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Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

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

2

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network [OSTI]

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

Dudley, June Han

2009-01-01T23:59:59.000Z

3

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network [OSTI]

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

Ghatikar, Girish

2010-01-01T23:59:59.000Z

4

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

5

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

6

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network [OSTI]

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

Piette, Mary Ann

2009-01-01T23:59:59.000Z

7

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network [OSTI]

for Automated Demand Response in Commercial Buildings. ” In2010. “Open Automated Demand Response Dynamic Pricing2009. “Open Automated Demand Response Communications

Ghatikar, Girish

2010-01-01T23:59:59.000Z

8

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

E-Print Network [OSTI]

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

9

Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards  

E-Print Network [OSTI]

to  Automated  Demand   Response  and  the  OpenADR  ®  Automated  Demand  Response  Program.   https://Data  for  Automated  Demand  Response  in  Commercial  

Ghatikar, Girish

2014-01-01T23:59:59.000Z

10

Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR  

E-Print Network [OSTI]

2009. Open Automated Demand Response Communications2010. Open Automated Demand Response Technologies forenergy efficiency and demand response: Framework concepts

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

11

Open Automated Demand Response Communications Specification (Version 1.0)  

SciTech Connect (OSTI)

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.

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

2009-02-28T23:59:59.000Z

12

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network [OSTI]

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

Piette, Mary Ann

2009-01-01T23:59:59.000Z

13

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network [OSTI]

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

Piette, Mary Ann

2009-01-01T23:59:59.000Z

14

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network [OSTI]

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

Dudley, June Han

2009-01-01T23:59:59.000Z

15

Automated Demand Response Technologies and Demonstration in New York City using OpenADR  

E-Print Network [OSTI]

C. McParland, "Open Automated Demand Response Communications2011. Utility & Demand Response Programs Energy ProviderAnnual Consumption (kWh) Demand Response Program Curtailment

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

16

Open Automated Demand Response for Small Commerical Buildings  

SciTech Connect (OSTI)

This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

2009-05-01T23:59:59.000Z

17

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network [OSTI]

Linking Continuous Energy Management and Open AutomatedKeywords: Continuous Energy Management, Automated Demandlinking continuous energy management and continuous

Piette, Mary Ann

2009-01-01T23:59:59.000Z

18

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network [OSTI]

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

Ghatikar, Girish

2010-01-01T23:59:59.000Z

19

Demand Response and Open Automated Demand Response Opportunities for Data Centers  

E-Print Network [OSTI]

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

Mares, K.C.

2010-01-01T23:59:59.000Z

20

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network [OSTI]

January 2008. Biography Mary Ann Piette is a Staff ScientistAutomated Demand Response Mary Ann Piette, Sila Kiliccote,

Piette, Mary Ann

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response  

E-Print Network [OSTI]

Protocol for Building Automation and Control  Networks.  Protocol for Building Automation and Control  Networks, Demand Response Automation Server  Demand Response Research 

Kiliccote, Sila

2011-01-01T23:59:59.000Z

22

Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response  

SciTech Connect (OSTI)

This report summarizes San Diego Gas& Electric Company?s collaboration with the Demand Response Research Center to develop and test automation capability for the Capacity Bidding Program in 2007. The report describes the Open Automated Demand Response architecture, summarizes the history of technology development and pilot studies. It also outlines the Capacity Bidding Program and technology being used by an aggregator that participated in this demand response program. Due to delays, the program was not fully operational for summer 2007. However, a test event on October 3, 2007, showed that the project successfully achieved the objective to develop and demonstrate how an open, Web?based interoperable automated notification system for capacity bidding can be used by aggregators for demand response. The system was effective in initiating a fully automated demand response shed at the aggregated sites. This project also demonstrated how aggregators can integrate their demand response automation systems with San Diego Gas& Electric Company?s Demand Response Automation Server and capacity bidding program.

Kiliccote, Sila; Piette, Mary Ann

2008-10-01T23:59:59.000Z

23

Northwest Open Automated Demand Response Technology Demonstration Project  

SciTech Connect (OSTI)

The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique opportunity to create DR programs that address both BPA's and SCL's markets simultaneously. Although simultaneously addressing both market could significantly increase the value of DR programs for BPA, SCL, and the end user, establishing program parameters that maximize this value is challenging because of complex contractual arrangements and the absence of a central Independent System Operator or Regional Transmission Organization in the northwest.

Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao

2010-03-17T23:59:59.000Z

24

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

your Power. (2008). "Demand Response Programs." RetrievedUsing Open Automated Demand Response, Lawrence Berkeley2008). "What is Demand Response?" Retrieved 10/10/2008, from

Lekov, Alex

2010-01-01T23:59:59.000Z

25

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network [OSTI]

congress_1252d.pdf. EPRI. 2009. Automated DemandProject – Revision 1. EPRI. Palo Alto, California: 2009.DOE DR DRAS DRRC EIS EMCS EPRI FERC FM HASP ISO ISONE LBNL

Ghatikar, Girish

2010-01-01T23:59:59.000Z

26

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

SciTech Connect (OSTI)

The Pacific Gas and Electric Company (PG&E) is conducting a pilot program to investigate the technical feasibility of bidding certain demand response (DR) resources into the California Independent System Operator's (CAISO) day-ahead market for ancillary services nonspinning reserve. Three facilities, a retail store, a local government office building, and a bakery, are recruited into the pilot program. For each facility, hourly demand, and load curtailment potential are forecasted two days ahead and submitted to the CAISO the day before the operation as an available resource. These DR resources are optimized against all other generation resources in the CAISO ancillary service. Each facility is equipped with four-second real time telemetry equipment to ensure resource accountability and visibility to CAISO operators. When CAISO requests DR resources, PG&E's OpenADR (Open Automated DR) communications infrastructure is utilized to deliver DR signals to the facilities energy management and control systems (EMCS). The pre-programmed DR strategies are triggered without a human in the loop. This paper describes the automated system architecture and the flow of information to trigger and monitor the performance of the DR events. We outline the DR strategies at each of the participating facilities. At one site a real time electric measurement feedback loop is implemented to assure the delivery of CAISO dispatched demand reductions. Finally, we present results from each of the facilities and discuss findings.

Kiliccote, Sila; Piette, Mary Ann; Ghatikar, Girish; Koch, Ed; Hennage, Dan; Hernandez, John; Chiu, Albert; Sezgen, Osman; Goodin, John

2009-11-06T23:59:59.000Z

27

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network [OSTI]

for Automated Demand Response in Commercial Buildings. ” InAutomated Demand Response for Small Commercial Buildings. ”in automated demand response programs with building control

Ghatikar, Girish

2010-01-01T23:59:59.000Z

28

Demand Response and Open Automated Demand Response Opportunities for Data Centers  

SciTech Connect (OSTI)

This study examines data center characteristics, loads, control systems, and technologies to identify demand response (DR) and automated DR (Open Auto-DR) opportunities and challenges. The study was performed in collaboration with technology experts, industrial partners, and data center facility managers and existing research on commercial and industrial DR was collected and analyzed. The results suggest that data centers, with significant and rapidly growing energy use, have significant DR potential. Because data centers are highly automated, they are excellent candidates for Open Auto-DR. 'Non-mission-critical' data centers are the most likely candidates for early adoption of DR. Data center site infrastructure DR strategies have been well studied for other commercial buildings; however, DR strategies for information technology (IT) infrastructure have not been studied extensively. The largest opportunity for DR or load reduction in data centers is in the use of virtualization to reduce IT equipment energy use, which correspondingly reduces facility cooling loads. DR strategies could also be deployed for data center lighting, and heating, ventilation, and air conditioning. Additional studies and demonstrations are needed to quantify benefits to data centers of participating in DR and to address concerns about DR's possible impact on data center performance or quality of service and equipment life span.

Ghatikar, Girish; Piette, Mary Ann; Fujita, Sydny; McKane, Aimee; Dudley, Junqiao Han; Radspieler, Anthony; Mares, K.C.; Shroyer, Dave

2009-12-30T23:59:59.000Z

29

Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards  

E-Print Network [OSTI]

Automated  Demand  Response  in  Commercial  Buildings.  Demand  Response  Infrastructure  for   Commercial  Buildings.  

Ghatikar, Girish

2014-01-01T23:59:59.000Z

30

Design and Implementation of an Open, Interoperable Automated Demand Response Infrastructure  

E-Print Network [OSTI]

of Fully Automated Demand Response in Large Facilities. CEC-Fully Automated Demand Response Tests in Large Facilities.Management and Demand Response in Commercial Building. ,

Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

2008-01-01T23:59:59.000Z

31

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network [OSTI]

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 (

Piette, Mary Ann

2009-01-01T23:59:59.000Z

32

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

33

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

34

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network [OSTI]

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

Piette, Mary Ann

2009-01-01T23:59:59.000Z

35

SmartHG: Energy Demand Aware Open Services for Smart Grid Intelligent Automation  

E-Print Network [OSTI]

solar panels)], for each time slot (say each hour) the DNO price policy defines an interval of energySmartHG: Energy Demand Aware Open Services for Smart Grid Intelligent Automation Enrico Tronci.prodanovic,jorn.gruber, barry.hayes}@imdea.org I. INTRODUCTION The SmartHG project [1], [2] has the goal of developing

Tronci, Enrico

36

Architecture Concepts and Technical Issues for an Open, Interoperable Automated Demand Response Infrastructure  

E-Print Network [OSTI]

energy efficiency and demand response in large facilities.was sponsored by the Demand Response Research Center whichInteroperable Automated Demand Response Infrastructure Ed

Koch, Ed; Piette, Mary Ann

2008-01-01T23:59:59.000Z

37

Design and Implementation of an Open, Interoperable Automated Demand Response Infrastructure  

E-Print Network [OSTI]

is manual demand response -- where building staff receives aand Demand Response in Commercial Building. ,April, LBNL-Keywords: Demand response, automation, commercial buildings,

Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

2008-01-01T23:59:59.000Z

38

Architecture Concepts and Technical Issues for an Open, Interoperable Automated Demand Response Infrastructure  

E-Print Network [OSTI]

is manual demand response -- where building staff receives aKeywords: Demand response, automation, commercial buildings,buildings, especially as it applies to Demand Response

Koch, Ed; Piette, Mary Ann

2008-01-01T23:59:59.000Z

39

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

SciTech Connect (OSTI)

We present an Open Automated Demand Response Communications Specifications (OpenADR) data model capable of communicating real-time prices to electricity customers. We also show how the same data model could be used to for other types of dynamic pricing tariffs (including peak pricing tariffs, which are common throughout the United States). Customers participating in automated demand response programs with building control systems can respond to dynamic prices by using the actual prices as inputs to their control systems. Alternatively, prices can be mapped into"building operation modes," which can act as inputs to control systems. We present several different strategies customers could use to map prices to operation modes. Our results show that OpenADR can be used to communicate dynamic pricing within the Smart Grid and that OpenADR allows for interoperability with existing and future systems, technologies, and electricity markets.

Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Kiliccote, Sila

2010-06-02T23:59:59.000Z

40

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network [OSTI]

in Demand Response for Wholesale Ancillary Services. ” Incan be used to link wholesale and retail real-time prices.11 Wholesale Electricity Market Information

Ghatikar, Girish

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Design and Operation of an Open, Interoperable Automated Demand Response Infrastructure for Commercial Buildings  

SciTech Connect (OSTI)

This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automated demand response (auto-DR). Automating DR allows greater levels of participation, improved reliability, and repeatability of the DR in participating facilities. This paper also presents the technical and architectural issues associated with auto-DR and description of the demand response automation server (DRAS), the client/server architecture-based middle-ware used to automate the interactions between the utilities or any DR serving entity and their customers for DR programs. Use case diagrams are presented to show the role of the DRAS between utility/ISO and the clients at the facilities.

Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Watson, David; Koch, Ed; Hennage, Dan

2009-05-01T23:59:59.000Z

42

Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards  

SciTech Connect (OSTI)

This report reviews the Open Automated Demand Response (OpenADR) deployments within the territories serviced by California?s investor-owned utilities (IOUs) and the transition from the OpenADR 1.0 specification to the formal standard?OpenADR 2.0. As demand response service providers and customers start adopting OpenADR 2.0, it is necessary to ensure that the existing Automated Demand Response (AutoDR) infrastructure investment continues to be useful and takes advantage of the formal standard and its many benefits. This study focused on OpenADR deployments and systems used by the California IOUs and included a summary of the OpenADR deployment from the U.S. Department of Energy-funded demonstration conducted by the Sacramento Municipal Utility District (SMUD). Lawrence Berkeley National Laboratory collected and analyzed data about OpenADR 1.0 deployments, categorized architectures, developed a data model mapping to understand the technical compatibility of each version, and compared the capabilities and features of the two specifications. The findings, for the first time, provided evidence of the total enabled load shed and average first cost for system enablement in the IOU and SMUD service territories. The OpenADR 2.0a profile specification semantically supports AutoDR system architectures and data propagation with a testing and certification program that promotes interoperability, scaled deployments by multiple vendors, and provides additional features that support future services.

