and Canada); it establishes a set of metrics that can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology.

  8. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST Energy Demand 2008-2018 forecast supports the analysis and recommendations of the 2007 Integrated Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly

  9. Demand Response Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies

    E-Print Network [OSTI]

    Ghatikar, Girish

    2014-01-01T23:59:59.000Z

    centers. 4. Demand Response Strategies Building from theBuilding Control Strategies and Techniques for Demand Response.Demand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Building

  10. Field Test Results of Automated Demand Response in a Large Office Building

    E-Print Network [OSTI]

    Han, Junqiao

    2008-01-01T23:59:59.000Z

    Building Control Strategies and Techniques for Demand Response,Automated Demand Response in a Large Office Building JunqiaoDemand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Building

  11. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

  12. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

  13. Decentralized demand management for water distribution

    E-Print Network [OSTI]

    Zabolio, Dow Joseph

    2012-06-07T23:59:59.000Z

    DECENTRALIZED DEMAND MANAGEMENT FOR WATER DISTRIBUTION A Thesis by DOW JOSEPH ZABOLIO, III Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May... OF THE DEMAND CURVE 30 31 35 39 Model Development Results 39 45 VI CONTROLLER DESIGN AND COSTS 49 Description of Controller Production and Installation Costs 49 50 VII SYSTEM EVALUATION AND ECONOMICS 53 System Response and Degree of Control...

  14. NERSC/DOE BER Requirements Meeting Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challengeMultiscaleLogos NERSC Logos NERSCWins1PresentationsLogistics Hotel

  15. NERSC/DOE BES Requirements Workshop Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challengeMultiscaleLogos NERSC LogosAttendees AttendeesAgendaLogistics

  16. NERSC/DOE FES Requirements Workshop Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challengeMultiscaleLogos NERSCJeffrey B. Neaton JeffreyTony LaddLogistics

  17. NERSC/DOE HEP 2012 Review Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challengeMultiscaleLogos NERSCJeffrey B.Stephen Jardin StephenLogistics

  18. Felton Bay Logistics, LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision has beenFfe2fb55-352f-473b-a2dd-50ae8b27f0a6 NoSan Leandro,LawFEMAProjectExpressFelton Bay Logistics, LLC

  19. Techno-economic analysis of using corn stover to supply heat and power to a corn ethanol plant - Part 1: Cost of feedstock supply logistics

    SciTech Connect (OSTI)

    Sokhansanj, Shahabaddine [ORNL; Mani, Sudhagar [University of Georgia; Togore, Sam [U.S. Department of Energy; Turhollow Jr, Anthony F [ORNL

    2010-01-01T23:59:59.000Z

    Supply of corn stover to produce heat and power for a typical 170 dam3 dry mill ethanol plant is proposed. The corn ethanol plant requires 5.6 MW of electricity and 52.3 MW of process heat, which creates the annual stover demand of as much as 140 Gg. The corn stover supply system consists of collection, preprocessing, transportation and on-site fuel storage and preparation to produce heat and power for the ethanol plant. Economics of the entire supply system was conducted using the Integrated Biomass Supply Analysis and Logistics (IBSAL) simulation model. Corn stover was delivered in three formats (square bales, dry chops and pellets) to the combined heat and power plant. Delivered cost of biomass ready to be burned was calculated at 73 $ Mg-1 for bales, 86 $ Mg-1 for pellets and 84 $ Mg-1 for field chopped biomass. Among the three formats of stover supply systems, delivered cost of pelleted biomass was the highest due to high pelleting cost. Bulk transport of biomass in the form of chops and pellets can provide a promising future biomass supply logistic system in the US, if the costs of pelleting and transport are minimized.

  20. International Oil Supplies and Demands. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1991-09-01T23:59:59.000Z

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  1. International Oil Supplies and Demands. Volume 2

    SciTech Connect (OSTI)

    Not Available

    1992-04-01T23:59:59.000Z

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  2. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    BEST PRACTICES AND RESULTS OF DR IMPLEMENTATION . 31 Encouraging End-User Participation: The Role of Incentives 16 Demand Response

  3. Hawaii demand-side management resource assessment. Final report, Reference Volume 3 -- Residential and commercial sector DSM analyses: Detailed results from the DBEDT DSM assessment model; Part 1, Technical potential

    SciTech Connect (OSTI)

    NONE

    1995-04-01T23:59:59.000Z

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. Numerous tables and figures illustrating the technical potential for demand-side management are included.

  4. Climate policy implications for agricultural water demand

    SciTech Connect (OSTI)

    Chaturvedi, Vaibhav; Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Wise, Marshall A.; Calvin, Katherine V.

    2013-03-28T23:59:59.000Z

    Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of two alternative land-use emissions mitigation policy options—one which taxes terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which only taxes fossil fuel and industrial emissions but places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to almost triple demand for water for agricultural systems across the century even in the absence of climate policy. In general policies to mitigate climate change increase agricultural demands for water still further, though the largest changes occur in the second half of the century, under both policy regimes. The two policies examined profoundly affected both the sources and magnitudes of the increase in irrigation water demands. The largest increases in agricultural irrigation water demand occurred in scenarios where only fossil fuel emissions were priced (but not land-use change emission) and were primarily driven by rapid expansion in bioenergy production. In these scenarios water demands were large relative to present-day total available water, calling into question whether it would be physically possible to produce the associated biomass energy. We explored the potential of improved water delivery and irrigation system efficiencies. These could potentially reduce demands substantially. However, overall demands remained high under our fossil-fuel-only tax policy. In contrast, when all carbon was priced, increases in agricultural water demands were smaller than under the fossil-fuel-only policy and were driven primarily by increased demands for water by non-biomass crops such as rice. Finally we estimate the geospatial pattern of water demands and find that regions such as China, India and other countries in south and east Asia might be expected to experience greatest increases in water demands.?

  5. Demand Dispatch-Intelligent

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation Proposed Newcatalyst phasesData Files Data FilesFeFe-HydrogenaseDemand

  6. Customer focused collaborative demand planning

    E-Print Network [OSTI]

    Jha, Ratan (Ratan Mohan)

    2008-01-01T23:59:59.000Z

    Many firms worldwide have adopted the process of Sales & Operations Planning (S&OP) process where internal departments within a firm collaborate with each other to generate a demand forecast. In a collaborative demand ...

  7. Demand Response: Load Management Programs

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01T23:59:59.000Z

    CenterPoint Load Management Programs CATEE Conference October, 2012 Agenda Outline I. General Demand Response Definition II. General Demand Response Program Rules III. CenterPoint Commercial Program IV. CenterPoint Residential Programs... V. Residential Discussion Points Demand Response Definition of load management per energy efficiency rule 25.181: ? Load control activities that result in a reduction in peak demand, or a shifting of energy usage from a peak to an off...

  8. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 Gorin Principal Authors Lynn Marshall Project Manager Kae C. Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting

  9. Demand Forecasting of New Products

    E-Print Network [OSTI]

    Sun, Yu

    Demand Forecasting of New Products Using Attribute Analysis Marina Kang A thesis submitted Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock upon currently employed new-SKU demand forecasting methods which involve the processing of large

  10. Assessment of Demand Response Resource

    E-Print Network [OSTI]

    Assessment of Demand Response Resource Potentials for PGE and Pacific Power Prepared for: Portland January 15, 2004 K:\\Projects\\2003-53 (PGE,PC) Assess Demand Response\\Report\\Revised Report_011504.doc #12;#12;quantec Assessment of Demand Response Resource Potentials for I-1 PGE and Pacific Power I. Introduction

  11. PAR and Supply Distribution System The PAR Program is administered by Materials Logistics (Central Distribution)

    E-Print Network [OSTI]

    Oliver, Douglas L.

    Logistics (Central Distribution) Services, a division of Materials Management. · The PAR Program is focused Administration: 1. See attached exhibit Models, 1-3 2. See Related Materials Management Forms 3. Weekly action group meeting(s) established to continue the work and ensuring good supply chain/materials management

  12. Ethanol Demand in United States Gasoline Production

    SciTech Connect (OSTI)

    Hadder, G.R.

    1998-11-24T23:59:59.000Z

    The Oak Ridge National Laboratory (OWL) Refinery Yield Model (RYM) has been used to estimate the demand for ethanol in U.S. gasoline production in year 2010. Study cases examine ethanol demand with variations in world oil price, cost of competing oxygenate, ethanol value, and gasoline specifications. For combined-regions outside California summer ethanol demand is dominated by conventional gasoline (CG) because the premised share of reformulated gasoline (RFG) production is relatively low and because CG offers greater flexibility for blending high vapor pressure components like ethanol. Vapor pressure advantages disappear for winter CG, but total ethanol used in winter RFG remains low because of the low RFG production share. In California, relatively less ethanol is used in CG because the RFG production share is very high. During the winter in California, there is a significant increase in use of ethanol in RFG, as ethanol displaces lower-vapor-pressure ethers. Estimated U.S. ethanol demand is a function of the refiner value of ethanol. For example, ethanol demand for reference conditions in year 2010 is 2 billion gallons per year (BGY) at a refiner value of $1.00 per gallon (1996 dollars), and 9 BGY at a refiner value of $0.60 per gallon. Ethanol demand could be increased with higher oil prices, or by changes in gasoline specifications for oxygen content, sulfur content, emissions of volatile organic compounds (VOCS), and octane numbers.

  13. Satisfiability of Elastic Demand in the Smart Grid

    E-Print Network [OSTI]

    Tomozei, Dan-Cristian

    2010-01-01T23:59:59.000Z

    We study a stochastic model of electricity production and consumption where appliances are adaptive and adjust their consumption to the available production, by delaying their demand and possibly using batteries. The model incorporates production volatility due to renewables, ramp-up time, uncertainty about actual demand versus planned production, delayed and evaporated demand due to adaptation to insufficient supply. We study whether threshold policies stabilize the system. The proofs use Markov chain theory on general state space.

  14. Smart Grid RFI: Addressing Policy and Logistical Challenges,...

    Broader source: Energy.gov (indexed) [DOE]

    Challenges, Comments from the Edison Electric Institute Smart Grid RFI: Addressing Policy and Logistical Challenges, Comments from the Edison Electric Institute The Edison Electric...

  15. Addressing Policy and Logistical Challenges to smart grid Implementati...

    Broader source: Energy.gov (indexed) [DOE]

    smart grid Implementation: eMeter Response to Department of Energy RFI Addressing Policy and Logistical Challenges to smart grid Implementation: eMeter Response to Department of...

  16. Smart Grid RFI: Addressing Policy and Logistical Challenges....

    Broader source: Energy.gov (indexed) [DOE]

    Challenges. Comments of the Alliance to Save Energy. Smart Grid RFI: Addressing Policy and Logistical Challenges. Comments of the Alliance to Save Energy. The Alliance to Save...

  17. Okaloosa Gas District Smart Grid RFI: Addressing Policy and Logistical...

    Broader source: Energy.gov (indexed) [DOE]

    Okaloosa Gas District Smart Grid RFI: Addressing Policy and Logistical Challenges to Smart Grid Implementation Okaloosa Gas District Smart Grid RFI: Addressing Policy and...

  18. Addressing Policy and Logistical Challenges to Smart Grid Implementati...

    Broader source: Energy.gov (indexed) [DOE]

    Smart Grid Implementation: Federal Register Notice Volume 75, No. 180 - Sep. 17, 2010 Addressing Policy and Logistical Challenges to Smart Grid Implementation: Federal Register...

  19. Addressing Policy and Logistical Challenges to Smart Grid Implementati...

    Broader source: Energy.gov (indexed) [DOE]

    Smart Grid Implementation: Comments by the Office of the Ohio Consumers' Counsel Addressing Policy and Logistical Challenges to Smart Grid Implementation: Comments by the Office of...

  20. Modeling Interplanetary Logistics: A Mathematical Model for Mission Planning

    E-Print Network [OSTI]

    de Weck, Olivier L.

    to develop a sustainable space transportation architecture it is critical that interplanetary supply chain a sustainable architecture it is necessary to recognize the interdependencies between missions and how missions, a reduction in cost can be achieved which promotes a more sustainable system architecture

  1. Fraunhofer Project Group in Transport and Logistics at NICTA

    E-Print Network [OSTI]

    Heiser, Gernot

    in Transport and Logistics · Further enhances Australia's position in the global innovation system. The NICTAFraunhofer Project Group in Transport and Logistics at NICTA NICTA and the Fraunhofer Institute for Experimental Software Engineering (IESE) have established the Fraunhofer Project Group on Transport

  2. Demand Response Programs, 6. edition

    SciTech Connect (OSTI)

    NONE

    2007-10-15T23:59:59.000Z

    The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demand response programs, energy providers and ISOs interested in offering demand response programs, and consultants and analysts looking for detailed information on demand response technology, applications, and participants. The report offers a look at the current Demand Response environment in the energy industry by: defining what demand response programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demand response; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demand response programs; and, providing a look at major demand response programs.

  3. INVENTORY MANAGEMENT WITH PARTIALLY OBSERVED NONSTATIONARY DEMAND

    E-Print Network [OSTI]

    Ludkovski, Mike

    INVENTORY MANAGEMENT WITH PARTIALLY OBSERVED NONSTATIONARY DEMAND ERHAN BAYRAKTAR AND MICHAEL LUDKOVSKI Abstract. We consider a continuous-time model for inventory management with Markov mod- ulated non inventory level. We then solve this equivalent formulation and directly characterize an optimal inventory

  4. SHORT-RUN MONEY DEMAND Laurence Ball

    E-Print Network [OSTI]

    Niebur, Ernst

    SHORT-RUN MONEY DEMAND Laurence Ball Johns Hopkins University August 2002 I am grateful with Goldfeld's partial adjustment model. A key innovation is the choice of the interest rate in the money on "near monies" -- close substitutes for M1 such as savings accounts and money market mutual funds

  5. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    and D. Kathan (2009). Demand Response in U.S. ElectricityEnergy Financial Group. Demand Response Research Center [2008). Assessment of Demand Response and Advanced Metering.

  6. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    Like HECO actual utility demand response implementations canindustry-wide utility demand response applications tend toobjective. Figure 4. Demand Response Objectives 17  

  7. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

    23 ii Retail Demand Response in SPP List of Figures and10 Figure 3. Demand Response Resources by11 Figure 4. Existing Demand Response Resources by Type of

  8. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01T23:59:59.000Z

    for each day type for the demand response study - moderate8.4 Demand Response Integration . . . . . . . . . . .for each day type for the demand response study - moderate

  9. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

    Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

    2008-01-01T23:59:59.000Z

    their partnership in demand response automation research andand Techniques for Demand Response. LBNL Report 59975. Mayof Fully Automated Demand Response in Large Facilities.

  10. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

    Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

    2006-01-01T23:59:59.000Z

    Fully Automated Demand Response Tests in Large Facilities”of Fully Automated Demand Response in Large Facilities”,was coordinated by the Demand Response Research Center and

  11. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    2 2.0 Demand ResponseFully Automated Demand Response Tests in Large Facilities,was coordinated by the Demand Response Research Center and

  12. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    of Energy demand-side management energy information systemdemand response. Demand-side management (DSM) program goalsa goal for demand-side management (DSM) coordination and

  13. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    3 2.1 Demand-Side Managementbuildings. The demand side management framework is discussedIssues 2.1 Demand-Side Management Framework Forecasting

  14. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    and best practices to guide HECO demand response developmentbest practices for DR renewable integration – Technically demand responseof best practices. This is partially because demand response

  15. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    of control. Water heater demand response options are notcurrent water heater and air conditioning demand responsecustomer response Demand response water heater participation

  16. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    District Small Business Summer Solutions: Energy and DemandSummer Solutions: Energy and Demand Impacts Monthly Energy> B-2 Coordination of Energy Efficiency and Demand Response

  17. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01T23:59:59.000Z

    World: Renewable Energy and Demand Response Proliferation intogether the renewable energy and demand response communityimpacts of renewable energy and demand response integration

  18. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

    Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

    2006-01-01T23:59:59.000Z

    Strategies for Demand Response in Commercial Buildings DavidStrategies for Demand Response in Commercial Buildings Davidadjusted for demand response in commercial buildings. The

  19. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

    Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

    2008-01-01T23:59:59.000Z

    Demand Response Systems National Conference on BuildingDemand Response Systems National Conference on BuildingDemand Response Systems National Conference on Building

  20. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    In terms of demand response capability, building operatorsautomated demand response and improve building energy andand demand response features directly into building design

  1. China's Coal: Demand, Constraints, and Externalities

    E-Print Network [OSTI]

    Aden, Nathaniel

    2010-01-01T23:59:59.000Z

    raising transportation oil demand. Growing internationalcoal by wire could reduce oil demand by stemming coal roadEastern oil production. The rapid growth of coal demand

  2. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    DEMAND RESPONSE .7 Wholesale Marketuse at times of high wholesale market prices or when systemenergy expenditure. In wholesale markets, spot energy prices

  3. Source Recertification, Refurbishment, and Transfer Logistics

    SciTech Connect (OSTI)

    Gastelum, Zoe N.; Duckworth, Leesa L.; Greenfield, Bryce A.; Doll, Stephanie R.

    2013-09-01T23:59:59.000Z

    The 2012 Gap Analysis of Department of Energy Radiological Sealed Sources, Standards, and Materials for Safeguards Technology Development [1] report, and the subsequent Reconciliation of Source Needs and Surpluses across the U.S. Department of Energy National Laboratory Complex [2] report, resulted in the identification of 33 requests for nuclear or radiological sealed sources for which there was potentially available, suitable material from within the U.S. Department of Energy (DOE) complex to fill the source need. Available, suitable material was defined by DOE laboratories as material slated for excess, or that required recertification or refurbishment before being used for safeguards technology development. This report begins by outlining the logistical considerations required for the shipment of nuclear and radiological materials between DOE laboratories. Then, because of the limited need for transfer of matching sources, the report also offers considerations for an alternative approach – the shipment of safeguards equipment between DOE laboratories or technology testing centers. Finally, this report addresses repackaging needs for the two source requests for which there was available, suitable material within the DOE complex.

  4. Division of IT Convergence Engineering Optimal Demand-Side Energy Management Under

    E-Print Network [OSTI]

    Boutaba, Raouf

    Division of IT Convergence Engineering Optimal Demand-Side Energy Management Under Real-time Demand of appliance specific adapters. Designed and implemented GHS Modeled the demand-side energy management problem (NP-hard) Designed a scheduling algorithm for demand side energy management Showed that our

  5. FROM PLANT AND LOGISTICS CONTROL TO MULTI-ENTERPRISE COLLABORATION: Milestone report of the Manufacturing & Logistics Systems Coordinating Committee

    E-Print Network [OSTI]

    Boyer, Edmond

    , product life cycles shrink, and profit margins decrease. In addition, the capital costs of manufacturing of the Manufacturing & Logistics Systems Coordinating Committee S.Y. Nofa* , G. Morelb , L. Monostoric , A. Molinad , F-765-494-1299 Abstract: Current and emerging manufacturing and logistics systems are posing new challenges

  6. Demand Response and Energy Efficiency

    E-Print Network [OSTI]

    Demand Response & Energy Efficiency International Conference for Enhanced Building Operations ESL-IC-09-11-05 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 2 ?Less than 5... for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 5 What is Demand Response? ?The temporary reduction of electricity demanded from the grid by an end-user in response to capacity shortages, system reliability events, or high wholesale...

  7. Centralized and Decentralized Control for Demand Response

    SciTech Connect (OSTI)

    Lu, Shuai; Samaan, Nader A.; Diao, Ruisheng; Elizondo, Marcelo A.; Jin, Chunlian; Mayhorn, Ebony T.; Zhang, Yu; Kirkham, Harold

    2011-04-29T23:59:59.000Z

    Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity, and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.

  8. Wireless Demand Response Controls for HVAC Systems

    SciTech Connect (OSTI)

    Federspiel, Clifford

    2009-06-30T23:59:59.000Z

    The objectives of this scoping study were to develop and test control software and wireless hardware that could enable closed-loop, zone-temperature-based demand response in buildings that have either pneumatic controls or legacy digital controls that cannot be used as part of a demand response automation system. We designed a SOAP client that is compatible with the Demand Response Automation Server (DRAS) being used by the IOUs in California for their CPP program, design the DR control software, investigated the use of cellular routers for connecting to the DRAS, and tested the wireless DR system with an emulator running a calibrated model of a working building. The results show that the wireless DR system can shed approximately 1.5 Watts per design CFM on the design day in a hot, inland climate in California while keeping temperatures within the limits of ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy.

  9. Driving Demand | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    strategies, results achieved to date, and advice for other programs. Driving Demand for Home Energy Improvements. This guide, developed by the Lawrence Berkeley National...

  10. Demand Response Technology Roadmap A

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    workshop agendas, presentation materials, and transcripts. For the background to the Demand Response Technology Roadmap and to make use of individual roadmaps, the reader is...

  11. Demand Response Technology Roadmap M

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    between May 2014 and February 2015. The Bonneville Power Administration (BPA) Demand Response Executive Sponsor Team decided upon the scope of the project in May. Two subsequent...

  12. System Demand-Side Management: Regional results

    SciTech Connect (OSTI)

    Englin, J.E.; Sands, R.D.; De Steese, J.G.; Marsh, S.J.

    1990-05-01T23:59:59.000Z

    To improve the Bonneville Power Administration's (Bonneville's) ability to analyze the value and impacts of demand-side programs, Pacific Northwest Laboratory (PNL) developed and implemented the System Demand-Side Management (SDSM) model, a microcomputer-based model of the Pacific Northwest Public Power system. This document outlines the development and application of the SDSM model, which is an hourly model. Hourly analysis makes it possible to examine the change in marginal revenues and marginal costs that accrue from the movement of energy consumption from daytime to nighttime. It also allows a more insightful analysis of programs such as water heater control in the context of hydroelectric-based generation system. 7 refs., 10 figs., 10 tabs.

  13. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product estimates. Margaret Sheridan provided the residential forecast. Mitch Tian prepared the peak demand

  14. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

  15. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

    Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the

  16. Honeywell Demonstrates Automated Demand Response Benefits for...

    Office of Environmental Management (EM)

    Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility,...

  17. China, India demand cushions prices

    SciTech Connect (OSTI)

    Boyle, M.

    2006-11-15T23:59:59.000Z

    Despite the hopes of coal consumers, coal prices did not plummet in 2006 as demand stayed firm. China and India's growing economies, coupled with solid supply-demand fundamentals in North America and Europe, and highly volatile prices for alternatives are likely to keep physical coal prices from wide swings in the coming year.

  18. Harnessing the power of demand

    SciTech Connect (OSTI)

    Sheffrin, Anjali; Yoshimura, Henry; LaPlante, David; Neenan, Bernard

    2008-03-15T23:59:59.000Z

    Demand response can provide a series of economic services to the market and also provide ''insurance value'' under low-likelihood, but high-impact circumstances in which grid reliablity is enhanced. Here is how ISOs and RTOs are fostering demand response within wholesale electricity markets. (author)

  19. Automated Demand Response and Commissioning

    SciTech Connect (OSTI)

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

    2005-04-01T23:59:59.000Z

    This paper describes the results from the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

  20. NALDA (Naval Aviation Logistics Data Analysis) CAI (computer aided instruction)

    SciTech Connect (OSTI)

    Handler, B.H. (Oak Ridge K-25 Site, TN (USA)); France, P.A.; Frey, S.C.; Gaubas, N.F.; Hyland, K.J.; Lindsey, A.M.; Manley, D.O. (Oak Ridge Associated Universities, Inc., TN (USA)); Hunnum, W.H. (North Carolina Univ., Chapel Hill, NC (USA)); Smith, D.L. (Memphis State Univ., TN (USA))

    1990-07-01T23:59:59.000Z

    Data Systems Engineering Organization (DSEO) personnel developed a prototype computer aided instruction CAI system for the Naval Aviation Logistics Data Analysis (NALDA) system. The objective of this project was to provide a CAI prototype that could be used as an enhancement to existing NALDA training. The CAI prototype project was performed in phases. The task undertaken in Phase I was to analyze the problem and the alternative solutions and to develop a set of recommendations on how best to proceed. The findings from Phase I are documented in Recommended CAI Approach for the NALDA System (Duncan et al., 1987). In Phase II, a structured design and specifications were developed, and a prototype CAI system was created. A report, NALDA CAI Prototype: Phase II Final Report, was written to record the findings and results of Phase II. NALDA CAI: Recommendations for an Advanced Instructional Model, is comprised of related papers encompassing research on computer aided instruction CAI, newly developing training technologies, instructional systems development, and an Advanced Instructional Model. These topics were selected because of their relevancy to the CAI needs of NALDA. These papers provide general background information on various aspects of CAI and give a broad overview of new technologies and their impact on the future design and development of training programs. The paper within have been index separately elsewhere.

  1. Autoregressive Time Series Forecasting of Computational Demand

    E-Print Network [OSTI]

    Sandholm, Thomas

    2007-01-01T23:59:59.000Z

    We study the predictive power of autoregressive moving average models when forecasting demand in two shared computational networks, PlanetLab and Tycoon. Demand in these networks is very volatile, and predictive techniques to plan usage in advance can improve the performance obtained drastically. Our key finding is that a random walk predictor performs best for one-step-ahead forecasts, whereas ARIMA(1,1,0) and adaptive exponential smoothing models perform better for two and three-step-ahead forecasts. A Monte Carlo bootstrap test is proposed to evaluate the continuous prediction performance of different models with arbitrary confidence and statistical significance levels. Although the prediction results differ between the Tycoon and PlanetLab networks, we observe very similar overall statistical properties, such as volatility dynamics.

  2. DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION

    SciTech Connect (OSTI)

    Fisk, William J.; Mendell, Mark J.; Davies, Molly; Eliseeva, Ekaterina; Faulkner, David; Hong, Tienzen; Sullivan, Douglas P.

    2014-01-06T23:59:59.000Z

    This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included: ? The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).? Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.? Currently-available optical people counting systems work well much of the time but have large counting errors in some situations. ? In meeting rooms, measurements of carbon dioxide at return-air grilles appear to be a better choice than wall-mounted sensors.? In California, demand controlled ventilation in general office spaces is projected to save significant energy and be cost effective only if typical VRs without demand controlled ventilation are very high relative to VRs in codes. Based on the research, several recommendations were developed for demand controlled ventilation specifications in the California Title 24 Building Energy Efficiency Standards.The research on classroom ventilation collected data over two years on California elementary school classrooms to investigate associations between VRs and student illness absence (IA). Major findings included: ? Median classroom VRs in all studied climate zones were below the California guideline, and 40percent lower in portable than permanent buildings.? Overall, one additional L/s per person of VR was associated with 1.6percent less IA. ? Increasing average VRs in California K-12 classrooms from the current average to the required level is estimated to decrease IA by 3.4percent, increasing State attendance-based funding to school districts by $33M, with $6.2 M in increased energy costs. Further VR increases would provide additional benefits.? Confirming these findings in intervention studies is recommended. ? Energy costs of heating/cooling unoccupied classrooms statewide are modest, but a large portion occurs in relatively few classrooms.

  3. Lessons for China from a comparison of logistics in the U.S. and China

    E-Print Network [OSTI]

    Xiong, Ming, S.M. Massachusetts Institute of Technology

    2010-01-01T23:59:59.000Z

    Logistics efficiency is low in China. In 2008, total logistics costs accounted for 18.1% of gross domestic product (GDP) in China, which was almost twice that of the United States. Increasing logistics efficiency can save ...

  4. Our MSc Logistics and Supply Chain Management is designed to give you state of the

    E-Print Network [OSTI]

    Painter, Kevin

    Systems Choose 3 from: · Supply Chain Analytics · Operations Management · Humanitarian Logistics · Green Logistics · Maritime Business and Economics · Maritime Logistics Global Purchasing and Supply Supply Chain

  5. High Level Overview of DOE Biomass Logistics II Project Activities

    Broader source: Energy.gov [DOE]

    Breakout Session 1B—Integration of Supply Chains I: Breaking Down Barriers High Level Overview of DOE Biomass Logistics II Project Activities Kevin Comer, Associate Principal, Antares Group Inc.

  6. Topics in ordinal logistic regression and its applications

    E-Print Network [OSTI]

    Kim, Hyun Sun

    2004-11-15T23:59:59.000Z

    Sample size calculation methods for ordinal logistic regression are proposed to test statistical hypotheses. The author was motivated to do this work by the need for statistical analysis of the red imported ?re ants data. The proposed methods...

  7. The Value of Lead Logistics Services Oliver Schneider1

    E-Print Network [OSTI]

    Boyer, Edmond

    for Enterprise Sciences (BWI), 8092 Zurich, Switzerland oschneider@ethz.ch 2 Kuehne + Nagel Management AG, 8834 Schindellegi, Switzerland andre.lindner@kuehne-nagel.com Abstract. Logistics Services are one of the most

  8. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01T23:59:59.000Z

    global gasoline and diesel price and income elasticities.shift in the short-run price elasticity of gasoline demand.Habits and Uncertain Relative Prices: Simulating Petrol Con-

  9. A Review of Green Logistics Schemes Used in Cities Around the World

    E-Print Network [OSTI]

    Geroliminis, Nikolaos; Daganzo, Carlos F.

    2005-01-01T23:59:59.000Z

    Table 2: Examples of green logistics schemes Geroliminisand Daganzo: "Green Logistics" Schemes around the world E XGerolìmìnìs and Daganzo: "Green Logìstìcs" Schemes around

  10. E-Print Network 3.0 - air logistics center Sample Search Results

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Sciences 16 Center for Excellence in Logistics and Distribution Summary: Sponsor: Oklahoma City Air Logistics Center Principal Investigator: Dr. Satish Bukkapatnam...