Ghatikar, Girish; Riess, David; Piette, Mary Ann

2014-01-02T23:59:59.000Z

43

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network [OSTI]

Reports X BIP X X X X X X X X PDC X X X X X X X X PCT X X XNOC  OASIS  PG&E  PCT  OpenADR  PDC  REST  RFC  RTP  SDG&E D.2.5 Peak Day Credit (PDC) Peak Day Credit (PDC) is a DR 

Piette, Mary Ann

2009-01-01T23:59:59.000Z

44

Automated Demand Response and Commissioning  

E-Print Network [OSTI]

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

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

2005-01-01T23:59:59.000Z

45

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

E-Print Network [OSTI]

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

46

Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response  

E-Print Network [OSTI]

S.  Kiliccote.   Estimating Demand Response Load  Impacts: in California.   Demand Response Research Center, Lawrence and Techniques for Demand Response.  LBNL Report 59975.  

Kiliccote, Sila

2011-01-01T23:59:59.000Z

47

Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response  

E-Print Network [OSTI]

high.  Demand response helps to manage building electricity Building  Control Strategies and Techniques for Demand Response.  Non?Residential Building in California.   Demand Response 

Kiliccote, Sila

2011-01-01T23:59:59.000Z

48

Automated Demand Response Technologies and Demonstration in New York City using OpenADR  

E-Print Network [OSTI]

and G. Heffner. “Do enabling technologies affect customerAutomated Demand Response Technologies and Demonstration inof Standards and Technology (NIST) along with organizations

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

49

Development and Demonstration of the Open Automated Demand Response Standard for the Residential Sector  

SciTech Connect (OSTI)

The goal of this study was to demonstrate a demand response system that can signal nearly every customer in all sectors through the integration of two widely available and non- proprietary communications technologies--Open Automated Demand Response (OpenADR) over lnternet protocol and Utility Messaging Channel (UMC) over FM radio. The outcomes of this project were as follows: (1) a software bridge to allow translation of pricing signals from OpenADR to UMC; and (2) a portable demonstration unit with an lnternet-connected notebook computer, a portfolio of DR-enabling technologies, and a model home. The demonstration unit provides visitors the opportunity to send electricity-pricing information over the lnternet (through OpenADR and UMC) and then watch as the model appliances and lighting respond to the signals. The integration of OpenADR and UMC completed and demonstrated in this study enables utilities to send hourly or sub-hourly electricity pricing information simultaneously to the residential, commercial and industrial sectors.

Herter, Karen; Rasin, Josh; Perry, Tim

2009-11-30T23:59:59.000Z

50

Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings  

E-Print Network [OSTI]

Open Automated Demand Response Demonstration Project” LBNL-2009a). “Open Automated Demand Response Communications inand Actions for Industrial Demand Response in California. ”

Kiliccote, Sila

2010-01-01T23:59:59.000Z

51

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

SciTech Connect (OSTI)

This report summarizes the Lawrence Berkeley National Laboratory?s research to date in characterizing energy efficiency and automated demand response opportunities for wastewater treatment facilities in California. The report describes the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy use and demand, as well as details of the wastewater treatment process. It also discusses control systems and energy efficiency and automated demand response opportunities. In addition, several energy efficiency and load management case studies are provided for wastewater treatment facilities.This study shows that wastewater treatment facilities can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for automated demand response at little additional cost. These improved controls may prepare facilities to be more receptive to open automated demand response due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

Lekov, Alex; Thompson, Lisa; McKane, Aimee; Song, Katherine; Piette, Mary Ann

2009-04-01T23:59:59.000Z

52

Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR  

SciTech Connect (OSTI)

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 to the default day-ahead hourly pricing. We summarize the existing demand response programs in New York and discuss OpenADR communication, prioritization of demand response signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demand response capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate both demand response participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.

Kim, Joyce Jihyun; Yin, Rongxin; Kiliccote, Sila

2013-10-01T23:59:59.000Z

53

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

your Power. (2008). "Demand Response Programs." RetrievedS. (2008). Automated Demand Response Results from Multi-Yearusing Open Automated Demand Response, California Energy

Lekov, Alex

2009-01-01T23:59:59.000Z

54

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,...

55

Installation and Commissioning Automated Demand Response Systems  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

56

Design and Operation of an Open, Interoperable Automated Demand Response Infrastructure for Commercial Buildings  

E-Print Network [OSTI]

and Demand Response in Commercial Building,” Report No.Demand Response Infrastructure for Commercial Buildings MaryDemand Response Infrastructure for Commercial Buildings Mary

Piette, Mary Ann

2010-01-01T23:59:59.000Z

57

Automated Demand Response: The Missing Link in the Electricity Value Chain  

E-Print Network [OSTI]

and Open Automated Demand Response. In Grid Interop Forum.Berkeley National Laboratory. Demand Response ResearchCenter, Demand Response Research Center PIER Team Briefing,

McKane, Aimee

2010-01-01T23:59:59.000Z

58

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

Consulting), and Dave Shroyer (SCG). Demand Response andOpen Automated Demand Response Opportunities for DataIAW Research Team, Demand Response Research Center, Lawrence

Watson, David S.

2013-01-01T23:59:59.000Z

59

Automated Demand Response Technologies and Demonstration in New York City using OpenADR  

E-Print Network [OSTI]

commercial building, demand response, dynamic pricing,demand response (Auto-DR) in large commercial buildingsdemand response (Auto-DR) in large commercial buildings

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

60

Automated Demand Response and Commissioning  

SciTech Connect (OSTI)

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.

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

2005-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network [OSTI]

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

Thompson, Lisa

2008-01-01T23:59:59.000Z

62

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network [OSTI]

Signals. ” SGIP NIST Smart Grid Collaboration Site. http://emix/. Last accessed: Open Smart Grid Users Group. “OpenADROpenADR technologies and Smart Grid standards activities.

Ghatikar, Girish

2010-01-01T23:59:59.000Z

63

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network [OSTI]

Signals. ” SGIP NIST Smart Grid Collaboration Site. http://Presented at the Grid Interop Forum, Albuquerque, NM.Last accessed: Open Smart Grid Users Group. “OpenADR Task

Ghatikar, Girish

2010-01-01T23:59:59.000Z

64

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

SciTech Connect (OSTI)

Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities.

Thompson, Lisa; Song, Katherine; Lekov, Alex; McKane, Aimee

2008-11-19T23:59:59.000Z

65

Results and commissioning issues from an automated demand response pilot  

E-Print Network [OSTI]

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

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

2004-01-01T23:59:59.000Z

66

Price Responsive Demand in New York Wholesale Electricity Market using OpenADR  

E-Print Network [OSTI]

Advanced Metering, and Demand Response in Electricity2006. Benefits of Demand Response in Electricity Markets and2010. Open Automated Demand Response Technologies for

Kim, Joyce Jihyun

2013-01-01T23:59:59.000Z

67

Automated Demand Response and Commissioning  

E-Print Network [OSTI]

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

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

2005-01-01T23:59:59.000Z

68

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

produce the greatest energy and demand savings. Aeration andand C.Y. Chang (2005). "Energy Demand in Sludge Dewatering."be modified to reduce energy demand during demand response

Lekov, Alex

2010-01-01T23:59:59.000Z

69

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network [OSTI]

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

Piette, Mary Ann

2010-01-01T23:59:59.000Z

70

Results and commissioning issues from an automated demand response pilot  

E-Print Network [OSTI]

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

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

2004-01-01T23:59:59.000Z

71

Scenarios for Consuming Standardized Automated Demand Response Signals  

E-Print Network [OSTI]

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

Koch, Ed

2009-01-01T23:59:59.000Z

72

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network [OSTI]

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

Piette, Mary Ann

2010-01-01T23:59:59.000Z

73

Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR  

E-Print Network [OSTI]

and demand response for large commercial buildings in Newdemand response and energy efficiency in commercial buildings.demand response participation for large commercial buildings

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

74

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network [OSTI]

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"

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

2006-01-01T23:59:59.000Z

75

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network [OSTI]

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

Kiliccote, Sila

2014-01-01T23:59:59.000Z

76

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

best practices that could be applied to form the basis for demand responsebest practices that could be applicable in improving the energy efficiency and demand responsedemand response activities. The following case studies illustrate best practices

Lekov, Alex

2010-01-01T23:59:59.000Z

77

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

best practices that could be applicable in improving the energy efficiency and demand responsebest practices that could be applied to form the basis for demand responsedemand response activities. The following case studies illustrate best practices

Lekov, Alex

2010-01-01T23:59:59.000Z

78

Installation and Commissioning Automated Demand Response Systems  

SciTech Connect (OSTI)

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.

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

79

Home Network Technologies and Automating Demand Response  

SciTech Connect (OSTI)

Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

McParland, Charles

2009-12-01T23:59:59.000Z

80

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

E-Print Network [OSTI]

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

Povinelli, Richard J.

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Fast Automated Demand Response to Enable the Integration of Renewable  

E-Print Network [OSTI]

LBNL-5555E Fast Automated Demand Response to Enable the Integration of Renewable Resources David S The work described in this report was coordinated by the Demand Response Research Center and funded ABSTRACT This study examines how fast automated demand response (AutoDR) can help mitigate grid balancing

82

Field Demonstration of Automated Demand Response for Both Winter and  

E-Print Network [OSTI]

) is a demand-side management strategy to reduce electricity use during times of high peak electric loads;1 Field Demonstration of Automated Demand Response for Both Winter and Summer Events in Large Buildings of a series of field test of automated demand response systems in large buildings in the Pacific Northwest

83

Opportunities for Automated Demand Response in Wastewater Treatment  

E-Print Network [OSTI]

LBNL-6056E Opportunities for Automated Demand Response in Wastewater Treatment Facilities Figure 1: Simplified diagram of major processes at a typical wastewater treatment plant #12;Results

84

Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings  

E-Print Network [OSTI]

Automated Demand Response for Small Commercial Buildings. ”Demand Response Strategies and Commissioning Commercial Buildingfor Automated Demand Response in Commercial Buildings Sila

Kiliccote, Sila

2010-01-01T23:59:59.000Z

85

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

SciTech Connect (OSTI)

This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

Lekov, Alex; Thompson, Lisa; McKane, Aimee; Rockoff, Alexandra; Piette, Mary Ann

2009-05-11T23:59:59.000Z

86

Installation and Commissioning Automated Demand Response Systems  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

87

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

E-Print Network [OSTI]

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...

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

2013-01-01T23:59:59.000Z

88

A DISTRIBUTED INTELLIGENT AUTOMATED DEMAND RESPONSE BUILDING MANAGEMENT SYSTEM  

SciTech Connect (OSTI)

The goal of the 2.5 year Distributed Intelligent Automated Demand Response (DIADR) project was to reduce peak electricity load of Sutardja Dai Hall at UC Berkeley by 30% while maintaining a healthy, comfortable, and productive environment for the occupants. We sought to bring together both central and distributed control to provide “deep” demand response1 at the appliance level of the building as well as typical lighting and HVAC applications. This project brought together Siemens Corporate Research and Siemens Building Technology (the building has a Siemens Apogee Building Automation System (BAS)), Lawrence Berkeley National Laboratory (leveraging their Open Automated Demand Response (openADR), Auto-­?Demand Response, and building modeling expertise), and UC Berkeley (related demand response research including distributed wireless control, and grid-­?to-­?building gateway development). Sutardja Dai Hall houses the Center for Information Technology Research in the Interest of Society (CITRIS), which fosters collaboration among industry and faculty and students of four UC campuses (Berkeley, Davis, Merced, and Santa Cruz). The 141,000 square foot building, occupied in 2009, includes typical office spaces and a nanofabrication laboratory. Heating is provided by a district heating system (steam from campus as a byproduct of the campus cogeneration plant); cooling is provided by one of two chillers: a more typical electric centrifugal compressor chiller designed for the cool months (Nov-­? March) and a steam absorption chiller for use in the warm months (April-­?October). Lighting in the open office areas is provided by direct-­?indirect luminaries with Building Management System-­?based scheduling for open areas, and occupancy sensors for private office areas. For the purposes of this project, we focused on the office portion of the building. Annual energy consumption is approximately 8053 MWh; the office portion is estimated as 1924 MWh. The maximum peak load during the study period was 1175 kW. Several new tools facilitated this work, such as the Smart Energy Box, the distributed load controller or Energy Information Gateway, the web-­?based DR controller (dubbed the Central Load-­?Shed Coordinator or CLSC), and the Demand Response Capacity Assessment & Operation Assistance Tool (DRCAOT). In addition, an innovative data aggregator called sMAP (simple Measurement and Actuation Profile) allowed data from different sources collected in a compact form and facilitated detailed analysis of the building systems operation. A smart phone application (RAP or Rapid Audit Protocol) facilitated an inventory of the building’s plug loads. Carbon dioxide sensors located in conference rooms and classrooms allowed demand controlled ventilation. The extensive submetering and nimble access to this data provided great insight into the details of the building operation as well as quick diagnostics and analyses of tests. For example, students discovered a short-­?cycling chiller, a stuck damper, and a leaking cooling coil in the first field tests. For our final field tests, we were able to see how each zone was affected by the DR strategies (e.g., the offices on the 7th floor grew very warm quickly) and fine-­?tune the strategies accordingly.

Auslander, David; Culler, David; Wright, Paul; Lu, Yan; Piette, Mary

2013-12-30T23:59:59.000Z

89

Opportunities for Open Automated Demand Response in Wastewater Treatment Facilities in California - Phase II Report. San Luis Rey Wastewater Treatment Plant Case Study  

E-Print Network [OSTI]

your Power. (2008). "Demand Response Programs." RetrievedTool Berkeley, CA, Demand Response Research Center.2008). "What is Demand Response?" Retrieved 10/10/2008, from

Thompson, Lisa

2010-01-01T23:59:59.000Z

90

Summary of the 2006 Automated Demand Response Pilot  

E-Print Network [OSTI]

This paper discusses the specific concept for, design of, and results from a pilot program to automate demand response with critical peak pricing. California utilities have been exploring the use of critical peak pricing (CPP) to help reduce peak...

Piette, M.; Kiliccote, S.

2007-01-01T23:59:59.000Z

91

Role of Standard Demand Response Signals for Advanced Automated Aggregation  

SciTech Connect (OSTI)

Emerging standards such as OpenADR enable Demand Response (DR) Resources to interact directly with Utilities and Independent System Operators to allow their facility automation equipment to respond to a variety of DR signals ranging from day ahead to real time ancillary services. In addition, there are Aggregators in today’s markets who are capable of bringing together collections of aggregated DR assets and selling them to the grid as a single resource. However, in most cases these aggregated resources are not automated and when they are, they typically use proprietary technologies. There is a need for a framework for dealing with aggregated resources that supports the following requirements: • Allows demand-side resources to participate in multiple DR markets ranging from wholesale ancillary services to retail tariffs without being completely committed to a single entity like an Aggregator; • Allow aggregated groups of demand-side resources to be formed in an ad hoc fashion to address specific grid-side issues and support the optimization of the collective response of an aggregated group along a number of different dimensions. This is important in order to taylor the aggregated performance envelope to the needs to of the grid; • Allow aggregated groups to be formed in a hierarchical fashion so that each group can participate in variety of markets from wholesale ancillary services to distribution level retail tariffs. This paper explores the issues of aggregated groups of DR resources as described above especially within the context of emerging smart grid standards and the role they will play in both the management and interaction of various grid-side entities with those resources.

Lawrence Berkeley National Laboratory; Kiliccote, Sila

2011-11-18T23:59:59.000Z

92

Scenarios for Consuming Standardized Automated Demand Response Signals  

SciTech Connect (OSTI)

Automated Demand Response (DR) programs require that Utility/ISO's deliver DR signals to participants via a machine to machine communications channel. Typically these DR signals constitute business logic information (e.g. prices and reliability/shed levels) as opposed to commands to control specific loads in the facility. At some point in the chain from the Utility/ISO to the loads in a facility, the business level information sent by the Utility/ISO must be processed and used to execute a DR strategy for the facility. This paper explores the various scenarios and types of participants that may utilize DR signals from the Utility/ISO. Specifically it explores scenarios ranging from single end user facility, to third party facility managers and DR Aggregators. In each of these scenarios it is pointed out where the DR signal sent from the Utility/ISO is processed and turned into the specific load control commands that are part of a DR strategy for a facility. The information in these signals is discussed. In some cases the DR strategy will be completely embedded in the facility while in others it may be centralized at a third party (e.g. Aggregator) and part of an aggregated set of facilities. This paper also discusses the pros and cons of the various scenarios and discusses how the Utility/ISO can use an open standardized method (e.g. Open Automated Demand Response Communication Standards) for delivering DR signals that will promote interoperability and insure that the widest range of end user facilities can participate in DR programs regardless of which scenario they belong to.

Koch, Ed; Piette, Mary Ann

2008-10-03T23:59:59.000Z

93

Automated Demand Response: The Missing Link in the Electricity Value Chain  

E-Print Network [OSTI]

Laboratory. Berkeley. Demand Response Research Center,and Automated Demand Response in Wastewater TreatmentLaboratory. Berkeley. Demand Response Research Center,

McKane, Aimee

2010-01-01T23:59:59.000Z

94

Development and evaluation of fully automated demand response in large facilities  

E-Print Network [OSTI]

and Demand Response in Commercial Buildings. ” LBNL Reportautomated Demand Response (DR) technologies in buildings.Automated Demand Response is initiated at a building or

Piette, Mary Ann; Sezgen, Osman; Watson, David S.; Motegi, Naoya; Shockman, Christine; ten Hope, Laurie

2004-01-01T23:59:59.000Z

95

Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Markets  

E-Print Network [OSTI]

Wholesale Electricity Demand Response Program Comparison,J. (2009) Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services.

Cappers, Peter

2014-01-01T23:59:59.000Z

96

Field Demonstration of Automated Demand Response for Both Winter and Summer Events in Large Buildings in the Pacific Northwest  

SciTech Connect (OSTI)

There are growing strains on the electric grid as cooling peaks grow and equipment ages. Increased penetration of renewables on the grid is also straining electricity supply systems and the need for flexible demand is growing. This paper summarizes results of a series of field test of automated demand response systems in large buildings in the Pacific Northwest. The objective of the research was two fold. One objective was to evaluate the use demand response automation technologies. A second objective was to evaluate control strategies that could change the electric load shape in both winter and summer conditions. Winter conditions focused on cold winter mornings, a time when the electric grid is often stressed. The summer test evaluated DR strategies in the afternoon. We found that we could automate both winter and summer control strategies with the open automated demand response communication standard. The buildings were able to provide significant demand response in both winter and summer events.

Piette, Mary Ann; Kiliccote, Sila; Dudley, Junqiao H.

2011-11-11T23:59:59.000Z

97

Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings  

SciTech Connect (OSTI)

California is a leader in automating demand response (DR) to promote low-cost, consistent, and predictable electric grid management tools. Over 250 commercial and industrial facilities in California participate in fully-automated programs providing over 60 MW of peak DR savings. This paper presents a summary of Open Automated DR (OpenADR) implementation by each of the investor-owned utilities in California. It provides a summary of participation, DR strategies and incentives. Commercial buildings can reduce peak demand from 5 to 15percent with an average of 13percent. Industrial facilities shed much higher loads. For buildings with multi-year savings we evaluate their load variability and shed variability. We provide a summary of control strategies deployed, along with costs to install automation. We report on how the electric DR control strategies perform over many years of events. We benchmark the peak demand of this sample of buildings against their past baselines to understand the differences in building performance over the years. This is done with peak demand intensities and load factors. The paper also describes the importance of these data in helping to understand possible techniques to reach net zero energy using peak day dynamic control capabilities in commercial buildings. We present an example in which the electric load shape changed as a result of a lighting retrofit.

Kiliccote, Sila; Piette, Mary Ann; Mathieu, Johanna; Parrish, Kristen

2010-05-14T23:59:59.000Z

98

2008-2010 Research Summary: Analysis of Demand Response Opportunities in California Industry  

E-Print Network [OSTI]

K.C. Mares, D. Shroyer. 2010. Demand Response andOpen Automated Demand Response Opportunities for Dataand the Role of Automated Demand Response. Lawrence Berkeley

Goli, Sasank

2013-01-01T23:59:59.000Z

99

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

Best Practices. Kiliccote, S. (2008). Automated Demand Responsebest operation practices and behaviors to enhance the impact of DR activities. 1.0 Introduction Background and Overview Demand Response (

Lekov, Alex

2009-01-01T23:59:59.000Z

100

Market transformation lessons learned from an automated demand response test in the Summer and Fall of 2003  

E-Print Network [OSTI]

of Fully Automated Demand Response in Large Facilities”Learned from an Automated Demand Response Test in the SummerLearned from an Automated Demand Response Test in the Summer

Shockman, Christine; Piette, Mary Ann; ten Hope, Laurie

2004-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

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

E-Print Network [OSTI]

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

Han, Junqiao

2008-01-01T23:59:59.000Z

102

Results and commissioning issues from an automated demand responsepilot  

SciTech Connect (OSTI)

This paper describes a research project to develop and test Automated Demand Response hardware and software technology in large facilities. We describe the overall project and some of the commissioning and system design problems that took place. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability purposes, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. There were a number of specific commissioning challenges in conducting this test including software compatibility, incorrect time zones, IT and EMCS failures, and hardware issues. The knowledge needed for this type of system commissioning combines knowledge of building controls with network management and knowledge of emerging information technologies.

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

2004-08-05T23:59:59.000Z

103

Field Demonstration of Automated Demand Response for Both Winter and Summer Events in Large Buildings in the Pacific Northwest  

E-Print Network [OSTI]

automated demand response systems in large buildings in theBuilding Control Strategies and Techniques for Demand Response,buildings were able to provide significant demand response

Piette, Mary Ann

2014-01-01T23:59:59.000Z

104

Findings from the 2004 Fully Automated Demand Response Tests in Large  

E-Print Network [OSTI]

LBNL-58178 Findings from the 2004 Fully Automated Demand Response Tests in Large Facilities M;Findings from the 2004 Fully Automated Demand Response Tests in Large Facilities September 7, 2005 Mary Ann Manager Dave Michel Contract 500-03-026 Sponsored by the California Energy Commission PIER Demand Response

105

Automated Demand Response: The Missing Link in the Electricity Value Chain  

SciTech Connect (OSTI)

In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

McKane, Aimee; Rhyne, Ivin; Lekov, Alex; Thompson, Lisa; Piette, MaryAnn

2009-08-01T23:59:59.000Z

106

Automated Demand Response: The Missing Link in the Electricity Value Chain  

SciTech Connect (OSTI)

In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This 'electricity value chain' defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to 'demo' potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives. In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

McKane, Aimee; Rhyne, Ivin; Piette, Mary Ann; Thompson, Lisa; Lekov, Alex

2008-08-01T23:59:59.000Z

107

Field Testing of Automated Demand Response for Integration of Renewable Resources in California's Ancillary Services Market for Regulation Products  

E-Print Network [OSTI]

and Techniques for Demand Response”, May 2007. LBNL-59975 38the Role of Automated Demand Response, 2010. Watson, D. , N.Fast Automated Demand Response to Enable Integration of

Kiliccote, Sila

2013-01-01T23:59:59.000Z

108

Demand Response Opportunities in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

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).

Goli, Sasank

2012-01-01T23:59:59.000Z

109

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network [OSTI]

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

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

2006-01-01T23:59:59.000Z

110

Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings  

SciTech Connect (OSTI)

Small and medium commercial customers in California make up about 20-25% of electric peak load in California. With the roll out of smart meters to this customer group, which enable granular measurement of electricity consumption, the investor-owned utilities will offer dynamic prices as default tariffs by the end of 2011. Pacific Gas and Electric Company, which successfully deployed Automated Demand Response (AutoDR) Programs to its large commercial and industrial customers, started investigating the same infrastructures application to the small and medium commercial customers. This project aims to identify available technologies suitable for automating demand response for small-medium commercial buildings; to validate the extent to which that technology does what it claims to be able to do; and determine the extent to which customers find the technology useful for DR purpose. Ten sites, enabled by eight vendors, participated in at least four test AutoDR events per site in the summer of 2010. The results showed that while existing technology can reliably receive OpenADR signals and translate them into pre-programmed response strategies, it is likely that better levels of load sheds could be obtained than what is reported here if better understanding of the building systems were developed and the DR response strategies had been carefully designed and optimized for each site.