  11. Full Rank Rational Demand Systems

    E-Print Network [OSTI]

    LaFrance, Jeffrey T; Pope, Rulon D.

    2006-01-01T23:59:59.000Z

    as a nominal income full rank QES. R EFERENCES (A.84)S. G. Donald. “Inferring the Rank of a Matrix. ” Journal of97-102. . “A Demand System Rank Theorem. ” Econometrica 57 (

  12. Marketing Demand-Side Management

    E-Print Network [OSTI]

    O'Neill, M. L.

    1988-01-01T23:59:59.000Z

    Demand-Side Management is an organizational tool that has proven successful in various realms of the ever changing business world in the past few years. It combines the multi-faceted desires of the customers with the increasingly important...

  13. Community Water Demand in Texas

    E-Print Network [OSTI]

    Griffin, Ronald C.; Chang, Chan

    Solutions to Texas water policy and planning problems will be easier to identify once the impact of price upon community water demand is better understood. Several important questions cannot be addressed in the absence of such information...

  14. Supply Chain Networks, Electronic Commerce, and Supply Side and Demand Side Risk

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Networks, Electronic Commerce, and Supply Side and Demand Side Risk Anna Nagurney as well as demand side risk are included in the formulation. The model consists of three tiers of decision chain network equilibrium model with electronic com- merce and with supply side and demand side risk

  15. Demand Response Spinning Reserve Demonstration

    SciTech Connect (OSTI)

    Eto, Joseph H.; Nelson-Hoffman, Janine; Torres, Carlos; Hirth,Scott; Yinger, Bob; Kueck, John; Kirby, Brendan; Bernier, Clark; Wright,Roger; Barat, A.; Watson, David S.

    2007-05-01T23:59:59.000Z

    The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

  16. Demand Response and Open Automated Demand Response Opportunities for Data Centers

    E-Print Network [OSTI]

    Mares, K.C.

    2010-01-01T23:59:59.000Z

    Standardized Automated Demand Response Signals. Presented atand Automated Demand Response in Industrial RefrigeratedActions for Industrial Demand Response in California. LBNL-

  17. Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    A. Barat, D. Watson. 2006 Demand Response Spinning ReserveKueck, and B. Kirby 2008. Demand Response Spinning ReserveReport 2009. Open Automated Demand Response Communications

  18. Driving change : evaluating strategies to control automotive energy demand growth in China

    E-Print Network [OSTI]

    Bonde Åkerlind, Ingrid Gudrun

    2013-01-01T23:59:59.000Z

    As the number of vehicles in China has relentlessly grown in the past decade, the energy demand, fuel demand and greenhouse gas emissions associated with these vehicles have kept pace. This thesis presents a model to project ...

  19. Inventory Management of Perishable Goods under Demand Variability

    E-Print Network [OSTI]

    Ayoub, Wisam Hanna

    2013-08-01T23:59:59.000Z

    science and economic parameters examining the impacts of different demand specifications on the cost minimization and profit maximization problem of fluid milk. The square root model from the food science literature is used to estimate the shelf...

  20. Exchange Rate Effects on Excess Demand in the United States for Canadian Oil .

    E-Print Network [OSTI]

    Dickey, James

    2011-01-01T23:59:59.000Z

    ??This paper examines a model of excess supply and excess demand for Canadian oil in the United States utilizing an error correction model and time… (more)

  1. Assessment of Industrial Load for Demand Response across Western Interconnect

    SciTech Connect (OSTI)

    Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL; Ma, Ookie [United States Department of Energy (DOE), Office of Efficiency and Renewable Energy (EERE)

    2013-11-01T23:59:59.000Z

    Demand response (DR) has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles that can provide more regional understanding and can be inserted into analysis software for further study. The developed framework utilizes a number of different informational resources, algorithms, and real-world measurements to perform a bottom-up approach in the development of a new database with representation of the potential demand response resource in the industrial sector across the U.S. This tool houses statistical values of energy and demand response (DR) potential by industrial plant and geospatially locates the information for aggregation for different territories without proprietary information. This report will discuss this framework and the analyzed quantities of demand response for Western Interconnect (WI) in support of evaluation of the cost production modeling with power grid modeling efforts of demand response.

  2. The interpretation of Charpy impact test data using hyper-logistic fitting functions

    SciTech Connect (OSTI)

    Helm, J.L. [Columbia Univ., New York, NY (United States)

    1996-12-31T23:59:59.000Z

    The hyperbolic tangent function is used almost exclusively for computer assisted curve fitting of Charpy impact test data. Unfortunately, there is no physical basis to justify the use of this function and it cannot be generalized to test data that exhibits asymmetry. Using simple physical arguments, a semi-empirical model is derived and identified as a special case of the so called hyper-logistic equation. Although one solution of this equation is the hyperbolic tangent, other more physically interpretable solutions are provided. From the mathematics of the family of functions derived from the hyper-logistic equation, several useful generalizations are made such that asymmetric and wavy Charpy data can be physically interpreted.

  3. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01T23:59:59.000Z

    Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning ReserveFormat of 2009-2011 Demand Response Activity Applications.

  4. CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY FORECAST Volume 1 in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard. Margaret Sheridan contributed to the residential forecast. Mitch Tian prepared the peak demand

  5. CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY FORECAST Volume 2 Director #12; i ACKNOWLEDGEMENTS The demand forecast is the combined product prepared the peak demand forecast. Ravinderpal Vaid provided the projections of commercial

  6. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

    McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

    2008-01-01T23:59:59.000Z

    California Energy Demand Scenario Projections to 2050 RyanCEC (2003a) California energy demand 2003-2013 forecast.CEC (2005a) California energy demand 2006-2016: Staff energy

  7. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    and Demand Response A pilot program from NSTAR in Massachusetts,Massachusetts, aiming to test whether an intensive program of energy efficiency and demand response

  8. Supply chain planning decisions under demand uncertainty

    E-Print Network [OSTI]

    Huang, Yanfeng Anna

    2008-01-01T23:59:59.000Z

    Sales and operational planning that incorporates unconstrained demand forecasts has been expected to improve long term corporate profitability. Companies are considering such unconstrained demand forecasts in their decisions ...

  9. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    California Long-term Energy Efficiency Strategic Plan. B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Response

  10. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

    McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

    2008-01-01T23:59:59.000Z

    annual per-capita electricity consumption by demand15 California electricity consumption projections by demandannual per-capita electricity consumption by demand

  11. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

    McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

    2008-01-01T23:59:59.000Z

    Vehicle Conventional and Alternative Fuel Response Simulatormodified to include alternative fuel demand scenarios (whichvehicle adoption and alternative fuel demand) later in the

  12. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01T23:59:59.000Z

    for Demand Response Technology Development The objective ofin planning demand response technology RD&D by conductingNew and Emerging Technologies into the California Smart Grid

  13. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    sector, the demand response potential of California buildinga demand response event prohibit a building’s participationdemand response strategies in California buildings are

  14. Benchmarking transportation logistics practices for effective system planning

    SciTech Connect (OSTI)

    Thrower, A.W. [Office of Civilian Radioactive Waste Management, U.S. Dept. of Energy, Washington, DC (United States); Dravo, A.N. [Booz Allen Hamilton, Washington, DC (United States); Keister, M. [Idaho National Laboratory, ID (United States)

    2007-07-01T23:59:59.000Z

    This paper presents preliminary findings of an Office of Civilian Radioactive Waste Management (OCRWM) benchmarking project to identify best practices for logistics enterprises. The results will help OCRWM's Office of Logistics Management (OLM) design and implement a system to move spent nuclear fuel (SNF) and high-level radioactive waste (HLW) to the Yucca Mountain repository for disposal when that facility is licensed and built. This report suggests topics for additional study. The project team looked at three Federal radioactive material logistics operations that are widely viewed to be successful: (1) the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico; (2) the Naval Nuclear Propulsion Program (NNPP); and (3) domestic and foreign research reactor (FRR) SNF acceptance programs. (authors)

  15. Turkey's energy demand and supply

    SciTech Connect (OSTI)

    Balat, M. [Sila Science, Trabzon (Turkey)

    2009-07-01T23:59:59.000Z

    The aim of the present article is to investigate Turkey's energy demand and the contribution of domestic energy sources to energy consumption. Turkey, the 17th largest economy in the world, is an emerging country with a buoyant economy challenged by a growing demand for energy. Turkey's energy consumption has grown and will continue to grow along with its economy. Turkey's energy consumption is high, but its domestic primary energy sources are oil and natural gas reserves and their production is low. Total primary energy production met about 27% of the total primary energy demand in 2005. Oil has the biggest share in total primary energy consumption. Lignite has the biggest share in Turkey's primary energy production at 45%. Domestic production should be to be nearly doubled by 2010, mainly in coal (lignite), which, at present, accounts for almost half of the total energy production. The hydropower should also increase two-fold over the same period.

  16. Skull Retrieval for Craniosynostosis Using Sparse Logistic Regression Models

    E-Print Network [OSTI]

    Washington at Seattle, University of

    diagnosed, quantifying the severity of the ab- normality is much more subjective and not a standard part

  17. Open Automated Demand Response Communications Specification (Version 1.0)

    SciTech Connect (OSTI)

    Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Koch, Ed; Hennage, Dan; Palensky, Peter; McParland, Charles

    2009-02-28T23:59:59.000Z

    The development of the Open Automated Demand Response Communications Specification, also known as OpenADR or Open Auto-DR, began in 2002 following the California electricity crisis. The work has been carried out by the Demand Response Research Center (DRRC), which is managed by Lawrence Berkeley National Laboratory. This specification describes an open standards-based communications data model designed to facilitate sending and receiving demand response price and reliability signals from a utility or Independent System Operator to electric customers. OpenADR is one element of the Smart Grid information and communications technologies that are being developed to improve optimization between electric supply and demand. The intention of the open automated demand response communications data model is to provide interoperable signals to building and industrial control systems that are preprogrammed to take action based on a demand response signal, enabling a demand response event to be fully automated, with no manual intervention. The OpenADR specification is a flexible infrastructure to facilitate common information exchange between the utility or Independent System Operator and end-use participants. The concept of an open specification is intended to allow anyone to implement the signaling systems, the automation server or the automation clients.

  18. Demand Response Programs for Oregon

    E-Print Network [OSTI]

    wholesale prices and looming shortages in Western power markets in 2000-01, Portland General Electric programs for large customers remain, though they are not active at current wholesale prices. Other programs demand response for the wholesale market -- by passing through real-time prices for usage above a set

  19. Water demand management in Kuwait

    E-Print Network [OSTI]

    Milutinovic, Milan, M. Eng. Massachusetts Institute of Technology

    2006-01-01T23:59:59.000Z

    Kuwait is an arid country located in the Middle East, with limited access to water resources. Yet water demand per capita is much higher than in other countries in the world, estimated to be around 450 L/capita/day. There ...

  20. WA-RD 470.1 June 1999 Demand Forecasting for Rural Transit

    E-Print Network [OSTI]

    WA-RD 470.1 June 1999 Demand Forecasting for Rural Transit This summary describes the key findings of a WSDOT project that is documented more fully in the technical report titled "Demand Forecasting for Rural to Washington for predicting demand for rural public transportation. Three Washington-based models were

  1. Abstract --Due to the potentially large number of Distributed Energy Resources (DERs) demand response, distributed

    E-Print Network [OSTI]

    Zhang, Wei

    to accurately estimate the transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies, where dynamics on time scales of seconds to minutes demand response. The aggregated model efficiently includes statistical information of the population

  2. Smart Grid RFI: Addressing Policy and Logistical Challenges

    Broader source: Energy.gov (indexed) [DOE]

    efficiency of grid operations and more optimal deployment of generation resources. Demand response activities may be able to improve grid efficiency as well. On the consumer...

  3. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    Report 2009. Open Automated Demand Response Communicationsand Techniques for Demand Response. California Energyand S. Kiliccote. Estimating Demand Response Load Impacts:

  4. Opportunities, Barriers and Actions for Industrial Demand Response in California

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

    and Techniques for Demand Response, report for theand Reliability Demand Response Programs: Final Report.Demand Response

  5. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    E-Print Network [OSTI]

    Thompson, Lisa

    2008-01-01T23:59:59.000Z

    Interoperable Automated Demand Response Infrastructure,study of automated demand response in wastewater treatmentopportunities for demand response control strategies in

  6. INTEGRATION OF PV IN DEMAND RESPONSE

    E-Print Network [OSTI]

    Perez, Richard R.

    INTEGRATION OF PV IN DEMAND RESPONSE PROGRAMS Prepared by Richard Perez et al. NREL subcontract response programs. This is because PV generation acts as a catalyst to demand response, markedly enhancing by solid evidence from three utility case studies. BACKGROUND Demand Response: demand response (DR

  7. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

  8. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

  9. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work Sheridan provided the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid

  10. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy for demand response program impacts and contributed to the residential forecast. Mitch Tian prepared

  11. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

  12. Assessment of Demand Response and Advanced Metering

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    #12;#12;2008 Assessment of Demand Response and Advanced Metering Staff Report Federal Energy metering penetration and potential peak load reduction from demand response have increased since 2006. Significant activity to promote demand response or to remove barriers to demand response occurred at the state

  13. 1SMARTER Supply Chain Connections Third Party Logistics

    E-Print Network [OSTI]

    Minnesota, University of

    to the price of oil · Ocean container time vs. inland transportation ­ weeks vs. days · Inventory carrying ­ Inventory cost reduction of 6 percent ­ Average fixed logistics cost reduction of 23 percent "The 18th ­ moving product manufacturing back from Asia ­ Analysis is done to determine landed costs and inventory

  14. Logistics in a Low Carbon World Dr Maja I. Piecyk

    E-Print Network [OSTI]

    Painter, Kevin

    with automated manual transmission 2% Set vehicle speed limiters at lower speeds 0.4% Reduce engine idling 3 Government #12;Potential CO2 Reduction and Costs in Different Sectors (idealised) Logistics Agriculture Other utilities Primary production & manufacturing Private services Power generation Public services cost c A c

  15. MIT Center for Transportation & Logistics Distinguished Speakers Series

    E-Print Network [OSTI]

    Entekhabi, Dara

    MIT Center for Transportation & Logistics Distinguished Speakers Series Richard A. Davey MBTA;Transportation Reform ­ Moving Forward Transportation Reform Governance & Oversight · MBTA Board reconfigured mirroring the MassDOT's Five (5) member Board. · MBTA remains a separate legal entity from MassDOT. · MBTA

  16. Freight/logistics symposium ..2 Airport guidebook...................3

    E-Print Network [OSTI]

    Minnesota, University of

    · Freight/logistics symposium ..2 · Airport guidebook...................3 · State Fair exhibit Administration in Boston, is charged with improving the nation's transpor- tation system through collaborations between the USDOT and other federal, state, local, and international agencies and entities. "This

  17. Biomass Logistics and Particle Technology Group Purdue Improved Drying

    E-Print Network [OSTI]

    Ginzel, Matthew

    to maintain quality of grain in storage. n Farmers primarily depended on open air solar drying after logistics Grain & pest management Pre-Harvest losses from: Insect, molds and birds Harvesting & handling of PICS, technology Open Air Solar Drying of Maize in Ejura Market, Ashanti Region, Ghana #12;4 Chronology

  18. Defense waste transportation: cost and logistics studies

    SciTech Connect (OSTI)

    Andrews, W.B.; Cole, B.M.; Engel, R.L.; Oylear, J.M.