Page, Janie; Kiliccote, Sila; Dudley, Junqiao Han; Piette, Mary Ann; Chiu, Albert K.; Kellow, Bashar; Koch, Ed; Lipkin, Paul

2011-07-01T23:59:59.000Z

111

Direct versus Facility Centric Load Control for Automated Demand Response  

SciTech Connect (OSTI)

Direct load control (DLC) refers to the scenario where third party entities outside the home or facility are responsible for deciding how and when specific customer loads will be controlled in response to Demand Response (DR) events on the electric grid. Examples of third parties responsible for performing DLC may be Utilities, Independent System Operators (ISO), Aggregators, or third party control companies. DLC can be contrasted with facility centric load control (FCLC) where the decisions for how loads are controlled are made entirely within the facility or enterprise control systems. In FCLC the facility owner has more freedom of choice in how to respond to DR events on the grid. Both approaches are in use today in automation of DR and both will continue to be used in future market segments including industrial, commercial and residential facilities. This paper will present a framework which can be used to differentiate between DLC and FCLC based upon where decisions are made on how specific loads are controlled in response to DR events. This differentiation is then used to compare and contrast the differences between DLC and FCLC to identify the impact each has on:(1)Utility/ISO and third party systems for managing demand response, (2)Facility systems for implementing load control, (3)Communications networks for interacting with the facility and (4)Facility operators and managers. Finally a survey of some of the existing DR related specifications and communications standards is given and their applicability to DLC or FCLC. In general FCLC adds more cost and responsibilities to the facilities whereas DLC represents higher costs and complexity for the Utility/ISO. This difference is primarily due to where the DR Logic is implemented and the consequences that creates. DLC may be more certain than FCLC because it is more predictable - however as more loads have the capability to respond to DR signals, people may prefer to have their own control of end-use loads and FCLC systems. Research is needed to understand the predictability of FCLC which is related to the perceived value of the DR from the facility manager or home owner's perspective.

Koch, Ed; Piette, Mary Ann

2009-11-06T23:59:59.000Z

112

What China Can Learn from International Experiences in Developing a Demand Response Program  

E-Print Network [OSTI]

K.C. Mares, D. Shroyer. , 2010. Demand Response andOpen Automated Demand Response Opportunities for DataProcessing Industry Demand Response Participation: A Scoping

Shen, Bo

2013-01-01T23:59:59.000Z

113

An Automation System for Optimizing a Supply Chain Network Design under the Influence of Demand Uncertainty  

E-Print Network [OSTI]

Automation . . . . . . . . . . . . . . . . . . . . . . iii 3Automation . . . . . . . . . . . . . . . . . . . . . . 5Dashboard/Cockpit Automation . . . . . . . . . . . . .

Polany, Rany

2012-01-01T23:59:59.000Z

114

Measurement and evaluation techniques for automated demand response demonstration  

E-Print Network [OSTI]

and Demand Response in Commercial Buildings. ” Highdemand-response technologies in large commercial and institutional buildings.building method California Independent System Operator (Cal ISO)’s Demand Response

Motegi, Naoya; Piette, Mary Ann; Watson, David S.; Sezgen, Osman; ten Hope, Laurie

2004-01-01T23:59:59.000Z

115

Intelligent Building Automation: A Demand Response Management Perspective  

E-Print Network [OSTI]

the energy consumption in response to energy price fluctuations, demand charges, or a direct request to reduce demand when the power grid reaches critical levels. However, in order for a demand response regime to be effective the building will need to have a...

Qazi, T.

2010-01-01T23:59:59.000Z

116

Abstract--Implementation of Distribution Automation (DA) and Demand Side Management (DSM) intended to serve both  

E-Print Network [OSTI]

Abstract--Implementation of Distribution Automation (DA) and Demand Side Management (DSM) intended with differentiate QoS in a multitasking environment. I. INTRODUCTION ODERN society demands a reliable and high by the distribution utility for the security. REMPLI (Remote Energy Management over Power Lines and Internet) system

Paris-Sud XI, Université de

117

Automated demand response applied to a set of commercial facilities.  

E-Print Network [OSTI]

?? Commercial facility demand response refers to voluntary actions by customers that change their consumption of electric power in response to price signals, incentives, or… (more)

Lincoln, Donald F.

2010-01-01T23:59:59.000Z

118

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

SciTech Connect (OSTI)

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.

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

2011-08-15T23:59:59.000Z

119

Price Responsive Demand in New York Wholesale Electricity Market using OpenADR  

E-Print Network [OSTI]

and provide demand response (DR) through building controland provide demand response (DR) through building controlDemand Response Automation Server (DRAS) in a 15-minute interval. This allows the continuous monitoring of the building's

Kim, Joyce Jihyun

2013-01-01T23:59:59.000Z

120

DemandDirect | 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 NoPublic Utilities Address:011-DNA Jump to:52c8ff988c1 No38e4011f618bDeer Park,Dell Prairie,DeltaDemand

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Decon2LS: An Open-Source Software Package for Automated Processing...  

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

Software Package for Automated Processing and Visualization of High Resolution Mass Spectrometry Data. Decon2LS: An Open-Source Software Package for Automated Processing and...

122

Development and evaluation of fully automated demand response in large facilities  

SciTech Connect (OSTI)

This report describes the results of a research project 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 electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through cost of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing, characterization, and evaluation relating to Auto-DR. This evaluation also included the related decisionmaking perspectives of the facility owners and managers. Another goal of this project was to develop and test a real-time signal for automated demand response that provided a common communication infrastructure for diverse facilities. The six facilities recruited for this project were selected from the facilities that received CEC funds for new DR technology during California's 2000-2001 electricity crises (AB970 and SB-5X).

Piette, Mary Ann; Sezgen, Osman; Watson, David S.; Motegi, Naoya; Shockman, Christine; ten Hope, Laurie

2004-03-30T23:59:59.000Z

123

Mass Market Demand Response and Variable Generation Integration Issues: A Scoping Study  

E-Print Network [OSTI]

Reliability Corporation National Institute of Standards and Technology Open Access Transmission Tariff Open Automated Demand Response Protocol Public Utility Commission Photovoltaic

Cappers, Peter

2012-01-01T23:59:59.000Z

124

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network [OSTI]

HVAC Control System Advanced Telemetry No DDC Zone Control Data Trending DDC Zone Control Data Trending Detail EMCS Trends

Dudley, June Han

2009-01-01T23:59:59.000Z

125

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network [OSTI]

It includes the following:  Load reduction bids per time It includes the following:  Load reduction bids per time It includes the following:  Load reduction bids per time 

Piette, Mary Ann

2009-01-01T23:59:59.000Z

126

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network [OSTI]

Schedules. ” www.pge.com/tariffs/. Last accessed: 4/26/10.and PG&E’s PDP rates (as a peak pricing tariff and as aproxy for TOU pricing tariff) were used. The technology

Ghatikar, Girish

2010-01-01T23:59:59.000Z

127

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

with hydro power and wind integration, more DR may be neededload growth, wind power integration, and fish operations are

Kiliccote, Sila

2010-01-01T23:59:59.000Z

128

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network [OSTI]

locational marginal price (LMP) for the Hourly DA_RTP pricingpricing structure for wholesale markets. For example, ISO-NE’s hourly locational marginal

Ghatikar, Girish

2010-01-01T23:59:59.000Z

129

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network [OSTI]

Center for the Study of Energy Markets Paper CSEMWP-105.OASIS SDO. 2010b. “Energy Market Information Exchange (eMIX)charges. • Wholesale energy market prices are volatile, and

Ghatikar, Girish

2010-01-01T23:59:59.000Z

130

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network [OSTI]

tonnage is due to air?source  heat pumps (Table 4).    Baseboard heater Air-source Heat Pump Ground-Source Heat

Dudley, June Han

2009-01-01T23:59:59.000Z

131

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network [OSTI]

Models DRAS Client API Simple REST Services Simple SOAPAPI SPECIFICATIONS 103   Utility Program Operator APIs .. 103   Participant Operator APIs.. 103   DRAS Client APIs 103   Use of Simple REST API and the minimum methods that must be supported are  as described in Section 9.3.1 that are similar for simple REST 

Piette, Mary Ann

2009-01-01T23:59:59.000Z

132

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

in significant energy and demand savings for refrigeratedbe modified to reduce energy demand during demand responsein refrigerated warehouse energy demand if they are not

Lekov, Alex

2009-01-01T23:59:59.000Z

133

automated worm response: Topics by E-print Network  

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

a means to accurately model the early phase Bagchi, Saurabh 11 Analysis of Open Automated Demand Response Deployments in California Energy Storage, Conversion and Utilization...

134

automated perfit analysis: Topics by E-print Network  

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

12;The Big Picture X-ray Microanalysis Perkins, Richard A. 10 Analysis of Open Automated Demand Response Deployments in California Energy Storage, Conversion and Utilization...

135

Manz Automation AG | 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 - 429Lacey,(MonasterLowellis a town in CarrollManteca,Change | OpenMany Farms,Manz

136

AIS Automation Dresden | 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 NoPublic Utilities Address: 160 East 300 SouthWater Rights,Information OfOpen EnergyEnergyAGE UFMGAGNIAHLAIS

137

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

E-Print Network [OSTI]

and Techniques for Demand Response, LBNL-59975, May 2007 [Protocol Development for Demand Response Calculation – Findsand S. Kiliccote, Estimating Demand Response Load Impacts:

Han, Junqiao

2008-01-01T23:59:59.000Z

138

Development and evaluation of fully automated demand response in large facilities  

E-Print Network [OSTI]

Development for Demand Response Calculation - Findings and2003. “Dividends with Demand Response. ” ASHRAE Journal,Management and Demand Response in Commercial Buildings. ”

Piette, Mary Ann; Sezgen, Osman; Watson, David S.; Motegi, Naoya; Shockman, Christine; ten Hope, Laurie

2004-01-01T23:59:59.000Z

139

Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings  

E-Print Network [OSTI]

2010 Assessment of Demand Response and  Advanced Metering:  Development for Demand Response  Calculation ? Findings and Energy  Efficiency and  Demand Response with Communicating 

Page, Janie

2012-01-01T23:59:59.000Z

140

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

E-Print Network [OSTI]

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,”

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings  

E-Print Network [OSTI]

Demand Response for Small Commercial Buildings.   Lawrence small?medium buildings’ roles in demand response  efforts.  demand response for small? medium commercial buildings 

Page, Janie

2012-01-01T23:59:59.000Z

142

Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study  

SciTech Connect (OSTI)

This report details a study into the demand response potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demand response and automated demand response, and this study was conducted to investigate facility attributes that are conducive to demand response or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demand response capabilities The average baseline demand at the Southeast facility was approximately 4 MW. During the rainy season (October-March) the facility treated 40% more wastewater than the dry season, but demand only increased by 4%. Submetering of the facility's lift pumps and centrifuges predicted load shifts capabilities of 154 kW and 86 kW, respectively, with large lift pump shifts in the rainy season. Analysis of demand data during maintenance events confirmed the magnitude of these possible load shifts, and indicated other areas of the facility with demand response potential. Load sheds were seen to be possible by shutting down a portion of the facility's aeration trains (average shed of 132 kW). Load shifts were seen to be possible by shifting operation of centrifuges, the gravity belt thickener, lift pumps, and external pump stations These load shifts were made possible by the storage capabilities of the facility and of the city's sewer system. Large load reductions (an average of 2,065 kW) were seen from operating the cogeneration unit, but normal practice is continuous operation, precluding its use for demand response. The study also identified potential demand response opportunities that warrant further study: modulating variable-demand aeration loads, shifting operation of sludge-processing equipment besides centrifuges, and utilizing schedulable self-generation.

Olsen, Daniel; Goli, Sasank; Faulkner, David; McKane, Aimee

2012-12-20T23:59:59.000Z

143

E-Print Network 3.0 - automated demand response Sample Search...  

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

75 Optimization and Control for Demand Management in Smart Grid Summary: Batteries, fuel cells, hydrogen, thermal storage, etc. UTILITIES Demand response, dynamic pricing,...

144

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

E-Print Network [OSTI]

shows how the actual load profile follows the hourly bidscriteria were as follows: Low load variability – enhancesloads, the actual loads do not closely follow the forecasted

Kiliccote, Sila

2010-01-01T23:59:59.000Z

145

Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response  

E-Print Network [OSTI]

Company   Service Oriented Architecture  Secure Socket based Web Service Oriented Architecture (SOA) for  platform?