    1982-08-01T23:59:59.000Z

    Transportation of nuclear wastes from defense programs is expected to significantly increase in the 1980s and 1990s as permanent waste disposal facilities come into operation. This report uses models of the defense waste transportation system to quantify potential transportation requirements for treated and untreated contact-handled transuranic (CH-TRU) wastes and high-level defense wastes (HLDW). Alternative waste management strategies in repository siting, waste retrieval and treatment, treatment facility siting, waste packaging and transportation system configurations were examined to determine their effect on transportation cost and hardware requirements. All cost estimates used 1980 costs. No adjustments were made for future changes in these costs relative to inflation. All costs are reported in 1980 dollars. If a single repository is used for defense wastes, transportation costs for CH-TRU waste currently in surface storage and similar wastes expected to be generated by the year 2000 were estimated to be 109 million dollars. Recovery and transport of the larger buried volumes of CH-TRU waste will increase CH-TRU waste transportation costs by a factor of 70. Emphasis of truck transportation and siting of multiple repositories would reduce CH-TRU transportation costs. Transportation of HLDW to repositories for 25 years beginning in 1997 is estimated to cost $229 M in 1980 costs and dollars. HLDW transportation costs could either increase or decrease with the selection of a final canister configuration. HLDW transportation costs are reduced when multiple repositories exist and emphasis is placed on truck transport.

  19. The importance of food demand management for climate mitigation

    E-Print Network [OSTI]

    Bajželj, Bojana; Richards, Keith S.; Allwood, Julian M.; Smith, Pete; Dennis, John S.; Curmi, Elizabeth; Gilligan, Christopher A.

    2014-08-31T23:59:59.000Z

    and fertiliser, and the inclusion of climate change as a driver of yield changes and irrigation demand. This would enable estimation of how shortfalls in irrigation water availability might affect future food production. Bioenergy scenarios also lie outside... the scope of the current paper; unless food demand patterns change significantly, there seems to be little spare land for bioenergy developments without a reduction of food availability. However, it is important to note that the model results we present...

  20. The alchemy of demand response: turning demand into supply

    SciTech Connect (OSTI)

    Rochlin, Cliff

    2009-11-15T23:59:59.000Z

    Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

  1. LOGISTIC FUNCTION PROFILE FIT: A least-squares program for fitting interface profiles to an extended logistic function

    SciTech Connect (OSTI)

    Kirchhoff, William H. [Surface and Microanalysis Science Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8370, Gaithersburg, Maryland 20899-8370 (United States)

    2012-09-15T23:59:59.000Z

    The extended logistic function provides a physically reasonable description of interfaces such as depth profiles or line scans of surface topological or compositional features. It describes these interfaces with the minimum number of parameters, namely, position, width, and asymmetry. Logistic Function Profile Fit (LFPF) is a robust, least-squares fitting program in which the nonlinear extended logistic function is linearized by a Taylor series expansion (equivalent to a Newton-Raphson approach) with no apparent introduction of bias in the analysis. The program provides reliable confidence limits for the parameters when systematic errors are minimal and provides a display of the residuals from the fit for the detection of systematic errors. The program will aid researchers in applying ASTM E1636-10, 'Standard practice for analytically describing sputter-depth-profile and linescan-profile data by an extended logistic function,' and may also prove useful in applying ISO 18516: 2006, 'Surface chemical analysis-Auger electron spectroscopy and x-ray photoelectron spectroscopy-determination of lateral resolution.' Examples are given of LFPF fits to a secondary ion mass spectrometry depth profile, an Auger surface line scan, and synthetic data generated to exhibit known systematic errors for examining the significance of such errors to the extrapolation of partial profiles.

  2. Global energy demand to 2060

    SciTech Connect (OSTI)

    Starr, C. (Electric Power Research Institute, Palo Alto, CA (USA))

    1989-01-01T23:59:59.000Z

    The projection of global energy demand to the year 2060 is of particular interest because of its relevance to the current greenhouse concerns. The long-term growth of global energy demand in the time scale of climatic change has received relatively little attention in the public discussion of national policy alternatives. The sociological, political, and economic issues have rarely been mentioned in this context. This study emphasizes that the two major driving forces are global population growth and economic growth (gross national product per capita), as would be expected. The modest annual increases assumed in this study result in a year 2060 annual energy use of >4 times the total global current use (year 1986) if present trends continue, and >2 times with extreme efficiency improvements in energy use. Even assuming a zero per capita growth for energy and economics, the population increase by the year 2060 results in a 1.5 times increase in total annual energy use.

  3. Near Optimal Demand-Side Energy Management Under Real-time Demand-Response Pricing

    E-Print Network [OSTI]

    Boutaba, Raouf

    Near Optimal Demand-Side Energy Management Under Real-time Demand-Response Pricing Jin Xiao, Jae--In this paper, we present demand-side energy manage- ment under real-time demand-response pricing as a task, demand-response, energy management I. INTRODUCTION The growing awareness of global climate change has

  4. Final Progress Report, Renewable and Logistics Fuels for Fuel Cells at the Colorado School of Mines

    SciTech Connect (OSTI)

    Sullivan, Neal P

    2012-08-06T23:59:59.000Z

    The objective of this program is to advance the current state of technology of solid-oxide fuel cells (SOFCs) to improve performance when operating on renewable and logistics hydrocarbon fuel streams. Outcomes will include: 1.) new SOFC materials and architectures that address the technical challenges associated with carbon-deposit formation and sulfur poisoning; 2.) new integration strategies for combining fuel reformers with SOFCs; 3.) advanced modeling tools that bridge the scales of fundamental charge-transfer chemistry to system operation and control; and 4.) outreach through creation of the Distinguished Lecturer Series to promote nationwide collaboration with fuel-cell researchers and scientists.

  5. Power system balancing with high renewable penetration : the potential of demand response .

    E-Print Network [OSTI]

    Critz, David Karl

    2012-01-01T23:59:59.000Z

    ??This study investigated the ability of responsive demand to stabilize the electrical grid when intermittent renewable resources are present. The WILMAR stochastic unit commitment model… (more)

  6. On-Demand Based Wireless Resources Trading for Green Communications

    E-Print Network [OSTI]

    Cheng, Wenchi; Zhang, Hailin; Wang, Qiang

    2011-01-01T23:59:59.000Z

    The purpose of Green Communications is to reduce the energy consumption of the communication system as much as possible without compromising the quality of service (QoS) for users. An effective approach for Green Wireless Communications is On-Demand strategy, which scales power consumption with the volume and location of user demand. Applying the On-Demand Communications model, we propose a novel scheme -- Wireless Resource Trading, which characterizes the trading relationship among different wireless resources for a given number of performance metrics. According to wireless resource trading relationship, different wireless resources can be consumed for the same set of performance metrics. Therefore, to minimize the energy consumption for given performance metrics, we can trade the other type of wireless resources for the energy resource under the demanded performance metrics. Based on the wireless resource trading relationship, we derive the optimal energy-bandwidth and energy-time wireless resource trading ...

  7. Covering models with time-dependent demand

    E-Print Network [OSTI]

    2007-10-22T23:59:59.000Z

    The different solutions in the search space are given in terms of the variables yk .... symbolize the new facilities to enter the market, and the dark-grey circles ...

  8. q-deformed logistic map with delay feedback

    E-Print Network [OSTI]

    Manish Dev Shrimali; Subhashish Banerjee

    2012-03-14T23:59:59.000Z

    The delay logistic map with two types of q-deformations: Tsallis and Quantum-group type are studied. The stability of the map and its bifurcation scheme is analyzed as a function of the deformation and delay feedback parameters. Chaos is suppressed in a certain region of deformation and feedback parameter space. The steady state obtained by delay feedback is maintained in one type of deformation while chaotic behavior is recovered in another type with increasing delay.

  9. Microsoft Word - NNSA Logistics A-76 Post - MEO VV Review Report...

    Broader source: Energy.gov (indexed) [DOE]

    Microsoft Word - NNSA Logistics A-76 Post - MEO VV Review Report 111.doc Microsoft Word - NNSA Logistics A-76 Post - MEO VV Review Report 111.doc Microsoft Word - NNSA...

  10. Generalized multi-commodity network flows : case studies in space logistics and complex infrastructure systems

    E-Print Network [OSTI]

    Ishimatsu, Takuto

    2013-01-01T23:59:59.000Z

    In transition to a new era of human space exploration, the question is what the next-generation space logistics paradigm should be. The past studies on space logistics have been mainly focused on a "vehicle" perspective ...

  11. file://P:\\Smart Grid\\Smart Grid RFI Policy and Logistical Comme

    Broader source: Energy.gov (indexed) [DOE]

    Docket: DOE-HQ-2010-0024 Policy and Logistical Challenges to Smart Grid Implementation Comment On: DOE-HQ-2010-0024-0001 Policy and Logistical Challenges to Smart Grid...

  12. GridWise Alliance: Smart Grid RFI: Addressing Policy and Logistical...

    Broader source: Energy.gov (indexed) [DOE]

    GridWise Alliance: Smart Grid RFI: Addressing Policy and Logistical Challenges GridWise Alliance: Smart Grid RFI: Addressing Policy and Logistical Challenges The GridWise Alliance...

  13. RedSeal Comments on "Smart Grid RFI: Addressing Policy and Logistical...

    Broader source: Energy.gov (indexed) [DOE]

    RedSeal Comments on "Smart Grid RFI: Addressing Policy and Logistical Challenges. RedSeal Comments on "Smart Grid RFI: Addressing Policy and Logistical Challenges. RedSeal Comments...

  14. How regional authorities can achieve economic development through investments in the logistics sector

    E-Print Network [OSTI]

    Khan, Taimur, 1973-

    2004-01-01T23:59:59.000Z

    Lessons for how a regional authority should develop its logistics sector are learned through case studies on four areas (section 2). In addition, a "logistics attractiveness" ranking framework is developed and applied ...

  15. Fuse Control for Demand Side Management: A Stochastic Pricing Analysis

    E-Print Network [OSTI]

    Oren, Shmuel S.

    a service contract for load curtailment. Index Terms--Demand side management, aggregated demand response

  16. Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    in Demand Response for Wholesale Ancillary Services Silain Demand Response for Wholesale Ancillary Services Silasuccessfully in the wholesale non- spinning ancillary

  17. Industrial Equipment Demand and Duty Factors

    E-Print Network [OSTI]

    Dooley, E. S.; Heffington, W. M.

    Demand and duty factors have been measured for selected equipment (air compressors, electric furnaces, injection molding machines, centrifugal loads, and others) in industrial plants. Demand factors for heavily loaded air compressors were near 100...

  18. Marketing & Driving Demand Collaborative - Social Media Tools...

    Energy Savers [EERE]

    drivingdemandsocialmedia010611.pdf More Documents & Publications Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 Social Media for Natural...

  19. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    temperature-based demand response in buildings that havedemand response advantages of global zone temperature setup in buildings

  20. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    demand-side management (DSM) framework presented in Table x provides three major areas for changing electric loads in buildings:

  1. Response to changes in demand/supply

    E-Print Network [OSTI]

    Response to changes in demand/supply through improved marketing 21.2 #12;#12;111 Impacts of changes log demand in 1995. The composites board mills operating in Korea took advantage of flexibility environment changes on the production mix, some economic indications, statistics of demand and supply of wood

  2. Response to changes in demand/supply

    E-Print Network [OSTI]

    Response to changes in demand/supply through improved marketing 21.2 http with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board, statistics of demand and supply of wood, costs and competitiveness were analysed. The reactions

  3. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the peak demand forecast. Ravinderpal Vaid provided the projections of commercial floor space

  4. FINAL STAFF FORECAST OF 2008 PEAK DEMAND

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

  5. THE STATE OF DEMAND RESPONSE IN CALIFORNIA

    E-Print Network [OSTI]

    THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response (DR) can.S. and internationally and lay out ideas that could help move California forward. KEY WORDS demand response, peak

  6. THE STATE OF DEMAND RESPONSE IN CALIFORNIA

    E-Print Network [OSTI]

    THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response can help reduce the threat of planned rotational outages. Demand response is also widely regarded as having

  7. Demand Response Resources in Pacific Northwest

    E-Print Network [OSTI]

    Demand Response Resources in Pacific Northwest Chuck Goldman Lawrence Berkeley National Laboratory cagoldman@lbl.gov Pacific Northwest Demand Response Project Portland OR May 2, 2007 #12;Overview · Typology Annual Reports ­ Journal articles/Technical reports #12;Demand Response Resources · Incentive

  8. Barrier Immune Radio Communications for Demand Response

    E-Print Network [OSTI]

    LBNL-2294E Barrier Immune Radio Communications for Demand Response F. Rubinstein, G. Ghatikar, J Ann Piette of Lawrence Berkeley National Laboratory's (LBNL) Demand Response Research Center (DRRC and Environment's (CIEE) Demand Response Emerging Technologies Development (DRETD) Program, under Work for Others

  9. Demand Response and Ancillary Services September 2008

    E-Print Network [OSTI]

    Demand Response and Ancillary Services September 2008 #12;© 2008 EnerNOC, Inc. All Rights Reserved programs The purpose of this presentation is to offer insight into the mechanics of demand response and industrial demand response resources across North America in both regulated and restructured markets As of 6

  10. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    LBNL-62226 Demand Responsive Lighting: A Scoping Study F. Rubinstein, S. Kiliccote Energy Environmental Technologies Division January 2007 #12;LBNL-62226 Demand Responsive Lighting: A Scoping Study in this report was coordinated by the Demand Response Research Center and funded by the California Energy

  11. Transportation Energy: Supply, Demand and the Future

    E-Print Network [OSTI]

    Saldin, Dilano

    Transportation Energy: Supply, Demand and the Future http://www.uwm.edu/Dept/CUTS//2050/energy05 as a source of energy. Global supply and demand trends will have a profound impact on the ability to use our) Transportation energy demand in the U.S. has increased because of the greater use of less fuel efficient vehicles

  12. Demand Side Bidding. Final Report

    SciTech Connect (OSTI)

    Spahn, Andrew

    2003-12-31T23:59:59.000Z

    This document sets forth the final report for a financial assistance award for the National Association of Regulatory Utility Commissioners (NARUC) to enhance coordination between the building operators and power system operators in terms of demand-side responses to Location Based Marginal Pricing (LBMP). Potential benefits of this project include improved power system reliability, enhanced environmental quality, mitigation of high locational prices within congested areas, and the reduction of market barriers for demand-side market participants. NARUC, led by its Committee on Energy Resources and the Environment (ERE), actively works to promote the development and use of energy efficiency and clean distributive energy policies within the framework of a dynamic regulatory environment. Electric industry restructuring, energy shortages in California, and energy market transformation intensifies the need for reliable information and strategies regarding electric reliability policy and practice. NARUC promotes clean distributive generation and increased energy efficiency in the context of the energy sector restructuring process. NARUC, through ERE's Subcommittee on Energy Efficiency, strives to improve energy efficiency by creating working markets. Market transformation seeks opportunities where small amounts of investment can create sustainable markets for more efficient products, services, and design practices.

  13. Demand Response Valuation Frameworks Paper

    SciTech Connect (OSTI)

    Heffner, Grayson

    2009-02-01T23:59:59.000Z

    While there is general agreement that demand response (DR) is a valued component in a utility resource plan, there is a lack of consensus regarding how to value DR. Establishing the value of DR is a prerequisite to determining how much and what types of DR should be implemented, to which customers DR should be targeted, and a key determinant that drives the development of economically viable DR consumer technology. Most approaches for quantifying the value of DR focus on changes in utility system revenue requirements based on resource plans with and without DR. This ''utility centric'' approach does not assign any value to DR impacts that lower energy and capacity prices, improve reliability, lower system and network operating costs, produce better air quality, and provide improved customer choice and control. Proper valuation of these benefits requires a different basis for monetization. The review concludes that no single methodology today adequately captures the wide range of benefits and value potentially attributed to DR. To provide a more comprehensive valuation approach, current methods such as the Standard Practice Method (SPM) will most likely have to be supplemented with one or more alternative benefit-valuation approaches. This report provides an updated perspective on the DR valuation framework. It includes an introduction and four chapters that address the key elements of demand response valuation, a comprehensive literature review, and specific research recommendations.

  14. The Environmental Impacts of Logistics Systems and Options for Mitigation Nakul Sathaye, Yuwei Li, Arpad Horvath and Samer Madanat

    E-Print Network [OSTI]

    California at Berkeley, University of

    . Transportation Sustainability and Green Logistics ................................................3 1 .....................................................................................3 1.2. Considering Green Logistics with Industry Perspectives...................................................................................................................44 #12;2 Table of Tables Table 1 ­ Paradoxes of Green Logistics

  15. Autimated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR

    E-Print Network [OSTI]

    Kim, J. J.; Yin, R.; Kiliccote, S.

    2013-01-01T23:59:59.000Z

    Open Automated Demand Response (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demand response participation for large commercial buildings in New York who are subject...

  16. Energy demand and population changes

    SciTech Connect (OSTI)

    Allen, E.L.; Edmonds, J.A.

    1980-12-01T23:59:59.000Z

    Since World War II, US energy demand has grown more rapidly than population, so that per capita consumption of energy was about 60% higher in 1978 than in 1947. Population growth and the expansion of per capita real incomes have led to a greater use of energy. The aging of the US population is expected to increase per capita energy consumption, despite the increase in the proportion of persons over 65, who consume less energy than employed persons. The sharp decline in the population under 18 has led to an expansion in the relative proportion of population in the prime-labor-force age groups. Employed persons are heavy users of energy. The growth of the work force and GNP is largely attributable to the growing participation of females. Another important consequence of female employment is the growth in ownership of personal automobiles. A third factor pushing up labor-force growth is the steady influx of illegal aliens.

  17. Demand Forecast and Performance Prediction in Peer-Assisted On-Demand Streaming Systems

    E-Print Network [OSTI]

    Li, Baochun

    Demand Forecast and Performance Prediction in Peer-Assisted On-Demand Streaming Systems Di Niu on the Internet. Automated demand forecast and performance prediction, if implemented, can help with capacity an accurate user demand forecast. In this paper, we analyze the operational traces collected from UUSee Inc

  18. Risk Management for Video-on-Demand Servers leveraging Demand Forecast

    E-Print Network [OSTI]

    Li, Baochun

    Risk Management for Video-on-Demand Servers leveraging Demand Forecast Di Niu, Hong Xu, Baochun Li on demand history using time se- ries forecasting techniques. The prediction enables dynamic and efficient}@eecg.toronto.edu Shuqiao Zhao Multimedia Development Group UUSee, Inc. shuqiao.zhao@gmail.com ABSTRACT Video-on-demand (Vo

  19. Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes

    E-Print Network [OSTI]

    Sastry, S. Shankar

    Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes. Developing novel schemes for demand response in smart electric gird is an increasingly active research area/SCADA for demand response in smart infrastructures face the following dilemma: On one hand, in order to increase

  20. US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

    E-Print Network [OSTI]

    that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controllingUS Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Massimo www.cepe.ethz.ch #12;US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

  1. COAL LOGISTICS. Tracking U.S. Coal Exports

    SciTech Connect (OSTI)

    Sall, G.W. [US Department of Energy, Office of Fossil Energy, Washington, DC (United States)

    1988-06-28T23:59:59.000Z

    COAL LOGISTICS has the capability to track coal from a U. S. mine or mining area to a foreign consumer`s receiving dock. The system contains substantial quantities of information about the types of coal available in different U. S. coalfields, present and potential inland transportation routes to tidewater piers, and shipping routes to and port capabilities in Italy, Japan, South Korea, Taiwan, and Thailand. It is designed to facilitate comparisons of coal quality and price at several stages of the export process, including delivered prices at a wide range of destinations. COAL LOGISTICS can be used to examine coal quality within or between any of 18 U. S. coalfields, including three in Alaska, or to compare alternative routes and associated service prices between coal-producing regions and ports-of-exit. It may be used to explore the possibilities of different ship sizes, marine routes, and foreign receiving terminals for coal exports. The system contains three types of information: records of coal quality, domestic coal transportation options, and descriptions of marine shipment routes. COAL LOGISTICS contains over 3100 proximate analyses of U. S. steam coals, usually supplemented by data for ash softening temperature and Hardgrove grindability; over 1100 proximate analyses for coals with metallurgical potential, usually including free swelling index values; 87 domestic coal transportation options: rail, barge, truck, and multi-mode routes that connect 18 coal regions with 15 U. S. ports and two Canadian terminals; and data on 22 Italian receiving ports for thermal and metallurgical coal and 24 coal receiving ports along the Asian Pacific Rim. An auxiliary program, CLINDEX, is included which is used to index the database files.

  2. Control and Optimization Meet the Smart Power Grid - Scheduling of Power Demands for Optimal Energy Management

    E-Print Network [OSTI]

    Koutsopoulos, Iordanis

    2010-01-01T23:59:59.000Z

    The smart power grid aims at harnessing information and communication technologies to enhance reliability and enforce sensible use of energy. Its realization is geared by the fundamental goal of effective management of demand load. In this work, we envision a scenario with real-time communication between the operator and consumers. The grid operator controller receives requests for power demands from consumers, with different power requirement, duration, and a deadline by which it is to be completed. The objective is to devise a power demand task scheduling policy that minimizes the grid operational cost over a time horizon. The operational cost is a convex function of instantaneous power consumption and reflects the fact that each additional unit of power needed to serve demands is more expensive as demand load increases.First, we study the off-line demand scheduling problem, where parameters are fixed and known. Next, we devise a stochastic model for the case when demands are generated continually and sched...

  3. Logistics & Fees - Combustion Energy Frontier Research Center

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickrinformationPostdocsCenterCentera A B C D E FLoggingLogistics

  4. Chapter 3 Airline Economics, Markets & Demand Learning Objectives

    E-Print Network [OSTI]

    of traffic o Yield o Capacity/ Available Seat Miles (ASM) o Unit Cost o Load Factor = Passengers/ Capacity Average Leg Load Factor Average Network Load Factor o Rejected Demand/Spill · Basic Airline Profit / Frequency Share Model "S-curve" #12;The student will be able to perform the following analysis (i

  5. Exhausting Battery Statistics Understanding the energy demands on mobile handsets

    E-Print Network [OSTI]

    Cambridge, University of

    energy models and resources managers designed for laptops [20] and data cen- ters [4] inapplicableExhausting Battery Statistics Understanding the energy demands on mobile handsets Narseo Vallina.surname@telekom.de ABSTRACT Despite the advances in battery technologies, mobile phones still suffer from severe energy

  6. Rates and technologies for mass-market demand response

    E-Print Network [OSTI]

    Herter, Karen; Levy, Roger; Wilson, John; Rosenfeld, Arthur

    2002-01-01T23:59:59.000Z

    Roger. 2002. Using Demand Response to Link Wholesale andfor advanced metering, demand response, and dynamic pricing.EPRI. 2001. Managing Demand-Response To Achieve Multiple

  7. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    Goodin. 2009. “Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services. ” InOpen Automated Demand Response Demonstration Project. LBNL-

  8. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

    Robinson, Michael, 2008, "Demand Response in Midwest ISOPresentation at MISO Demand Response Working Group Meeting,Coordination of Retail Demand Response with Midwest ISO

  9. Results and commissioning issues from an automated demand response pilot

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, Dave; Sezgen, Osman; Motegi, Naoya

    2004-01-01T23:59:59.000Z

    of Fully Automated Demand Response in Large Facilities"Management and Demand Response in Commercial Buildings", L Band Commissioning Issues from an Automated Demand Response.

  10. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    E-Print Network [OSTI]

    Goli, Sasank

    2012-01-01T23:59:59.000Z

    and Open Automated Demand Response. In Grid Interop Forum.work was sponsored by the Demand Response Research Center (load-management.php. Demand Response Research Center (2009).

  11. Demand Response in U.S. Electricity Markets: Empirical Evidence

    E-Print Network [OSTI]

    Cappers, Peter

    2009-01-01T23:59:59.000Z

    Reliability Corporation. Demand response data task force:Energy. Benefits of demand response in electricity marketsAssessment of demand response & advanced metering, staff

  12. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    A. Barat, D. Watson. Demand Response Spinning ReserveOpen Automated Demand Response Communication Standards:Dynamic Controls for Demand Response in a New Commercial

  13. Direct versus Facility Centric Load Control for Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

    Interoperable Automated Demand Response Infrastructure.and Techniques for Demand Response. LBNL Report 59975. Mayand Communications for Demand Response and Energy Efficiency

  14. Open Automated Demand Response Communications Specification (Version 1.0)

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    and Techniques for Demand Response. May 2007. LBNL-59975.to facilitate automating  demand response actions at the Interoperable Automated Demand Response Infrastructure,

  15. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    of Fully Automated Demand  Response in Large Facilities.  Fully Automated Demand Response Tests in Large Facilities.  Open Automated  Demand Response Communication Standards: 

  16. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01T23:59:59.000Z

    C. McParland, Open Automated Demand Response Communicationsand Open Automated Demand Response", Grid Interop Forum,Testing of Automated Demand Response for Integration of

  17. Opportunities, Barriers and Actions for Industrial Demand Response in California

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

    13 Table 2. Demand Side Management Framework for IndustrialDR Strategies The demand-side management (DSM) frameworkpresented in Table 2. Demand Side Management Framework for

  18. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

  19. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    description of six energy and demand management concepts.how quickly it can modify energy demand. This is not a newimprovements in both energy efficiency and demand response (

  20. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    Institute, “Curbing Global Energy Demand Growth: The Energyup Assessment of Energy Demand in India Transportationa profound effect on energy demand. Policy analysts wishing

  1. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    Building Control Strategies and Techniques for Demand Response.Building Systems and DR Strategies 16 Demand ResponseDemand Response Systems. ” Proceedings, 16 th National Conference on Building

  2. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01T23:59:59.000Z

    in California. DEMAND RESPONSE AND COMMERCIAL BUILDINGSload and demand response against other buildings and alsoDemand Response and Energy Efficiency in Commercial Buildings",

  3. Open Automated Demand Response Communications Specification (Version 1.0)

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    Keywords: demand response, buildings, electricity use, Interface  Automated Demand Response  Building Automation of demand response in  commercial buildings.   One key 

  4. Results and commissioning issues from an automated demand response pilot

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, Dave; Sezgen, Osman; Motegi, Naoya

    2004-01-01T23:59:59.000Z

    Management and Demand Response in Commercial Buildings", L BAutomated Demand Response National Conference on BuildingAutomated Demand Response National Conference on Building

  5. Scenarios for Consuming Standardized Automated Demand Response Signals

    E-Print Network [OSTI]

    Koch, Ed

    2009-01-01T23:59:59.000Z

    Keywords: Demand response, automation, commercial buildings,Demand Response and Energy Efficiency in Commercial Buildings,Building Control Strategies and Techniques for Demand Response.

  6. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    Demand  Response for Small Commercial Buildings.   CEC?500?automated demand response  For small commercial buildings, AUTOMATED DEMAND RESPONSE FOR SMALL COMMERCIAL BUILDINGS

  7. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

    2006-01-01T23:59:59.000Z

    for Demand Response in New and Existing Commercial BuildingsDemand Response Strategies and National Conference on BuildingDemand Response Strategies and Commissioning Commercial Building

  8. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    for Automated Demand Response in Commercial Buildings. Inbased demand response information to building controlDemand Response Standard for the Residential Sector. California Energy Commission, PIER Buildings

  9. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    is manual demand response where building staff receive acommercial buildings’ demand response technologies andBuilding Control Strategies and Techniques for Demand Response.

  10. Direct versus Facility Centric Load Control for Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

    Keywords: Demand response, automation, commercial buildings,Demand Response and Energy Efficiency in Commercial Buildings,Building Control Strategies and Techniques for Demand Response.

  11. Fuel cell technology for prototype logistic fuel cell mobile systems

    SciTech Connect (OSTI)

    Sederquist, R.A.; Garow, J.

    1995-08-01T23:59:59.000Z

    Under the aegis of the Advanced Research Project Agency`s family of programs to develop advanced technology for dual use applications, International Fuel Cells Corporation (IFC) is conducting a 39 month program to develop an innovative system concept for DoD Mobile Electric Power (MEP) applications. The concept is to integrate two technologies, the phosphoric acid fuel cell (PAFC) with an auto-thermal reformer (ATR), into an efficient fuel cell power plant of nominally 100-kilowatt rating which operates on logistic fuels (JP-8). The ATR fuel processor is the key to meeting requirements for MEP (including weight, volume, reliability, maintainability, efficiency, and especially operation on logistic fuels); most of the effort is devoted to ATR development. An integrated demonstration test unit culminates the program and displays the benefits of the fuel cell system, relative to the standard 100-kilowatt MEP diesel engine generator set. A successful test provides the basis for proceeding toward deployment. This paper describes the results of the first twelve months of activity during which specific program aims have remained firm.

  12. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    battery voltage. NOTE: This device does not control the thermoelectric air conditioner on the plastic model house.

  13. Distributed Demand Response and User Adaptation in Smart Grids

    E-Print Network [OSTI]

    Fan, Zhong

    2010-01-01T23:59:59.000Z

    This paper proposes a distributed framework for demand response and user adaptation in smart grid networks. In particular, we borrow the concept of congestion pricing in Internet traffic control and show that pricing information is very useful to regulate user demand and hence balance network load. User preference is modeled as a willingness to pay parameter which can be seen as an indicator of differential quality of service. Both analysis and simulation results are presented to demonstrate the dynamics and convergence behavior of the algorithm.