Kiliccote, Sila

2011-01-01T23:59:59.000Z

146

Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response  

E-Print Network [OSTI]

U-tube fixtures. Shut off hot water heater. Increase zoneU-tube fixtures. Shut off hot water heater. Increase zoneof all lighting. Shut off hot water heater. Increase zone

Kiliccote, Sila

2011-01-01T23:59:59.000Z

147

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

Sodium Sulfur (NaS) Zinc- Air Battery Demand Response CostsSodium Sulfur (NaS) Zinc- Air Battery Low High AverageSodium Sulfur (NaS) Zinc- Air Battery Demand Response Costs

Watson, David S.

2013-01-01T23:59:59.000Z

148

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

E-Print Network [OSTI]

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

Garrido, Antonio

149

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

E-Print Network [OSTI]

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

Garrido, Antonio

150

Strategies for Demand Response in Commercial Buildings  

E-Print Network [OSTI]

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

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

2006-01-01T23:59:59.000Z

151

Changes in worldwide demand for metals (final). Open File report  

SciTech Connect (OSTI)

Worldwide demand for metals was analyzed to identify the important factors that explain differences in the level of demand among world countries. The per capita demand for steel, aluminum, copper, and total nonferrous metals was investigated for 40 to 50 countries over a 22-year period. These countries have been further grouped into four world regions for purposes of making generalizations about the importance of these factors for countries in different stages of development and with dissimilar levels of per capita gross domestic product (GDP). Intercountry and intertemporal differences are explained largely by differences in per capita GDP and changes over time in per capita GDP, oil real prices, and to a lesser extent, metal real prices. The trend in world consumption is dramatically different in the last decade than the previous one. In 1962-73, per capita consumption increased in all areas and consumption intensity (consumption divided by (GDP) increased in most areas). In 1973-84, per capita consumption fell in most areas and intensity fell dramatically, except in developing nations.

Faucett, J.G.; Chmelynski, H.J.

1986-08-01T23:59:59.000Z

152

Demand Response Energy Consulting 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 NoPublic Utilities Address:011-DNA Jump to:52c8ff988c1 No38e4011f618bDeer Park,Dell Prairie,DeltaDemand Response

153

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network [OSTI]

demand-side management activities and commercial buildings’demand-side management (DSM) framework presented in Figure 1 provides continuous energy management concepts for shaping electric loads in buildings,demand-side management activities, DR methods and levels of automation. We highlight OpenADR as a standard for commercial buildings

Kiliccote, Sila

2014-01-01T23:59:59.000Z

154

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

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,

Shen, Bo

2013-01-01T23:59:59.000Z

155

Property:OpenEI/UtilityRate/FlatDemandMonth8 | 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 ResourcesLoadingPenobscotInformation Max Jump to:FlatDemandMonth3 Jump to:FlatDemandMonth8 Jump to:

156

Property:OpenEI/UtilityRate/FlatDemandMonth9 | 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 ResourcesLoadingPenobscotInformation Max Jump to:FlatDemandMonth3 Jump to:FlatDemandMonth8 Jump

157

Property:OpenEI/UtilityRate/FixedDemandChargeMonth8 | Open Energy  

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 ResourcesLoadingPenobscotInformation Max Jump to: navigation,Information FixedDemandChargeMonth8

158

Property:OpenEI/UtilityRate/FlatDemandMonth4 | 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 ResourcesLoadingPenobscotInformation Max Jump to:FlatDemandMonth3 Jump to: navigation, search This

159

Property:OpenEI/UtilityRate/FlatDemandMonth5 | 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 ResourcesLoadingPenobscotInformation Max Jump to:FlatDemandMonth3 Jump to: navigation, search

160

Property:OpenEI/UtilityRate/FlatDemandMonth6 | 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 ResourcesLoadingPenobscotInformation Max Jump to:FlatDemandMonth3 Jump to: navigation,

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Property:OpenEI/UtilityRate/FlatDemandMonth7 | 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 ResourcesLoadingPenobscotInformation Max Jump to:FlatDemandMonth3 Jump to:

162

Property:OpenEI/UtilityRate/DemandChargePeriod2 | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump to:DemandChargePeriod2 Jump

163

Property:OpenEI/UtilityRate/DemandChargePeriod2FAdj | Open Energy  

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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump to:DemandChargePeriod2

164

Property:OpenEI/UtilityRate/DemandChargePeriod4 | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: Demand Charge Period 4

165

Property:OpenEI/UtilityRate/DemandChargePeriod4FAdj | Open Energy  

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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: Demand Charge Period

166

Property:OpenEI/UtilityRate/DemandChargePeriod5 | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: Demand Charge

167

Property:OpenEI/UtilityRate/DemandChargePeriod5FAdj | Open Energy  

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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: Demand

168

Property:OpenEI/UtilityRate/DemandChargePeriod6 | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: DemandNumber. Name:

169

Property:OpenEI/UtilityRate/DemandChargePeriod6FAdj | Open Energy  

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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: DemandNumber.

170

Property:OpenEI/UtilityRate/DemandChargePeriod7 | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: DemandNumber.This is a

171

Property:OpenEI/UtilityRate/DemandChargePeriod7FAdj | Open Energy  

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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: DemandNumber.This is

172

Property:OpenEI/UtilityRate/DemandChargePeriod8 | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: DemandNumber.This is

173

Property:OpenEI/UtilityRate/DemandChargePeriod8FAdj | Open Energy  

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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: DemandNumber.This

174

Property:OpenEI/UtilityRate/DemandChargePeriod9 | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms Jump to:URI Jump Name: DemandNumber.This

175

Property:OpenEI/UtilityRate/DemandWindow | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms JumpEnergyDemandWindow Jump to: navigation,

176

Property:OpenEI/UtilityRate/EnableDemandCharge | 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 ResourcesLoadingPenobscot County,ContAddr2NumberOfPrograms JumpEnergyDemandWindow Jump to:

177

Property:OpenEI/UtilityRate/FlatDemandMonth3 | 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 ResourcesLoadingPenobscotInformation Max Jump to:FlatDemandMonth3 Jump to: navigation, search This is

178

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

179

KSL Kuttler Automation Systems GmbH | 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 - 429 Throttled (botOpen6 Climate ZoneJeromeCountyKGRA Energy LLC JumpKOENEN GmbHKSL

180

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network [OSTI]

6/16/2010. OASIS SDO. “Energy Market Information Exchange (of Prices CAISO’s Wholesale Energy Market Prices PG&E’s PDPWe used the CAISO wholesale energy market prices for the RTP

Ghatikar, Girish

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Automated Demand Response Technologies and Demonstration in New York City using OpenADR  

E-Print Network [OSTI]

to the capacity and energy markets. As of 2011, only 15% ofcosts in the near term energy markets. NYS customers arein NYS’s wholesale energy market, innovations in building

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

182

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network [OSTI]

AND SMART GRID The GridWise® interoperability framework [6] was developed to facilitate systems integration and

Ghatikar, Girish

2010-01-01T23:59:59.000Z

183

Design and Operation of an Open, Interoperable Automated Demand Response Infrastructure for Commercial Buildings  

E-Print Network [OSTI]

Power Research Institute (EPRI) IntelliGrid Consortium, “ThePower Delivery System,” EPRI, Jan. 2, http://www.epri.com/Power Research Institute (EPRI) that started in 2004. The

Piette, Mary Ann

2010-01-01T23:59:59.000Z

184

Automated Demand Response Technologies and Demonstration in New York City using OpenADR  

E-Print Network [OSTI]

between buildings and various stakeholders in NYS includingbetween buildings and various stakeholders in NYS includingin NYS’s wholesale energy market, innovations in building

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

185

Automated Demand Response Technologies and Demonstration in New York City using OpenADR  

E-Print Network [OSTI]

system operators, energy suppliers, etc. ) to subscribingor retail third-party energy supplier contract. In NYS, MHPfrom a retail energy supplier. Con Edison’s customers who

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

186

Automation systems for Demand Response, ForskEL (Smart Grid Project) | Open  

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 Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWendeGuo Feng Bio Jump to: navigation, searchEnergy

187

Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards  

E-Print Network [OSTI]

of  Standards  and  Technology,  Lawrence  Berkeley  Honeywell,  and  IPKeys  Technologies.  Published  in  the  Environmental  Energy  Technologies  Division.  Presented  

Ghatikar, Girish

2014-01-01T23:59:59.000Z

188

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network [OSTI]

Fully Automated Demand Response Tests in Large Facilities”.also provided through the Demand Response Research Center (of Fully Automated Demand Response in Large Facilities”

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

189

The Impact of Control Technology on the Demand Response Potential of California Industrial Refrigerated Facilities Final Report  

E-Print Network [OSTI]

and Automated Demand Response in Industrial RefrigeratedDemand Response .. ..Technology on the Demand Response Potential of California

Scott, Doug

2014-01-01T23:59:59.000Z

190

Participation through Automation: Fully Automated Critical Peak Pricing in Commercial Buildings  

E-Print Network [OSTI]

Figure 2. Demand Response Automation Server and BuildingDemand Response Control Strategies in Commercial Buildings,X X Example of Demand Response from an Office Building This

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

2006-01-01T23:59:59.000Z

191

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)

192

Test Automation Test Automation  

E-Print Network [OSTI]

Test Automation Test Automation Mohammad Mousavi Eindhoven University of Technology, The Netherlands Software Testing 2013 Mousavi: Test Automation #12;Test Automation Outline Test Automation Mousavi: Test Automation #12;Test Automation Why? Challenges of Manual Testing Test-case design: Choosing inputs

Mousavi, Mohammad

193

Automated Critical Peak Pricing Field Tests: Program Description and Results  

E-Print Network [OSTI]

is manual demand response -- where building staff receive afor demand response analysis ?ELECTRIC Whole building powerof automated demand response (Auto-DR) in buildings and

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-01-01T23:59:59.000Z

194

Automated Demand Response and Commissioning  

E-Print Network [OSTI]

HVAC strategies include concepts such as global zone set point increase (from 72 °F-75 °F), resetting duct static pressure,

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

2005-01-01T23:59:59.000Z

195

Automated 3D Rigid Registration of Open 2D Manifolds Sune Darkner1,2, Martin Vester-Christensen1, Rasmus Larsen1, Claus Nielsen2, Rasmus R. Paulsen2  

E-Print Network [OSTI]

Automated 3D Rigid Registration of Open 2D Manifolds Sune Darkner1,2, Martin Vester-Christensen1 on the boundary of open surfaces so this is not the right choice for our data. Corresponding author: Sune Darkner

196

Participation through Automation: Fully Automated Critical Peak Pricing in Commercial Buildings  

E-Print Network [OSTI]

Figure 2. Demand Response Automation Server and BuildingII system to notify the Automation Server of an up comingoccurs day-ahead). 2. The Automation Server posts two pieces

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

2006-01-01T23:59:59.000Z

197

Advanced Controls and Communications for Demand Response and Energy Efficiency in Commercial Buildings  

E-Print Network [OSTI]

of Fully Automated Demand Response in Large Facilities”NYSERDA) and the Demand Response Research Center (LLC “Working Group 2 Demand Response Program Evaluation –

Kiliccote, Sila; Piette, Mary Ann; Hansen, David

2006-01-01T23:59:59.000Z

198

Analytical Frameworks to Incorporate Demand Response in Long-term Resource Planning  

E-Print Network [OSTI]

Cost- effectiveness of Demand Response. ” Prepared for theon the National Action Plan on Demand Response, February.Role of Automated Demand Response. ” LBNL-4189E, November.

Satchwell, Andrew

2014-01-01T23:59:59.000Z

199

Intelligent Building Energy Information and Control Systems for Low-Energy Operations and Optimal Demand Response  

E-Print Network [OSTI]

account  demand  response  signals,  building?integrated of Automated Demand Response in Commercial Buildings.  and Demand Response in Commercial  Buildings. , LBNL 

Piette, Mary Ann

2014-01-01T23:59:59.000Z

200

Chilled Water Thermal Storage System and Demand Response at the University of California at Merced  

E-Print Network [OSTI]

Building Control Strategies and Techniques for Demand Response.of Automated Demand Response in a Large Office Building.there demand response potential in commercial building that

Granderson, Jessica

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

Embaby, and M. Rao (2006). Refinery Wastewater Treatment: Aand Assessment of Al Ruwais Refinery Wastewater." Journal ofThe Effects of Petroleum Refinery Wastewater on the Rate of

Lekov, Alex

2010-01-01T23:59:59.000Z

202

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

Processing Industry Energy Efficiency Initiative, CaliforniaK. (2004). Bringing Energy Efficiency to the Water andAgricultural/Water End-Use Energy Efficiency Program. Lyco

Lekov, Alex

2010-01-01T23:59:59.000Z

203

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

nanofiltration, and reverse osmosis membranes, as well asion exchange, reverse osmosis, and ammonia stripping.Metcalf & Eddy Inc. 2003). Reverse osmosis occurs when water

Lekov, Alex

2010-01-01T23:59:59.000Z

204

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

50 Effluent Hydropower- Kilowatt Output as Function of HeadDepartment of Energy (2003). Hydropower Setting a Course forEnergy Commission). Hydropower: Hydropower turbines for low-

Lekov, Alex

2010-01-01T23:59:59.000Z

205

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

best practices that could be applicable in improving the energy efficiencyEnergy efficiency measures that have been successfully implemented in municipal wastewater treatment facilities can serve as best practices

Lekov, Alex

2010-01-01T23:59:59.000Z

206

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

A byproduct of this process is biogas which contains 50– 70%Partners LLC 2007). This biogas can be used to generate heatmethane fermentation and biogas recovery (Green 1995).