  14. Climate Mitigation Policy Implications for Global Irrigation Water Demand

    SciTech Connect (OSTI)

    Chaturvedi, Vaibhav; Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Wise, Marshall A.

    2013-08-22T23:59:59.000Z

    Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of alternative land-use emissions mitigation policy options—one which values terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to lead to increased demand for water for agricultural systems (+200%), even in the absence of climate change. In general policies to mitigate climate change will increase agricultural demands for water, regardless of whether or not terrestrial carbon is valued or not. Burgeoning demands for water are driven by the demand for bioenergy in response to emissions mitigation policies. We also find that the policy matters. Increases in the demand for water when terrestrial carbon emissions go un-prices are vastly larger than when terrestrial system carbon emissions are prices at the same rate as fossil fuel and industrial emissions. Our estimates for increased water demands when terrestrial carbon systems go un-priced are larger than earlier studies. We find that the deployment of improved irrigation delivery systems could mitigate some of the increase in water demands, but cannot reverse the increases in water demands when terrestrial carbon emissions go un-priced. Finally we estimates that the geospatial pattern of water demands could stress some parts of the world, e.g. China, India and other countries in south and east Asia, earlier and more intensely than in other parts of the world, e.g. North America.

  15. Industrial Demand-Side Management in Texas

    E-Print Network [OSTI]

    Jaussaud, D.

    of programs result in lower consumption and/or lower peak demand, and ultimately reduce the need to build new capacity. Hence demand-side management can be used as a resource option to be considered alongside more traditional supply-side resources in a...INDUSTRIAL DEMAND-SIDE MANAGEMENT IN TEXAS Danielle Jaussaud Economic Analysis Section Public Utility Commission of Texas Austin, Texas ABSTRACT The industrial sector in Texas is highly energy intensive and represents a large share...

  16. Price-elastic demand in deregulated electricity markets

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.

    2003-05-01T23:59:59.000Z

    The degree to which any deregulated market functions efficiently often depends on the ability of market agents to respond quickly to fluctuating conditions. Many restructured electricity markets, however, experience high prices caused by supply shortages and little demand-side response. We examine the implications for market operations when a risk-averse retailer's end-use consumers are allowed to perceive real-time variations in the electricity spot price. Using a market-equilibrium model, we find that price elasticity both increases the retailers revenue risk exposure and decreases the spot price. Since the latter induces the retailer to reduce forward electricity purchases, while the former has the opposite effect, the overall impact of price responsive demand on the relative magnitudes of its risk exposure and end-user price elasticity. Nevertheless, price elasticity decreases cumulative electricity consumption. By extending the analysis to allow for early settlement of demand, we find that forward stage end-user price responsiveness decreases the electricity forward price relative to the case with price-elastic demand only in real time. Moreover, we find that only if forward stage end-user demand is price elastic will the equilibrium electricity forward price be reduced.

  17. Deep Demand Response: The Case Study of the CITRIS Building at the University of California-Berkeley

    E-Print Network [OSTI]

    Culler, David E.

    Deep Demand Response: The Case Study of the CITRIS Building at the University of California quality. We have made progress towards achieving deep demand response of 30% reduction of peak loads modeling expertise), and UC Berkeley (related demand response research including distributed wireless

  18. Maximum-Demand Rectangular Location Problem

    E-Print Network [OSTI]

    Manish Bansal

    2014-10-01T23:59:59.000Z

    Oct 1, 2014 ... Demand and service can be defined in the most general sense. ... Industrial and Systems Engineering, Texas A&M University, September 2014.

  19. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01T23:59:59.000Z

    in the presence of renewable resources and on the amount ofprimarily from renewable resources, and to a limited extentintegration of renewable resources and deferrable demand. We

  20. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    3 3.0 Previous Experience with Demand Responsive Lighting11 4.3. Prevalence of Lighting13 4.4. Impact of Title 24 on Lighting

  1. Wastewater plant takes plunge into demand response

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Commission and the Bonneville Power Administration, the Eugene-Springfield Water Pollution Control Facility in Eugene, Ore., was put through a series of demand response tests....

  2. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    peak demand management. Photo sensors for daylight drivenare done by local photo-sensors and control hardwaresensing device in a photo sensor is typically a photodiode,

  3. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    Response Controls for HVAC Systems Clifford Federspiel,tests. Figure 5: Specific HVAC electric power consumptioncontrol, demand response, HVAC, wireless Executive Summary

  4. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

    Commission (FERC) 2008a. “Wholesale Competition in RegionsDemand Response into Wholesale Electricity Markets,” (URL:1 2. Wholesale and Retails Electricity Markets in

  5. Demand Response - Policy | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    prices or when grid reliability is jeopardized. In regions with centrally organized wholesale electricity markets, demand response can help stabilize volatile electricity prices...

  6. Robust newsvendor problem with autoregressive demand

    E-Print Network [OSTI]

    2014-05-19T23:59:59.000Z

    May 19, 2014 ... bust distribution-free autoregressive forecasting method, which copes .... (Bandi and Bertsimas, 2012) to estimate the demand forecast. As.

  7. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    2013-06-19T23:59:59.000Z

    Jun 19, 2013 ... efficient linear programming formulation for the demand response of such a consumer who could be a price taker, industrial or commercial user ...

  8. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    water heaters with embedded demand responsive controls can be designed to automatically provide day-ahead and real-time response

  9. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    in peak demand. This definition of energy efficiency makesthe following definitions are used: Energy efficiency refersThis definition implicitly distinguishes energy efficiency

  10. Geographically Based Hydrogen Demand and Infrastructure Rollout...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Rollout Scenario Analysis Geographically Based Hydrogen Demand and Infrastructure Rollout Scenario Analysis Presentation by Margo Melendez at the 2010-2025 Scenario Analysis for...

  11. Geographically Based Hydrogen Demand and Infrastructure Analysis...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Analysis Geographically Based Hydrogen Demand and Infrastructure Analysis Presentation by NREL's Margo Melendez at the 2010 - 2025 Scenario Analysis for Hydrogen Fuel Cell Vehicles...

  12. Estimation and specification tests of count data recreation demand functions

    E-Print Network [OSTI]

    Gomez, Irma Adriana

    1991-01-01T23:59:59.000Z

    addressed this issue by employing various estimators which are based on a count distribution. Although researchers have recognized the need to model recreation demand as stemming from a count data generating process, there is little guidance in selecting... a stochastic model for this type of data, Previous research in this area has so far engaged only in heuristic comparisons of various count data estimators. Hence, as in standard regression analysis, it is desirable to test whether the fitted count...

  13. Assessing Vehicle Electricity Demand Impacts on California Electricity Supply

    E-Print Network [OSTI]

    McCarthy, Ryan W.

    2009-01-01T23:59:59.000Z

    fuel electricity demands, and generation from these plantplants .. 47 Additional generation .. 48 Electricityelectricity demand increases generation from NGCC power plants.

  14. Strategies for Aligning Program Demand with Contractor's Seasonal...

    Energy Savers [EERE]

    Aligning Program Demand with Contractor's Seasonal Fluctuations Strategies for Aligning Program Demand with Contractor's Seasonal Fluctuations Better Buildings Neighborhood Program...

  15. Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.

    SciTech Connect (OSTI)

    Starke, Michael R [ORNL; Kirby, Brendan J [ORNL; Kueck, John D [ORNL; Todd, Duane [Alcoa; Caulfield, Michael [Alcoa; Helms, Brian [Alcoa

    2009-02-01T23:59:59.000Z

    Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.

  16. Port-city relationships in Europe and Asia Published in: Journal of International Logistics and Trade 4(2), pp. 13-35

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Port-city relationships in Europe and Asia Published in: Journal of International Logistics-712 Republic of Korea Abstract This paper investigates the nature of port-city relationships in two major port studies or general models, it proposes a complementary approach based on urban and port indicators

  17. Value of Demand Response -Introduction Klaus Skytte

    E-Print Network [OSTI]

    Pool Spot Time of use tariffs Load management Consumers active at the spot market Fast decrease in demand to prices. Similar to Least-cost planning and demand-side management. DR differs by using prices side. Investors want more stable prices ­ less fluctuations. Higher short-term security of supply

  18. DEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT

    E-Print Network [OSTI]

    Bierlaire, Michel

    of the response of travelers to real-time pre- trip information. The demand simulator is an extension of dynamicDEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT Constantinos Antoniou, Moshe Ben-Akiva, Michel Bierlaire, and Rabi Mishalani Massachusetts Institute of Technology, Cambridge, MA 02139 Abstract

  19. Demand Response and Electric Grid Reliability

    E-Print Network [OSTI]

    Wattles, P.

    2012-01-01T23:59:59.000Z

    Demand Response and Electric Grid Reliability Paul Wattles Senior Analyst, Market Design & Development, ERCOT CATEE Conference, Galveston October 10, 2012 2 North American Bulk Power Grids CATEE Conference October 10, 2012 ? The ERCOT... adequacy ? ?Achieving more DR participation would . . . displace some generation investments, but would achieve the same level of reliability... ? ?Achieving this ideal requires widespread demand response and market structures that enable loads...

  20. A Vision of Demand Response - 2016

    SciTech Connect (OSTI)

    Levy, Roger

    2006-10-15T23:59:59.000Z

    Envision a journey about 10 years into a future where demand response is actually integrated into the policies, standards, and operating practices of electric utilities. Here's a bottom-up view of how demand response actually works, as seen through the eyes of typical customers, system operators, utilities, and regulators. (author)

  1. SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK DRAFTSTAFFREPORT May ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION B. B assessment of the capability of the physical electricity system to provide power to meet electricity demand

  2. Demand for NGL as olefin plant feedstock

    SciTech Connect (OSTI)

    Dodds, A.R. [Quantum Chemical Corp., Houston, TX (United States)

    1997-12-31T23:59:59.000Z

    Olefin plant demand for natural gas liquids as feedstock constitutes a key market for the NGL industry. Feedstock flexibility and the price sensitive nature of petrochemical demand are described. Future trends are presented. The formation and objectives of the Petrochemical Feedstock Association of the Americas are discussed.

  3. Demand Response Programs Oregon Public Utility Commission

    E-Print Network [OSTI]

    , Demand Side Management #12;Current Programs/Tariffs ­ Load Control Programs Cool Keeper, Utah (currentlyDemand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director 33 MW, building to 90 MW) Irrigation load control, Idaho (35 MW summer, 2004) Lighting load control

  4. Analysis of the Oklahoma City Air Logistics Centers's (ALC) contract management processes .

    E-Print Network [OSTI]

    Burton, Bennet A.

    2007-01-01T23:59:59.000Z

    ??This paper assesses the process capabilities and competencies of Air Force Material Command's (AFMC) Air Logistics Center (ALC) at Tinker AFB, OK. The assessment uses… (more)

  5. Analysis of Transportation and Logistics Challenges Affecting the Deployment of Larger Wind Turbines: Summary of Results

    SciTech Connect (OSTI)

    Cotrell, J.; Stehly, T.; Johnson, J.; Roberts, J. O.; Parker, Z.; Scott, G.; Heimiller, D.

    2014-01-01T23:59:59.000Z

    There is relatively little literature that characterizes transportation and logistics challenges and the associated effects on U.S. wind markets. The objectives of this study were to identify the transportation and logistics challenges, assess the associated impacts, and provide recommendations for strategies and specific actions to address the challenges. The authors primarily relied on interviews with wind industry project developers, original equipment manufacturers, and transportation and logistics companies to obtain the information and industry perspectives needed for this study. They also reviewed published literature on trends and developments in increasing wind turbine size, logistics, and transportation issues.

  6. E-Print Network 3.0 - automated ammunition logistics Sample Search...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Mars and beyond... . I. Introduction ne of the major logistical challenges in human space exploration is asset management Source: de Weck, Olivier L. - Department of Aeronautics...

  7. Uranium 2009 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2010-01-01T23:59:59.000Z

    With several countries currently building nuclear power plants and planning the construction of more to meet long-term increases in electricity demand, uranium resources, production and demand remain topics of notable interest. In response to the projected growth in demand for uranium and declining inventories, the uranium industry – the first critical link in the fuel supply chain for nuclear reactors – is boosting production and developing plans for further increases in the near future. Strong market conditions will, however, be necessary to trigger the investments required to meet projected demand. The "Red Book", jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency, is a recognised world reference on uranium. It is based on information compiled in 40 countries, including those that are major producers and consumers of uranium. This 23rd edition provides a comprehensive review of world uranium supply and demand as of 1 January 2009, as well as data on global ur...

  8. Towards a systematic characterization of the potential of demand side management

    E-Print Network [OSTI]

    Kleinhans, David

    2014-01-01T23:59:59.000Z

    With an increasing share of electric energy produced from non-dispatchable renewable sources both energy storage and demand side management might gain tremendously in importance. While there has been significant progress in general properties and technologies of energy storage, the systematic characterization of features particular to demand side management such as its intermittent, time-dependent potential seems to be lagging behind. As a consequence, the development of efficient and sustainable strategies for demand side management and its integration into large-scale energy system models are impeded. This work introduces a novel framework for a systematic time-resolved characterization of the potential for demand side management. It is based on the specification of individual devices both with respect to their scheduled demand and their potential of load shifting. On larger scales sector-specific profiles can straightforwardly be taken into account. The potential for demand side management is then specifie...

  9. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

    2010-01-29T23:59:59.000Z

    This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

  10. Strategies for Demand Response in Commercial Buildings

    SciTech Connect (OSTI)

    Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

    2006-06-20T23:59:59.000Z

    This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

  11. Revised Economic andRevised Economic and Demand ForecastsDemand Forecasts

    E-Print Network [OSTI]

    Revised Economic andRevised Economic and Demand ForecastsDemand Forecasts April 14, 2009 Massoud,000 MW #12;6 Demand Forecasts Price Effect (prior to conservation) - 5,000 10,000 15,000 20,000 25,000 30 Jourabchi #12;2 Changes since the Last Draft ForecastChanges since the Last Draft Forecast Improved

  12. An Econometrics Analysis of Freight Rail Demand Growth in Albert Wijeweera a, *

    E-Print Network [OSTI]

    1 An Econometrics Analysis of Freight Rail Demand Growth in Australia Albert Wijeweera a, * , Hong of non-bulk freight demand in Australia. The paper uses a simple but robust econometrics method this growth at about four per cent per year (BTRE, 2006). The econometric model used herein enables us

  13. The Impact of Technological Change and Lifestyles on the Energy Demand

    E-Print Network [OSTI]

    Steininger, Karl W.

    demand into a model of total private consumption. Private consumption is determined by economic variables of technological and socio- demographic variables on the demand for gasoline/diesel, heating and electricity. Key, households' electricity and heat consumption are growing rapidly despite of technological progress

  14. Managing water demand as a regulated open MAS. (Work in progress)

    E-Print Network [OSTI]

    Garrido, Antonio

    1 Managing water demand as a regulated open MAS. (Work in progress) Vicente Botti1 , Antonio Scientific Research Council, {vbotti,agarridot,agiret}@dsic.upv.es, pablo@iiia.csic.es I. WATER MANAGEMENT management models are based on equa- tional descriptions of aggregate supply and demand in a water basin [2

  15. Managing water demand as a regulated open MAS. (Work in progress)

    E-Print Network [OSTI]

    Garrido, Antonio

    1 Managing water demand as a regulated open MAS. (Work in progress) Vicente Botti 1 , Antonio Scientific Research Council, {vbotti,agarridot,agiret}@dsic.upv.es, pablo@iiia.csic.es I. WATER MANAGEMENT management models are based on equa­ tional descriptions of aggregate supply and demand in a water basin [2

  16. Large-Scale Integration of Deferrable Demand and Renewable Energy Sources

    E-Print Network [OSTI]

    Oren, Shmuel S.

    1 Large-Scale Integration of Deferrable Demand and Renewable Energy Sources Anthony Papavasiliou. In order to accurately assess the impacts of renewable energy integration and demand response integration model for assessing the impacts of the large-scale integration of renewable energy sources

  17. Demand Response This is the first of the Council's power plans to treat demand response as a resource.1

    E-Print Network [OSTI]

    Demand Response This is the first of the Council's power plans to treat demand response the resource and describes some of the potential advantages and problems of the development of demand response. WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding

  18. FERC sees huge potential for demand response

    SciTech Connect (OSTI)

    NONE

    2010-04-15T23:59:59.000Z

    The FERC study concludes that U.S. peak demand can be reduced by as much as 188 GW -- roughly 20 percent -- under the most aggressive scenario. More moderate -- and realistic -- scenarios produce smaller but still significant reductions in peak demand. The FERC report is quick to point out that these are estimates of the potential, not projections of what could actually be achieved. The main varieties of demand response programs include interruptible tariffs, direct load control (DLC), and a number of pricing schemes.

  19. Demand Response Resources for Energy and Ancillary Services (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01T23:59:59.000Z

    Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

  20. The Coal Logistics System: Documentation and user's guide

    SciTech Connect (OSTI)

    Not Available

    1988-10-01T23:59:59.000Z

    The Coal Logistics System (CLS) has the capability to track coal from a US mine or mining area to a foreign consumer's receiving dock. The system contains substantial quantities of information about the types of coal available in different US coalfields, present and potential inland transportation routes to tidewater piers, and shipping routes to and port capabilities in the five importing nations now included. It is designed to facilitate comparisons of coal quality and price at several stages of the export process, including delivered prices at a wide range of destinations from Trieste to Vado Ligure in Italy, and from Muroran in northern Japan, to Sri Racha, near Bangkok, along the Asian Pacific Rim. The CLS can also be used to examine coal quality within or between any of 18 US coalfields, including three in Alaska, or compare alternative routes and associated service prices between coal producing regions and ports-of-exit. It may be used to explore the possibilities of different ship sizes, marine routes, and foreign receiving terminals for coal exports. The CLS interacts with users through a series of menus that provide the user with simple choices. 30 figs.

  1. Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

    SciTech Connect (OSTI)

    Yin, Rongxin; Kiliccote, Sila; Piette, Mary Ann; Parrish, Kristen

    2010-05-14T23:59:59.000Z

    This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30percent using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

  2. Volatile coal prices reflect supply, demand uncertainties

    SciTech Connect (OSTI)

    Ryan, M.

    2004-12-15T23:59:59.000Z

    Coal mine owners and investors say that supply and demand are now finally in balance. But coal consumers find that both spot tonnage and new contract coal come at a much higher price.

  3. Micro economics for demand-side management

    E-Print Network [OSTI]

    Kibune, Hisao

    1991-01-01T23:59:59.000Z

    This paper aims to interpret Demand-Side Management (DSM) activity and to point out its problems, adopting microeconomics as an analytical tool. Two major findings follow. first, the cost-benefit analysis currently in use ...

  4. Capitalize on Existing Assets with Demand Response

    E-Print Network [OSTI]

    Collins, J.

    2008-01-01T23:59:59.000Z

    Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assets—at no cost and no risk. Demand response, the voluntary...

  5. Global Energy: Supply, Demand, Consequences, Opportunities

    ScienceCinema (OSTI)

    Arun Majumdar

    2010-01-08T23:59:59.000Z

    July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

  6. A residential energy demand system for Spain

    E-Print Network [OSTI]

    Labandeira Villot, Xavier

    2005-01-01T23:59:59.000Z

    Sharp price fluctuations and increasing environmental and distributional concerns, among other issues, have led to a renewed academic interest in energy demand. In this paper we estimate, for the first time in Spain, an ...

  7. Measuring the capacity impacts of demand response

    SciTech Connect (OSTI)

    Earle, Robert; Kahn, Edward P.; Macan, Edo

    2009-07-15T23:59:59.000Z

    Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demand response can help address the decreasing returns to scale in capacity value, but more flexible demand response has decreasing returns to scale as well. (author)

  8. The Economics of Energy (and Electricity) Demand

    E-Print Network [OSTI]

    Platchkov, Laura M.; Pollitt, Michael G.

    home to charge up at night. 12 The Tesla Roadster is an electric sport car prototype manufactured by Tesla Motors (http://www.teslamotors.com/). 13 This is based on there being around 25 million homes... 25 3.3.2 Electrification of personal transport New sources of electricity demand may emerge which substantially change the total demand for electricity and the way electricity is consumed by the household. The Tesla Roadster12 stores 53 k...

  9. Real-Time Demand Side Energy Management

    E-Print Network [OSTI]

    Victor, A.; Brodkorb, M.

    2006-01-01T23:59:59.000Z

    Real-Time Demand Side Energy Management Annelize Victor Michael Brodkorb Sr. Business Consultant Business Development Manager Aspen Technology, Inc. Aspen Technology España, S.A. Houston, TX Barcelona, Spain ABSTRACT To remain... competitive, manufacturers must capture opportunities to increase bottom-line profitability. The goal of this paper is to present a new methodology for reducing energy costs – “Demand-Side Energy Management.” Learn how process manufacturers assess energy...

  10. Seasonal demand and supply analysis of turkeys

    E-Print Network [OSTI]

    Blomo, Vito James

    1972-01-01T23:59:59.000Z

    SEASONAL DEMAND AND SUPPLY ANALYSIS OF TURKEYS A Thesis by VITO JAMES BLOMO Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1972 Ma)or Sub...)ect: Agricultural Economics SEASONAL DEMAND AND SUPPLY ANALYSIS OF TURKEYS A Thesis by VITO JAMES BLOMO Approved as to style and content by: (Chairman of C mmittee) (Head of Department) (Member) (Member) ( ber) (Memb er) May 1972 ABSTRACT Seasonal...

  11. U.S. Regional Demand Forecasts Using NEMS and GIS

    SciTech Connect (OSTI)

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01T23:59:59.000Z

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

  12. Electricity Demand Evolution Driven by Storm Motivated Population Movement

    SciTech Connect (OSTI)

    Allen, Melissa R [ORNL; Fernandez, Steven J [ORNL; Fu, Joshua S [ORNL; Walker, Kimberly A [ORNL

    2014-01-01T23:59:59.000Z

    Managing the risks posed by climate change to energy production and delivery is a challenge for communities worldwide. Sea Level rise and increased frequency and intensity of natural disasters due to sea surface temperature rise force populations to move locations, resulting in changing patterns of demand for infrastructure services. Thus, Infrastructures will evolve to accommodate new load centers while some parts of the network are underused, and these changes will create emerging vulnerabilities. Combining climate predictions and agent based population movement models shows promise for exploring the universe of these future population distributions and changes in coastal infrastructure configurations. In this work, we created a prototype agent based population distribution model and developed a methodology to establish utility functions that provide insight about new infrastructure vulnerabilities that might result from these patterns. Combining climate and weather data, engineering algorithms and social theory, we use the new Department of Energy (DOE) Connected Infrastructure Dynamics Models (CIDM) to examine electricity demand response to increased temperatures, population relocation in response to extreme cyclonic events, consequent net population changes and new regional patterns in electricity demand. This work suggests that the importance of established evacuation routes that move large populations repeatedly through convergence points as an indicator may be under recognized.

  13. Power system balancing with high renewable penetration : the potential of demand response

    E-Print Network [OSTI]

    Critz, David Karl

    2012-01-01T23:59:59.000Z

    This study investigated the ability of responsive demand to stabilize the electrical grid when intermittent renewable resources are present. The WILMAR stochastic unit commitment model was used to represent a version of ...

  14. Regional Differences in Corn Ethanol Production: Profitability and Potential Water Demands

    E-Print Network [OSTI]

    Higgins, Lindsey M.

    2010-07-14T23:59:59.000Z

    Through the use of a stochastic simulation model this project analyzes both the impacts of the expanding biofuels sector on water demand in selected regions of the United States and variations in the profitability of ethanol production due...

  15. The process of resort second home development demand quantification : exploration of methodologies and case study application

    E-Print Network [OSTI]

    Wholey, Christopher J. (Christoper John)

    2011-01-01T23:59:59.000Z

    Prevalent methodologies utilized by resort second home development professionals to quantify demand for future projects are identified and critiqued. The strengths of each model are synthesized in order to formulate an ...

  16. Stochastic dynamic optimization of consumption and the induced price elasticity of demand in smart grids

    E-Print Network [OSTI]

    Faghih, Ali

    2011-01-01T23:59:59.000Z

    This thesis presents a mathematical model of consumer behavior in response to stochastically-varying electricity prices, and a characterization of price-elasticity of demand created by optimal utilization of storage and ...

  17. New Demand for Old Food: the U.S. Demand for Olive Oil

    E-Print Network [OSTI]

    Bo Xiong; William Matthews; Daniel Sumner

    U.S. consumption of olive oil has tripled over the past twenty years, but nearly all olive oil continues to be imported. Estimation of demand parameters using monthly import data reveals that demand for non-virgin oil is income inelastic, but virgin oils have income elasticities above one. Moreover, demand for oils differentiated by origin and quality is price-elastic. These olive oils are highly substitutable with each other but not with other vegetable oils. News about the health and culinary benefits of olive oil and the spread of Mediterranean diet contribute significantly to the rising demand in the United States.

  18. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

    2006-01-01T23:59:59.000Z

    4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

  19. Demand-Side Management and Energy Efficiency Revisited

    E-Print Network [OSTI]

    Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

    2007-01-01T23:59:59.000Z

    EPRI). 1984. ”Demand Side Management. Vol. 1:Overview of Key1993. ”Industrial Demand-Side Management Programs: What’sJ. Kulick. 2004. ”Demand side management and energy e?ciency

  20. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

    Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the4. Status of Demand Side Management in Midwest ISO 5.

  1. CALIFORNIA ENERGY CALIFORNIA ENERGY DEMAND 2010-2020

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2010-2020 ADOPTED FORECAST for this report: Kavalec, Chris and Tom Gorin, 2009. California Energy Demand 20102020, Adopted Forecast. California Energy Commission. CEC2002009012CMF #12; i Acknowledgments The demand forecast

  2. Coordinating production quantities and demand forecasts through penalty schemes

    E-Print Network [OSTI]

    Swaminathan, Jayashankar M.

    Coordinating production quantities and demand forecasts through penalty schemes MURUVVET CELIKBAS1 departments which enable organizations to match demand forecasts with production quantities. This research problem where demand is uncertain and the marketing de- partment provides a forecast to manufacturing

  3. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    Parsons, Simon

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc in demand forecasting for new communication services. Acknowledgments: The writing of this paper commenced employers or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica- tions

  4. Analysis of Open Automated Demand Response Deployments in California

    E-Print Network [OSTI]

    LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

  5. PIER: Demand Response Research Center Director, Mary Ann Piette

    E-Print Network [OSTI]

    1 PIER: Demand Response Research Center Director, Mary Ann Piette Program Development and Outreach Response Research Plan #12;2 Demand Response Research Center Objective Scope Stakeholders Develop, prioritize, conduct and disseminate multi- institutional research to facilitate Demand Response. Technologies

  6. Commercial Fleet Demand for Alternative-Fuel Vehicles in California

    E-Print Network [OSTI]

    Golob, Thomas F; Torous, Jane; Bradley, Mark; Brownstone, David; Crane, Soheila Soltani; Bunch, David S

    1996-01-01T23:59:59.000Z

    Precursors of demand for alternative-fuel vehicles: resultsFLEET DEMAND FOR ALTERNATIVE-FUEL VEHICLES IN CALIFORNIA*Abstract—Fleet demand for alternative-fuel vehicles (‘AFVs’

  7. California Baseline Energy Demands to 2050 for Advanced Energy Pathways

    E-Print Network [OSTI]

    McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

    2008-01-01T23:59:59.000Z

    ED2, September. CEC (2005b) Energy demand forecast methodsCalifornia Baseline Energy Demands to 2050 for Advancedof a baseline scenario for energy demand in California for a

  8. Demand Control Utilizing Energy Management Systems - Report of Field Tests

    E-Print Network [OSTI]

    Russell, B. D.; Heller, R. P.; Perry, L. W.

    1984-01-01T23:59:59.000Z

    Energy Management systems and particularly demand controllers are becoming more popular as commercial and light industrial operations attempt to reduce their electrical usage and demand. Numerous techniques are used to control energy use and demand...

  9. Behavioral Aspects in Simulating the Future US Building Energy Demand

    E-Print Network [OSTI]

    Stadler, Michael

    2011-01-01T23:59:59.000Z

    Importance Total off- site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decrease

  10. Learning Energy Demand Domain Knowledge via Feature Transformation

    E-Print Network [OSTI]

    Povinelli, Richard J.

    Learning Energy Demand Domain Knowledge via Feature Transformation Sanzad Siddique Department -- Domain knowledge is an essential factor for forecasting energy demand. This paper introduces a method knowledge substantially improves energy demand forecasting accuracy. However, domain knowledge may differ

  11. Energy Demands and Efficiency Strategies in Data Center Buildings

    E-Print Network [OSTI]

    Shehabi, Arman

    2010-01-01T23:59:59.000Z

    iv Chapter 5: National energy demand and potential energyEnergy Demands and Efficiency Strategies   in Data Center AC02?05CH11231.   Energy Demands and Efficiency Strategies

  12. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    for Demand Response in a New Commercial Building in NewDemand Response and Energy Efficiency in Commercial Buildings.Demand Response Mary Ann Piette, Sila Kiliccote, and Girish Ghatikar Lawrence Berkeley National Laboratory Building

  13. Smart Buildings Using Demand Response March 6, 2011

    E-Print Network [OSTI]

    Kammen, Daniel M.