Lekov, Alex

2010-01-01T23:59:59.000Z

207

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

biological operations. Tertiary treatment processes wastewaterwastewater treatment system, called the Living Machine, uses natural non-chemical biologicalbiological (Wilkinson 2000). Each type generally refers to a certain point in the wastewater treatment

Lekov, Alex

2010-01-01T23:59:59.000Z

208

Toward a Systematic Approach to the Design and Evaluation of Automated Mobility-on-Demand Systems: A Case Study in Singapore  

E-Print Network [OSTI]

The objective of this work is to provide analytical guidelines and financial justification for the design of shared-vehicle mobility-on-demand systems. Specifically, we consider the fundamental issue of determining the ...

Spieser, Kevin

2014-04-24T23:59:59.000Z

209

Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Study Case in New York  

E-Print Network [OSTI]

of Fully Automated Demand Response in Large Facilities.for Energy Efficiency and Demand Response”, Proceedings ofAuthority (NYSERDA), the Demand Response Research Center (

Kiliccote, Sila; Piette, Mary Ann; Watson, David S.; Hughes, Glenn

2006-01-01T23:59:59.000Z

210

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

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

211

Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results  

E-Print Network [OSTI]

Techniques  for  Demand  Response.   Lawrence  Berkeley Communications  for  Demand Response and Energy Efficiency for  Automated  Demand  Response  Demonstration.   2004.  

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

2007-01-01T23:59:59.000Z

212

automated critical peakpricing: Topics by E-print Network  

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

of California eScholarship Repository Summary: to show the potential for automated demand response systems.of their demand response strategy. If the potential site...

213

Progress toward Producing Demand-Response-Ready Appliances  

SciTech Connect (OSTI)

This report summarizes several historical and ongoing efforts to make small electrical demand-side devices like home appliances more responsive to the dynamic needs of electric power grids. Whereas the utility community often reserves the word demand response for infrequent 2 to 6 hour curtailments that reduce total electrical system peak load, other beneficial responses and ancillary services that may be provided by responsive electrical demand are of interest. Historically, demand responses from the demand side have been obtained by applying external, retrofitted, controlled switches to existing electrical demand. This report is directed instead toward those manufactured products, including appliances, that are able to provide demand responses as soon as they are purchased and that require few, or no, after-market modifications to make them responsive to needs of power grids. Efforts to be summarized include Open Automated Demand Response, the Association of Home Appliance Manufacturer standard CHA 1, a simple interface being developed by the U-SNAP Alliance, various emerging autonomous responses, and the recent PinBus interface that was developed at Pacific Northwest National Laboratory.

Hammerstrom, Donald J.; Sastry, Chellury

2009-12-01T23:59:59.000Z

214

OpenADR Open Source Toolkit: Developing Open Source Software for the Smart Grid  

E-Print Network [OSTI]

building and facilities managers implement automated demand responsedemand shedding strategies quickly and automatically when requested by utility operations. By integrating automated building responses

McParland, Charles

2012-01-01T23:59:59.000Z

215

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

E-Print Network [OSTI]

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

Li, Baochun

216

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...

217

FEMP Presents Its Newest On-Demand eTraining Course on Building...  

Energy Savers [EERE]

On-Demand eTraining Course on Building Automation Systems FEMP Presents Its Newest On-Demand eTraining Course on Building Automation Systems November 19, 2013 - 12:00am Addthis...

218

Opportunities, Barriers and Actions for Industrial Demand Response in California  

SciTech Connect (OSTI)

In 2006 the Demand Response Research Center (DRRC) formed an Industrial Demand Response Team to investigate opportunities and barriers to implementation of Automated Demand Response (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated controls strategies that are 'hardened' and pre-programmed into facility's software and hardware; More affordable because automation can help reduce labor costs associated with manual DR strategies initiated by facility staff and can be used for long-term.

McKane, Aimee T.; Piette, Mary Ann; Faulkner, David; Ghatikar, Girish; Radspieler Jr., Anthony; Adesola, Bunmi; Murtishaw, Scott; Kiliccote, Sila

2008-01-31T23:59:59.000Z

219

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

E-Print Network [OSTI]

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

220

Home Network Technologies and Automating Demand Response  

E-Print Network [OSTI]

side. Table 1. US Energy Consumption by Sector (2009 -half of all energy consumption in the US. On a per customer

McParland, Charles

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Distributed Automated Demand Response - Energy Innovation Portal  

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 phasesDataTranslocation oftheAmperometricEnergy Analysis Energy Analysis

222

Demand Response Opportunities in Industrial Refrigerated Warehouses in California  

SciTech Connect (OSTI)

Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

Goli, Sasank; McKane, Aimee; Olsen, Daniel

2011-06-14T23:59:59.000Z

223

2008-2010 Research Summary: Analysis of Demand Response  

E-Print Network [OSTI]

LBNL-5680E 2008-2010 Research Summary: Analysis of Demand Response Opportunities in California. · #12;· · · 1.1. Role of the Demand Response Research Center · · · · · · #12;Figure 2: Discovery Process Treatment Facility Controls #12;2.1.2. Automated Demand Response Strategies #12;2.1.3. San Luis Rey

224

Demand Response Opportunities in Industrial Refrigerated Warehouses in  

E-Print Network [OSTI]

LBNL-4837E Demand Response Opportunities in Industrial Refrigerated Warehouses in California Sasank thereof or The Regents of the University of California. #12;Demand Response Opportunities in Industrial centralized control systems can be excellent candidates for Automated Demand Response (Auto- DR) due

225

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

E-Print Network [OSTI]

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

Dudley, Junqiao Han

2010-01-01T23:59:59.000Z

226

Demand Charges | 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 NoPublic Utilities Address:011-DNA Jump to:52c8ff988c1 No38e4011f618bDeer Park,Dell Prairie,Delta

227

Energy Demand | 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 No revisionWind,Soilsfilesystem socket.pngFigure 55 From

228

Test Automation Ant JUnit Test Automation  

E-Print Network [OSTI]

Test Automation Ant JUnit Test Automation Mohammad Mousavi Eindhoven University of Technology, The Netherlands Software Testing 2012 Mousavi: Test Automation #12;Test Automation Ant JUnit Outline Test Automation Ant JUnit Mousavi: Test Automation #12;Test Automation Ant JUnit Why? Challenges of Manual Testing

Mousavi, Mohammad

229

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

230

Wireless Demand Response Controls for HVAC Systems  

SciTech Connect (OSTI)

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.

Federspiel, Clifford

2009-06-30T23:59:59.000Z

231

E-Print Network 3.0 - automated transportation management Sample...  

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

Plus Planet Strategic Partnerships Summary: Distribution & Substation Automation Demand Response MetersAMI MDMS Home Energy Management Building... , Enernoc, GE Johnson...

232

Commercial and Industrial Base Intermittent Resource Management Pilot  

E-Print Network [OSTI]

2:1002–1004. FERC. Demand Response and Advanced Metering.and Open Automated Demand Response in Wastewater Treatmentand Open Automated Demand Response in Refrigerated

Kiliccote, Sila

2011-01-01T23:59:59.000Z

233

TJ Automation | 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 revisionEnvReviewNonInvasiveExplorationUT-g GrantAtlas (PACAOpenSummersideJumpSyria: EnergyTEST UTILITYAutomation

234

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

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

Shen, Bo

2013-01-01T23:59:59.000Z

235

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

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

Shen, Bo

2013-01-01T23:59:59.000Z

236

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

237

Coordinating Automated Vehicles via Communication  

E-Print Network [OSTI]

1.1 Vehicle Automation . . . . . . . . . . . 1.1.1 Controlareas of technology in vehicle automation and communicationChapter 1 Introduction Vehicle Automation Automation is an

Bana, Soheila Vahdati

2001-01-01T23:59:59.000Z

238

Demand Response Valuation Frameworks Paper  

E-Print Network [OSTI]

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

Heffner, Grayson

2010-01-01T23:59:59.000Z

239

Strategies for Demand Response in Commercial Buildings  

SciTech Connect (OSTI)

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.

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

2006-06-20T23:59:59.000Z

240

Automation Status  

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:YearRound-Up fromDepartmentTie Ltd: Scope ChangeL-01-06 AuditAugust 5,Re evised June 2010 AutomNREL

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

E-Print Network 3.0 - automated mesh indexing Sample Search Results  

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

Summary: in the development of mesh generation algorithms 9, however, the process is still far from full automation 8... generation continues to be an open problem...

242

Demand Response Spinning Reserve Demonstration  

E-Print Network [OSTI]

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

2007-01-01T23:59:59.000Z

243

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

244

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...

245

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.

246

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

247

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network [OSTI]

05CH11231. References EPRI, Energy Audit Manual for Water/Research Institute, Energy Audit Manual for Water/Wastewater

Thompson, Lisa

2008-01-01T23:59:59.000Z

248

Role of Standard Demand Response Signals for Advanced Automated Aggregation  

E-Print Network [OSTI]

peak shaving, load shifting and following, spinning and non-the following actors; ISO/RTO, Distribution Company, LoadLoad State State Feedback Feedback Determine Current Operational State Figure 1: DR Business Process In general the process above involves the following

Kiliccote, Sila

2013-01-01T23:59:59.000Z

249

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network [OSTI]

applications. Mary Ann Piette is a Staff Scientist atResponse Ed Koch, Akuacom Mary Ann Piette, Lawrence BerkeleyCA 94903 ed@akuacom.com Mary Ann Piette Lawrence Berkeley

Piette, Mary Ann

2010-01-01T23:59:59.000Z

250

Field Testing of Automated Demand Response for Integration of Renewable  

E-Print Network [OSTI]

TCP/IP over CDMA CAISO Utility UC MERCED Solar Power System Thermal Energy Storage #12;EMS DRAS Client and Electric Company April 2012 #12;DISCLAIMER This document was prepared as an account

251

Honeywell Demonstrates Automated Demand Response Benefits for Utility,  

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

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) "ofEarly Career Scientists'Montana.ProgramJulietip sheetK-4In 2013 many|HumansDepartment ofLogo

252

Demand Management Institute (DMI) | 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 Home Page on Office of InspectorConcentrating Solar Power Basics (The following text09-0018-CXBasin JumpTexas Elec CoopInstitute

253

Transportation Demand Management (TDM) Encyclopedia | Open Energy  

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:FAQ < RAPID Jump to:Seadov Pty LtdSteen,LtdInformation Dixie ValleyLibrary <NAMATransport Topics Ask

254

Automated Microarray Image Analysis Toolbox for MATLAB  

SciTech Connect (OSTI)

The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

White, Amanda M.; Daly, Don S.; Willse, Alan R.; Protic, Miroslava; Chandler, Darrell P.

2005-09-01T23:59:59.000Z

255

Viability of Modern Automated Rapid Transit Applications  

E-Print Network [OSTI]

guideway: elevated, underground, at grade · Fully automated: electric-powered, electronic controls · Non · Headways/frequency: about 30 seconds/120 veh/hr · Small vehicles: 4-6 passengers, low weight · Eco: 4 km, 21 vehicles, two stations (parking and terminal) · Open to public service Spring 2011, 22

Minnesota, University of

256

Multiplex automated genome engineering  

DOE Patents [OSTI]

The present invention relates to automated methods of introducing multiple nucleic acid sequences into one or more target cells.

Church, George M; Wang, Harris H; Isaacs, Farren J

2013-10-29T23:59:59.000Z

257

An Automated, yet Interactive and Portable DB designer Ioannis Alagiannis1  

E-Print Network [OSTI]

SQL open source DBMS. The tool suggests design features for both offline and online workloads. It providesSQL and MySQL. Thus, one has to face the dilemma of selecting an expensive commercial DBMS that provides automating tools or an open source DBMS whose lack of automated tools might increase the operational cost

Polyzotis, Neoklis (Alkis)

258

Charmaine Toy Automation Engineer,  

E-Print Network [OSTI]

@me.berkeley.edu Nonstationary Velocity Profiles for Emergency Vehicles on Automated Highways This paper explores the notion and usefulness of nonstationary velocity profiles for high priority emergency vehicle transit on automatedCharmaine Toy Automation Engineer, DiCon Fiberoptics, Inc., Richmond, CA 94804 e-mail: charm

Horowitz, Roberto

259

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

260

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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.

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

262

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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.

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

263

Building Energy Management Open-Source Software Development ...  

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

be able to optimize electricity usage to reduce energy consumption and help implement demand response (DR). This opens up demand side ancillary services markets and creates...

264

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

265

Demand Response Valuation Frameworks Paper  

E-Print Network [OSTI]

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

Heffner, Grayson

2010-01-01T23:59:59.000Z

266

AiiDA: Automated Interactive Infrastructure and Database for Computational Science  

E-Print Network [OSTI]

Computational science has seen in the last decades a spectacular rise in the scope, breadth, and depth of its efforts. Notwithstanding this prevalence and impact, it is often still performed using the renaissance model of individual artisans gathered in a workshop, under the guidance of an established practitioner. Great benefits could follow instead from adopting concepts and tools coming from computer science to manage, preserve, and share these computational efforts. We illustrate here our paradigm sustaining such vision, based around the four pillars of Automation, Data, Environment, and Sharing, and discuss its implementation in the open-source AiiDA platform (http://www.aiida.net). The platform is tuned first to the demands of computational materials science: coupling remote management with automatic data generation; ensuring provenance, preservation, and searchability of heterogeneous data through a design based on directed acyclic graphs; encoding complex sequences of low-level codes into scientific w...

Pizzi, Giovanni; Sabatini, Riccardo; Marzari, Nicola; Kozinsky, Boris

2015-01-01T23:59:59.000Z

267

Joint Genome Institute's Automation Approach and History  

E-Print Network [OSTI]

Joint Genome Institute’s Automation Approach and Historythroughput environment; – automation does not necessarilyissues “Islands of Automation” – modular instruments with

Roberts, Simon

2006-01-01T23:59:59.000Z

268

On Demand Guarantees in Iran.  

E-Print Network [OSTI]

??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)

Ahvenainen, Laura

2009-01-01T23:59:59.000Z

269

Integration of Renewables Via Demand Management: Highly Dispatchable and Distributed Demand Response for the Integration of Distributed Generation  

SciTech Connect (OSTI)

GENI Project: AutoGrid, in conjunction with Lawrence Berkeley National Laboratory and Columbia University, will design and demonstrate automated control software that helps manage real-time demand for energy across the electric grid. Known as the Demand Response Optimization and Management System - Real-Time (DROMS-RT), the software will enable personalized price signal to be sent to millions of customers in extremely short timeframes—incentivizing them to alter their electricity use in response to grid conditions. This will help grid operators better manage unpredictable demand and supply fluctuations in short time-scales —making the power generation process more efficient and cost effective for both suppliers and consumers. DROMS-RT is expected to provide a 90% reduction in the cost of operating demand response and dynamic pricing Projects in the U.S.

None

2012-02-11T23:59:59.000Z

270

Energy Demand Staff Scientist  

E-Print Network [OSTI]

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

Eisen, Michael

271

Evaluation of Representative Smart Grid Investment Project Technologies: Demand Response  

SciTech Connect (OSTI)

This document is one of a series of reports estimating the benefits of deploying technologies similar to those implemented on the Smart Grid Investment Grant (SGIG) projects. Four technical reports cover the various types of technologies deployed in the SGIG projects, distribution automation, demand response, energy storage, and renewables integration. A fifth report in the series examines the benefits of deploying these technologies on a national level. This technical report examines the impacts of a limited number of demand response technologies and implementations deployed in the SGIG projects.

Fuller, Jason C.; Prakash Kumar, Nirupama; Bonebrake, Christopher A.

2012-02-14T23:59:59.000Z

272

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

273

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

274

Architectures of Test Automation 1 High Volume Test AutomationHigh Volume Test Automation  

E-Print Network [OSTI]

Architectures of Test Automation 1 High Volume Test AutomationHigh Volume Test Automation Cem Kaner Institute of Technology October 2003 #12;Architectures of Test Automation 2 Acknowledgements developed a course on test automation architecture, and in the Los Altos Workshops on Software Testing

275

Copyright (c) Cem Kaner, Automated Testing. 1 Software Test Automation:Software Test Automation  

E-Print Network [OSTI]

Copyright (c) Cem Kaner, Automated Testing. 1 Software Test Automation:Software Test Automation: A RealA Real--World ProblemWorld Problem Cem Kaner, Ph.D., J.D. #12;Copyright (c) Cem Kaner, Automated Testing. 2 This TalkThis Talk The most widely used class of automated testing tools leads senior software

276

High Volume Test Automation 1 High Volume Test AutomationHigh Volume Test Automation  

E-Print Network [OSTI]

High Volume Test Automation 1 High Volume Test AutomationHigh Volume Test Automation Keynote Automation 2 AcknowledgementsAcknowledgements · Many of the ideas in this presentation were initially jointly developed with Doug Hoffman,as we developed a course on test automation architecture, and in the Los Altos

277

Findings from Seven Years of Field Performance Data for Automated  

E-Print Network [OSTI]

in Commercial Buildings S. Kiliccote, M.A. Piette, J. Mathieu, K. Parrish Environmental Energy Technologies;1 Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings. It provides a summary of participation, DR strategies and incentives. Commercial buildings can reduce peak

278

Analysis of Residential Demand Response and Double-Auction Markets  

SciTech Connect (OSTI)

Demand response and dynamic pricing programs are expected to play increasing roles in the modern Smart Grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demand response programs at the residential level. With the combination of automated bidding and response strategies coupled with education programs and customer response, emerging demand response programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system.

Fuller, Jason C.; Schneider, Kevin P.; Chassin, David P.

2011-10-10T23:59:59.000Z

279

A Verified Hybrid Controller For Automated Vehicles  

E-Print Network [OSTI]

con- trollers for vehicle automation," in American ControlTomizuka, Vehicle lateral control for highway automation,"

Lygeros, J.; Godbole, D. N.; Sastry, S.

1997-01-01T23:59:59.000Z

280

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

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

Shen, Bo

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Automated distribution scheme speeds service restoration  

SciTech Connect (OSTI)

This article describes an automated distribution scheme that met Lakeland Electric requirements for an automated scheme that would restore power to a major customer in less than 60 seconds. In January 1993, Lakeland Electric and Water (LEW) took on the design and construction of a new 12.47-kV automated distribution system for the Publix Supermarket Industrial complex. The industrial complex in Lakeland, Florida, totals 2 million square feet and houses a dairy processing plant, bakery, produce plant, deli plant, data processing facility for Publix`s entire retail network, purchasing department, as well as several maintenance facilities. The retail chain is LEW`s largest customer with a peak demand of 15.5 MW and a load factor of 81%. Publix`s rapid expansion plan has placed a great deal of pressure on this facility to perform at peak level with no interruptions of product flow. The task at hand was to provide Publix with a state-of-the-art, automated, distribution system built to withstand the inherent weather-related situations in central Florida, lightning and hurricanes.

Atwell, E. [Lakeland Electric and Water, FL (United States)] [Lakeland Electric and Water, FL (United States); Gamvrelis, T. [Harris Canada, Inc., Calgary, Alberta (Canada). Control Div.] [Harris Canada, Inc., Calgary, Alberta (Canada). Control Div.; Kearns, D. [S and C Electric Co., Chicago, IL (United States)] [S and C Electric Co., Chicago, IL (United States); Landman, R. [H and L Instruments, North Hampton, NH (United States)] [H and L Instruments, North Hampton, NH (United States)

1996-01-01T23:59:59.000Z

282

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

283

Customer focused collaborative demand planning  

E-Print Network [OSTI]

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 ...

Jha, Ratan (Ratan Mohan)

2008-01-01T23:59:59.000Z

284

Demand Response: Load Management Programs  

E-Print Network [OSTI]

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...

Simon, J.

2012-01-01T23:59:59.000Z

285

TRAVEL DEMAND AND RELIABLE FORECASTS  

E-Print Network [OSTI]

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

Minnesota, University of

286

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

287

Demand Forecasting of New Products  

E-Print Network [OSTI]

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

Sun, Yu

288

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

289

Scoping Study for Demand Respose DFT II Project in Morgantown, WV  

SciTech Connect (OSTI)

This scoping study describes the underlying data resources and an analysis tool for a demand response assessment specifically tailored toward the needs of the Modern Grid Initiatives Demonstration Field Test in Phase II in Morgantown, WV. To develop demand response strategies as part of more general distribution automation, automated islanding and feeder reconfiguration schemes, an assessment of the demand response resource potential is required. This report provides the data for the resource assessment for residential customers and describes a tool that allows the analyst to estimate demand response in kW for each hour of the day, by end-use, season, day type (weekday versus weekend) with specific saturation rates of residential appliances valid for the Morgantown, WV area.

Lu, Shuai; Kintner-Meyer, Michael CW

2008-06-06T23:59:59.000Z

290

RF test bench automation Description  

E-Print Network [OSTI]

RF test bench automation Description: Callisto would like to implement automated RF test bench. Three RF test benches have to be studied and automated: LNA noise temperature test bench LNA gain phase of the test benches and an implementation of the automation phase. Tasks: Noise temperature

Dobigeon, Nicolas

291

Cognitive Engineering Automation and Human  

E-Print Network [OSTI]

· Home automation · Robotics · Unmanned vehicles (UAVs and UGVs) · Drug design/Molecular geneticsCognitive Engineering PSYC 530 Automation and Human Performance Raja Parasuraman #12;Overview Automation-Related Accidents Levels and Stages of Automation Information Acquisition and Analysis Decision

Parasuraman, Raja

292

ON-DEMAND SERIAL DILUTION USING QUANTIZED NANO/PICOLITER-SCALE DROPLETS  

SciTech Connect (OSTI)

This paper describes a fully automated droplet-based microfluidic device for on-demand serial dilution that is capable of achieving a dilution ratio of >6000 (concentration ranges from 1 mM to 160nM) over 35 nanoliter-scale droplets. This serial diluter can be applied to high throughput and label-free kinetic assays by integrating with our previously developed on-demand droplet-based microfluidic with mass spectrometry detection.

Jambovane, Sachin R.; Prost, Spencer A.; Sheen, Allison M.; Magnuson, Jon K.; Kelly, Ryan T.

2014-10-29T23:59:59.000Z

293

Automated Systematic Testing of Open Distributed Programs  

E-Print Network [OSTI]

to alternate behaviors. At the same time, we use the concrete execution to determine, at runtime, the partial behaviors. At the same time, we use the concrete execution to guide the symbolic execution along a distinct, to explore all distinct behaviors that may result from a program's execution given different data inputs

Sen, Koushik

294

Automated Systematic Testing of Open Distributed Programs  

E-Print Network [OSTI]

. At the same time, we use the concrete execution to determine, at runtime, the partial order of events. At the same time, we use the concrete execution to guide the symbolic execution along a distinct execution behaviors that may result from a program's execution given different data inputs and schedules. The key idea

Sen, Koushik

295

Automation Alley Technology Center | 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 NoPublic Utilities Address: 160 EastMaine: EnergyAustin Energy Place: Texas Service Territory:andAutodesk Jump

296

Mirle Automation Corporation | 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: EnergyMinnErgy LLCMinwindPower PlantPowerMirle

297

Solar Automation Inc | 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:FAQ < RAPID Jump to:Seadov Pty Ltd Jump to:Information Silver Peak Area (Henkle, EtSolapur BioInc Place:

298

home automation | OpenEI Community  

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 Home Page on Office of InspectorConcentrating SolarElectric Coop,SaveWhiskey Flats GeothermalElectricsecretaryguidanceheathome

299

OpenEI Community - home automation  

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 hasInformation Earth'sOklahoma/Geothermal < Oklahomast, 2012Coastfred <divmeasureshas

300

Energy Automation Systems Inc | 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 NoPublic Utilities Address:011-DNA Jump37. It is classifiedProject)EnerVault CorporationSolaireEnergreen

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Automated Lattice Perturbation Theory  

SciTech Connect (OSTI)

I review recent developments in automated lattice perturbation theory. Starting with an overview of lattice perturbation theory, I focus on the three automation packages currently "on the market": HiPPy/HPsrc, Pastor and PhySyCAl. I highlight some recent applications of these methods, particularly in B physics. In the final section I briefly discuss the related, but distinct, approach of numerical stochastic perturbation theory.