    Smart Buildings Using Demand Response March 6, 2011 Sila Kiliccote Deputy, Demand Response Research Center Program Manager, Building Technologies Department Environmental Energy Technologies only as needed) · Energy Efficiency strategies are permanent (occur daily) 4 #12;Demand-Side

  14. Feedstock Logistics of a Mobile Pyrolysis System and Assessment of Soil Loss Due to Biomass Removal for Bioenergy Production

    E-Print Network [OSTI]

    Bumguardner, Marisa

    2012-10-19T23:59:59.000Z

    The purpose of this study was to assess feedstock logistics for a mobile pyrolysis system and to quantify the amount of soil loss caused by harvesting agricultural feedstocks for bioenergy production. The analysis of feedstock logistics...

  15. Residential Electricity Demand in China -- Can Efficiency Reverse the Growth?

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.; Zhou, Nan

    2009-05-18T23:59:59.000Z

    The time when energy-related carbon emissions come overwhelmingly from developed countries is coming to a close. China has already overtaken the United States as the world's leading emitter of greenhouse gas emissions. The economic growth that China has experienced is not expected to slow down significantly in the long term, which implies continued massive growth in energy demand. This paper draws on the extensive expertise from the China Energy Group at LBNL on forecasting energy consumption in China, but adds to it by exploring the dynamics of demand growth for electricity in the residential sector -- and the realistic potential for coping with it through efficiency. This paper forecasts ownership growth of each product using econometric modeling, in combination with historical trends in China. The products considered (refrigerators, air conditioners, fans, washing machines, lighting, standby power, space heaters, and water heating) account for 90percent of household electricity consumption in China. Using this method, we determine the trend and dynamics of demandgrowth and its dependence on macroeconomic drivers at a level of detail not accessible by models of a more aggregate nature. In addition, we present scenarios for reducing residential consumption through efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, thus allowing for a technologically realistic assessment of efficiency opportunities specifically in the Chinese context.

  16. Response to several FOIA requests - Renewable Energy. Demand...

    Office of Environmental Management (EM)

    Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA...

  17. The business value of demand response for balance responsible parties.

    E-Print Network [OSTI]

    Jonsson, Mattias

    2014-01-01T23:59:59.000Z

    ?? By using IT-solutions, the flexibility on the demand side in the electrical systems could be increased. This is called demand response and is part… (more)

  18. Implementation Proposal for the National Action Plan on Demand...

    Broader source: Energy.gov (indexed) [DOE]

    and the Department of Energy. Implementation Proposal for the National Action Plan on Demand Response - July 2011 More Documents & Publications National Action Plan on Demand...

  19. FERC Presendation: Demand Response as Power System Resources...

    Broader source: Energy.gov (indexed) [DOE]

    Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 Demand Response as...

  20. ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES

    E-Print Network [OSTI]

    Gross, George

    ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES BY ANUPAMA SUNIL KOWLI B of consumers - called demand response resources (DRRs) - whose role has become increasingly important

  1. Tool Improves Electricity Demand Predictions to Make More Room...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Tool Improves Electricity Demand Predictions to Make More Room for Renewables Tool Improves Electricity Demand Predictions to Make More Room for Renewables October 3, 2011 -...

  2. Energy Upgrade California Drives Demand From Behind the Wheel...

    Energy Savers [EERE]

    Upgrade California Drives Demand From Behind the Wheel Energy Upgrade California Drives Demand From Behind the Wheel Photo of a trailer with the Energy Upgrade California logo and...

  3. Reducing Energy Demand in Buildings Through State Energy Codes...

    Energy Savers [EERE]

    Reducing Energy Demand in Buildings Through State Energy Codes Reducing Energy Demand in Buildings Through State Energy Codes Building Codes Project for the 2013 Building...

  4. BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES

    E-Print Network [OSTI]

    LBL-33887 UC-000 BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES Jonathan G. Koomey ............................................................................................... 2 Demand-Side Efficiency Technologies I. Energy Management Systems (EMSs

  5. assessing workforce demand: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    and Utilization Websites Summary: LBNL-5319E Assessing the Control Systems Capacity for Demand Response in California Industries in this report was coordinated by the Demand...

  6. China's Coal: Demand, Constraints, and Externalities

    SciTech Connect (OSTI)

    Aden, Nathaniel; Fridley, David; Zheng, Nina

    2009-07-01T23:59:59.000Z

    This study analyzes China's coal industry by focusing on four related areas. First, data are reviewed to identify the major drivers of historical and future coal demand. Second, resource constraints and transport bottlenecks are analyzed to evaluate demand and growth scenarios. The third area assesses the physical requirements of substituting coal demand growth with other primary energy forms. Finally, the study examines the carbon- and environmental implications of China's past and future coal consumption. There are three sections that address these areas by identifying particular characteristics of China's coal industry, quantifying factors driving demand, and analyzing supply scenarios: (1) reviews the range of Chinese and international estimates of remaining coal reserves and resources as well as key characteristics of China's coal industry including historical production, resource requirements, and prices; (2) quantifies the largest drivers of coal usage to produce a bottom-up reference projection of 2025 coal demand; and (3) analyzes coal supply constraints, substitution options, and environmental externalities. Finally, the last section presents conclusions on the role of coal in China's ongoing energy and economic development. China has been, is, and will continue to be a coal-powered economy. In 2007 Chinese coal production contained more energy than total Middle Eastern oil production. The rapid growth of coal demand after 2001 created supply strains and bottlenecks that raise questions about sustainability. Urbanization, heavy industrial growth, and increasing per-capita income are the primary interrelated drivers of rising coal usage. In 2007, the power sector, iron and steel, and cement production accounted for 66% of coal consumption. Power generation is becoming more efficient, but even extensive roll-out of the highest efficiency units would save only 14% of projected 2025 coal demand for the power sector. A new wedge of future coal consumption is likely to come from the burgeoning coal-liquefaction and chemicals industries. If coal to chemicals capacity reaches 70 million tonnes and coal-to-liquids capacity reaches 60 million tonnes, coal feedstock requirements would add an additional 450 million tonnes by 2025. Even with more efficient growth among these drivers, China's annual coal demand is expected to reach 3.9 to 4.3 billion tonnes by 2025. Central government support for nuclear and renewable energy has not reversed China's growing dependence on coal for primary energy. Substitution is a matter of scale: offsetting one year of recent coal demand growth of 200 million tonnes would require 107 billion cubic meters of natural gas (compared to 2007 growth of 13 BCM), 48 GW of nuclear (compared to 2007 growth of 2 GW), or 86 GW of hydropower capacity (compared to 2007 growth of 16 GW). Ongoing dependence on coal reduces China's ability to mitigate carbon dioxide emissions growth. If coal demand remains on a high growth path, carbon dioxide emissions from coal combustion alone would exceed total US energy-related carbon emissions by 2010. Within China's coal-dominated energy system, domestic transportation has emerged as the largest bottleneck for coal industry growth and is likely to remain a constraint to further expansion. China has a low proportion of high-quality reserves, but is producing its best coal first. Declining quality will further strain production and transport capacity. Furthermore, transporting coal to users has overloaded the train system and dramatically increased truck use, raising transportation oil demand. Growing international imports have helped to offset domestic transport bottlenecks. In the long term, import demand is likely to exceed 200 million tonnes by 2025, significantly impacting regional markets.

  7. Utility Sector Impacts of Reduced Electricity Demand

    SciTech Connect (OSTI)

    Coughlin, Katie

    2014-12-01T23:59:59.000Z

    This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

  8. Uranium 2014 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2014-01-01T23:59:59.000Z

    Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. It presents the results of a thorough review of world uranium supplies and demand and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Long-term projections of nuclear generating capacity and reactor-related uranium requirements are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major changes in the industry.

  9. Uranium 2005 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2006-01-01T23:59:59.000Z

    Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. This 21st edition presents the results of a thorough review of world uranium supplies and demand as of 1st January 2005 and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Projections of nuclear generating capacity and reactor-related uranium requirements through 2025 are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major c...

  10. Patterns of crude demand: Future patterns of demand for crude oil as a func-

    E-Print Network [OSTI]

    Langendoen, Koen

    from the perspective of `peak oil', that is from the pers- pective of the supply of crude, and price#12;2 #12;Patterns of crude demand: Future patterns of demand for crude oil as a func- tion is given on the problems within the value chain, with an explanation of the reasons why the price of oil

  11. Ecotourism demand in North-East Italy.fig Ecotourism demand in North-East Italy

    E-Print Network [OSTI]

    Tempesta, Tiziano

    Ecotourism demand in North-East Italy.fig 1 Ecotourism demand in North-East Italy Tempesta T.1 and analyse ecotourism in North-East Italy. The main objectives were to: a) define a methodology that would quantify the recreational flow from the results of phone and in-person interviews, b) analyse ecotourism

  12. ERCOT's Weather Sensitive Demand Response Pilot

    E-Print Network [OSTI]

    Carter, T.

    2013-01-01T23:59:59.000Z

    ERCOT’s Weather Sensitive Demand Response Pilot CATEE 12-17-13 ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Disclaimer The information contained in this report has been obtained from... services along with other information about our business is available online at constellation.com. ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Demand Response in ERCOT CATEE 121313 - Tim Carter...

  13. Demand Response Initiatives at CPS Energy

    E-Print Network [OSTI]

    Luna, R.

    2013-01-01T23:59:59.000Z

    Demand Response Initiatives at CPS Energy Clean Air Through Energy Efficiency (CATEE) Conference December 17, 2013 ESL-KT-13-12-53 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 CPSE’s DR Program • DR... than the military bases and Toyota combined. • Schools & Universities contributed 6 MW’s of Demand Response in 2013. 2013 DR Participants Trinity University - $5,654 Fort Sam ISD - $18,860 Judson ISD - $45,540 Alamo Colleges - $98,222 UTSA - $168...

  14. Demand Responsive Lighting: A Scoping Study

    SciTech Connect (OSTI)

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-03T23:59:59.000Z

    The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

  15. Climate, extreme heat, and electricity demand in California

    SciTech Connect (OSTI)

    Miller, N.L.; Hayhoe, K.; Jin, J.; Auffhammer, M.

    2008-04-01T23:59:59.000Z

    Climate projections from three atmosphere-ocean climate models with a range of low to mid-high temperature sensitivity forced by the Intergovernmental Panel for Climate Change SRES higher, middle, and lower emission scenarios indicate that, over the 21st century, extreme heat events for major cities in heavily air-conditioned California will increase rapidly. These increases in temperature extremes are projected to exceed the rate of increase in mean temperature, along with increased variance. Extreme heat is defined here as the 90 percent exceedance probability (T90) of the local warmest summer days under the current climate. The number of extreme heat days in Los Angeles, where T90 is currently 95 F (32 C), may increase from 12 days to as many as 96 days per year by 2100, implying current-day heat wave conditions may last for the entire summer, with earlier onset. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-2099 tend to be 20-30 percent higher than those projected under the lower B1 emission scenario, ranging from approximately double the historical number of days for inland California cities (e.g. Sacramento and Fresno), up to four times for previously temperate coastal cities (e.g. Los Angeles, San Diego). These findings, combined with observed relationships between high temperature and electricity demand for air-conditioned regions, suggest potential shortfalls in transmission and supply during T90 peak electricity demand periods. When the projected extreme heat and peak demand for electricity are mapped onto current availability, maintaining technology and population constant only for demand side calculations, we find the potential for electricity deficits as high as 17 percent. Similar increases in extreme heat days are suggested for other locations across the U.S. southwest, as well as for developing nations with rapidly increasing electricity demands. Electricity response to recent extreme heat events, such as the July 2006 heat wave in California, suggests that peak electricity demand will challenge current supply, as well as future planned supply capacities when population and income growth are taken into account.

  16. Installation and Commissioning Automated Demand Response Systems

    SciTech Connect (OSTI)

    Global Energy Partners; Pacific Gas and Electric Company; Kiliccote, Sila; Kiliccote, Sila; Piette, Mary Ann; Wikler, Greg; Prijyanonda, Joe; Chiu, Albert

    2008-04-21T23:59:59.000Z

    Demand Response (DR) can be defined as actions taken to reduce electric loads when contingencies, such as emergencies and congestion, occur that threaten supply-demand balance, or market conditions raise supply costs. California utilities have offered price and reliability DR based programs to customers to help reduce electric peak demand. The lack of knowledge about the DR programs and how to develop and implement DR control strategies is a barrier to participation in DR programs, as is the lack of automation of DR systems. Most DR activities are manual and require people to first receive notifications, and then act on the information to execute DR strategies. Levels of automation in DR can be defined as follows. Manual Demand Response involves a labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. We refer to this as Auto-DR (Piette et. al. 2005). Auto-DR for commercial and industrial facilities can be defined as fully automated DR initiated by a signal from a utility or other appropriate entity and that provides fully-automated connectivity to customer end-use control strategies. One important concept in Auto-DR is that a homeowner or facility manager should be able to 'opt out' or 'override' a DR event if the event comes at time when the reduction in end-use services is not desirable. Therefore, Auto-DR is not handing over total control of the equipment or the facility to the utility but simply allowing the utility to pass on grid related information which then triggers facility defined and programmed strategies if convenient to the facility. From 2003 through 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) developed and tested a series of demand response automation communications technologies known as Automated Demand Response (Auto-DR). In 2007, LBNL worked with three investor-owned utilities to commercialize and implement Auto-DR programs in their territories. This paper summarizes the history of technology development for Auto-DR, and describes the DR technologies and control strategies utilized at many of the facilities. It outlines early experience in commercializing Auto-DR systems within PG&E DR programs, including the steps to configure the automation technology. The paper also describes the DR sheds derived using three different baseline methodologies. Emphasis is given to the lessons learned from installation and commissioning of Auto-DR systems, with a detailed description of the technical coordination roles and responsibilities, and costs.

  17. ESD.260J / 1.260J / 15.770J Logistics Systems, Fall 2003

    E-Print Network [OSTI]

    Caplice, Christopher George, 1961-

    See description under subject 1.260J. This course is a survey of analytic tools, approaches, and techniques which are useful in the design and operation of logistics systems and integrated supply chains. The material is ...

  18. The optimal reverse logistics network for consumer batteries in North America

    E-Print Network [OSTI]

    Rahman, Asgar

    2013-01-01T23:59:59.000Z

    The recycling of household consumer batteries is gaining legislative support throughout North America. The intent of this thesis document is to provide a broad overview of the current North American reverse logistics network ...

  19. Impact of modern logistics on industrial location choice and property markets

    E-Print Network [OSTI]

    Li, Yu, 1976-

    2007-01-01T23:59:59.000Z

    The debate on the impact of modern logistics on industrial location choice and property markets focuses on (1) whether modern inventory control and supply- chain configuration consolidate manufacturing and distribution ...

  20. The impact of out-of-theater supply flow visibility on in-theater logistics

    E-Print Network [OSTI]

    Giordano, Michael A. (Michael Anthony)

    2012-01-01T23:59:59.000Z

    The United States Army's end-to-end logistical network during times of conflict is made up of two separate networks. One network, managed by the Department of Defense, controls the shipment of supplies from the manufacturing ...