Monahan, Christopher

2014-11-01T23:59:59.000Z

302

Demonstration of Automated Heavy-Duty Vehicles  

E-Print Network [OSTI]

a future in which vehicle automation technologies are ableto support the heavy vehicle automation including PrecisionCommittee on Vehicle-Highway Automation, and the attendees

2006-01-01T23:59:59.000Z

303

Development of Building Automation and Control Systems  

E-Print Network [OSTI]

A design flow for building automation and control systems,’’Development of Building Automation and Control Systems Yangdesign of the build- ing automation system (including the

Yang, Yang; Zhu, Qi; Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

2012-01-01T23:59:59.000Z

304

Demand Response Programs, 6. edition  

SciTech Connect (OSTI)

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.

NONE

2007-10-15T23:59:59.000Z

305

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

306

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

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

Levy, Roger

2014-01-01T23:59:59.000Z

307

Retail Demand Response in Southwest Power Pool  

E-Print Network [OSTI]

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

308

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

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

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

309

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

310

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

311

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

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

Levy, Roger

2014-01-01T23:59:59.000Z

312

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

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

Levy, Roger

2014-01-01T23:59:59.000Z

313

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

314

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

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

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

315

Strategies for Demand Response in Commercial Buildings  

E-Print Network [OSTI]

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

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

2006-01-01T23:59:59.000Z

316

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

317

China's Coal: Demand, Constraints, and Externalities  

E-Print Network [OSTI]

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

Aden, Nathaniel

2010-01-01T23:59:59.000Z

318

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

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

Shen, Bo

2013-01-01T23:59:59.000Z

319

Assessing the Control Systems Capacity for Demand Response in California Industries  

SciTech Connect (OSTI)

California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This,study identifies sectors that have the technical capability to implement Demand Response (DR) and Automated Demand Response (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors Demand Response efforts should be focused. Analysis of the survey responses showed that while the vast majority of industrial facilities have semi- or fully automated control systems, participation in Demand Response programs is still low due to perceived barriers. The results also showed that the facilities that use continuous processes are good Demand Response candidates. When comparing facilities participating in Demand Response to those not participating, several similarities and differences emerged. Demand Response-participating facilities and non-participating facilities had similar timings of peak energy use, production processes, and participation in energy audits. Though the survey sample was smaller than anticipated, the results seemed to support our preliminary assumptions. Demonstrations of Auto-Demand Response in industrial facilities with good control capabilities are needed to dispel perceived barriers to participation and to investigate industrial subsectors suggested of having inherent Demand Response potential.

Ghatikar, Girish; McKane, Aimee; Goli, Sasank; Therkelsen, Peter; Olsen, Daniel

2012-01-18T23:59:59.000Z

320

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...

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

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...

322

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...

323

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...

324

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

SciTech Connect (OSTI)

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.

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

2009-06-28T23:59:59.000Z

325

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

326

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

327

Enhanced training effectiveness using automated student assessment.  

SciTech Connect (OSTI)

Training simulators have become increasingly popular tools for instructing humans on performance in complex environments. However, the question of how to provide individualized and scenario-specific assessment and feedback to students remains largely an open question. In this work, we follow-up on previous evaluations of the Automated Expert Modeling and Automated Student Evaluation (AEMASE) system, which automatically assesses student performance based on observed examples of good and bad performance in a given domain. The current study provides an empirical evaluation of the enhanced training effectiveness achievable with this technology. In particular, we found that students given feedback via the AEMASE-based debrief tool performed significantly better than students given only instructor feedback.

Forsythe, James Chris

2010-05-01T23:59:59.000Z

328

General approach to automation of FLASH subsystems  

E-Print Network [OSTI]

General approach to automation of FLASH subsystems Boguslaw Kosda #12;Agenda Motivation Nature of automation software for high energy experiments. Ultimate role of the automation software: Maximization of lasers availability. Automation of routine activities as startup, shutdown ... Continuous monitoring

329

Retail Demand Response in Southwest Power Pool  

E-Print Network [OSTI]

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

330

Design Automation Challenges in Automotive CPS Sayan Mitra  

E-Print Network [OSTI]

Design Automation Challenges in Automotive CPS Sayan Mitra mitras@illinois.edu In principle, best theorem proving. Unfortunately, a stan- dardized open repository of benchmarks for automotive CPS-up companies, in which each play a role and the automotive CPS community flourishes. A good benchmark

Rajkumar, Ragunathan "Raj"

331

China, India demand cushions prices  

SciTech Connect (OSTI)

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.

Boyle, M.

2006-11-15T23:59:59.000Z

332

Harnessing the power of demand  

SciTech Connect (OSTI)

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)

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

2008-03-15T23:59:59.000Z

333

Demand Response for Ancillary Services  

SciTech Connect (OSTI)

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.

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

2013-01-01T23:59:59.000Z

334

Solid Edge ActiveXSolid Edge ActiveX AutomationAutomation  

E-Print Network [OSTI]

;Solid Edge ActiveX AutomationSolid Edge ActiveX Automation How ActiveX Automation works?How ActiveX Automation works? In Solid Edge, every document, every part, and every feature ofIn Solid Edge, everySolid Edge ActiveXSolid Edge ActiveX AutomationAutomation Creating Automation Client Using

Krovi, Venkat

335

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

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-

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

336

Automated Microbial Genome Annotation  

SciTech Connect (OSTI)

Miriam Land of the DOE Joint Genome Institute at Oak Ridge National Laboratory gives a talk on the current state and future challenges of moving toward automated microbial genome annotation at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM

Land, Miriam [DOE Joint Genome Institute at Oak Ridge National Laboratory

2009-05-29T23:59:59.000Z

337

Office Automation Document Preparation  

E-Print Network [OSTI]

.2 Distinctions 1.3 Facilities 1.3.1 Document Preparation 1.3.2 Records Management 1.3.3 Communication 1 organizations contemplating the installation of document-preparation systems. * Administrative managersOffice Automation and Document Preparation for the v' University of North Carolina at Chapel Hill

North Carolina at Chapel Hill, University of

338

Full Rank Rational Demand Systems  

E-Print Network [OSTI]

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 (

LaFrance, Jeffrey T; Pope, Rulon D.

2006-01-01T23:59:59.000Z

339

Marketing Demand-Side Management  

E-Print Network [OSTI]

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...

O'Neill, M. L.

1988-01-01T23:59:59.000Z

340

Community Water Demand in Texas  

E-Print Network [OSTI]

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...

Griffin, Ronald C.; Chang, Chan

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Demand Response Spinning Reserve Demonstration  

SciTech Connect (OSTI)

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.

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

342

Falling MTBE demand bursts the methanol bubble  

SciTech Connect (OSTI)

Methanol spot markets in Europe and the US have been hit hard by weakening demand from methyl tert-butyl ether (MTBE) producers. In Europe, spot prices for domestic T2 product have dropped to DM620-DM630/m.t. fob from early-January prices above DM800/m.t. and US spot prices have slipped to $1.05/gal fob from $1.35/gal. While chemical applications for methanol show sustained demand, sharp methanol hikes during 1994 have priced MTBE out of the gasoline-additive market. {open_quotes}We`ve learned an important lesson. We killed [MTBE] applications in the rest of the world,{close_quotes} says one European methanol producer. Even with methanol currently at DM620/m.t., another manufacturer points out, MTBE production costs still total $300/m.t., $30/m.t. more than MTBE spot prices. Since late 1994, Europe`s 3.3-million m.t./year MTBE production has been cut back 30%.

Wiesmann, G.; Cornitius, T.

1995-03-01T23:59:59.000Z

343

Automated gas chromatography  

DOE Patents [OSTI]

An apparatus and process for the continuous, near real-time monitoring of low-level concentrations of organic compounds in a liquid, and, more particularly, a water stream. A small liquid volume of flow from a liquid process stream containing organic compounds is diverted by an automated process to a heated vaporization capillary where the liquid volume is vaporized to a gas that flows to an automated gas chromatograph separation column to chromatographically separate the organic compounds. Organic compounds are detected and the information transmitted to a control system for use in process control. Concentrations of organic compounds less than one part per million are detected in less than one minute. 7 figs.

Mowry, C.D.; Blair, D.S.; Rodacy, P.J.; Reber, S.D.

1999-07-13T23:59:59.000Z

344

Demand Response as a System Reliability Resource  

E-Print Network [OSTI]

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

Joseph, Eto

2014-01-01T23:59:59.000Z

345

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

346

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

347

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

348

Automated Job Hazards Analysis  

Broader source: Energy.gov [DOE]

AJHA Program - The Automated Job Hazard Analysis (AJHA) computer program is part of an enhanced work planning process employed at the Department of Energy's Hanford worksite. The AJHA system is routinely used to performed evaluations for medium and high risk work, and in the development of corrective maintenance work packages at the site. The tool is designed to ensure that workers are fully involved in identifying the hazards, requirements, and controls associated with tasks.

349

Methodology for Prototyping Increased Levels of Automation  

E-Print Network [OSTI]

of automation than previous NASA vehicles, due to program requirements for automation, including Automated Ren into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool levels of automation than previous NASA vehicles. A key technology to the success of the CEV

Valasek, John

350

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

351

Supply chain planning decisions under demand uncertainty  

E-Print Network [OSTI]

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 ...

Huang, Yanfeng Anna

2008-01-01T23:59:59.000Z

352

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

353

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

354

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

355

Demand Response as a System Reliability Resource  

E-Print Network [OSTI]

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

Joseph, Eto

2014-01-01T23:59:59.000Z

356

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

357

International Oil Supplies and Demands  

SciTech Connect (OSTI)

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.

Not Available

1991-09-01T23:59:59.000Z

358

Turkey's energy demand and supply  

SciTech Connect (OSTI)

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.

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

2009-07-01T23:59:59.000Z

359

International Oil Supplies and Demands  

SciTech Connect (OSTI)

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.

Not Available

1992-04-01T23:59:59.000Z

360

MTBE: Capacity boosts on hold amid demand concerns  

SciTech Connect (OSTI)

Uncertainty reigns in the methyl tert-butyl ether (MTBE) market. {open_quotes}We have no choice but to put our expansion plans on the back burner,{close_quotes} says one producer. {open_quotes}Because of government actions, there are no MTBE plants being built or expanded.{close_quotes} Spot MTBE prices have risen ti 82 cts- 83 cts/gal from 76 cts-78 cts/gal earlier this month as the demand for octane enhancement increases for the summer driving season. Some observers say EPA may relax different oxygen requirements for gasoline in different seasons. That would simplify production and supply for MTBE makers.

NONE

1995-05-03T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

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

362

Chilled Water Thermal Storage System and Demand Response at the University of California at Merced  

SciTech Connect (OSTI)

The University of California at Merced is a unique campus that has benefited from intensive efforts to maximize energy efficiency, and has participated in a demand response program for the past two years. Campus demand response evaluations are often difficult because of the complexities introduced by central heating and cooling, non-coincident and diverse building loads, and existence of a single electrical meter for the entire campus. At the University of California at Merced, a two million gallon chilled water storage system is charged daily during off-peak price periods and used to flatten the load profile during peak demand periods. This makes demand response more subtle and challenges typical evaluation protocols. The goal of this research is to study demand response savings in the presence of storage systems in a campus setting. First, University of California at Merced summer electric loads are characterized; second, its participation in two demand response events is detailed. In each event a set of strategies were pre-programmed into the campus control system to enable semi-automated response. Finally, demand savings results are applied to the utility's DR incentives structure to calculate the financial savings under various DR programs and tariffs. A key conclusion to this research is that there is significant demand reduction using a zone temperature set point change event with the full off peak storage cooling in use.

Granderson, Jessica; Dudley, Junqiao Han; Kiliccote, Sila; Piette, Mary Ann

2009-10-08T23:59:59.000Z

363

Virtual Machine in Automation Projects.  

E-Print Network [OSTI]

?? Virtual machine, as an engineering tool, has recently been introduced into automation projects in Tetra Pak Processing System AB. The goal of this paper… (more)

Xing, Xiaoyuan

2010-01-01T23:59:59.000Z

364

Valliappa Lakshmanan Automating the Analysis of  

E-Print Network [OSTI]

Geospatial Images January 5, 2012 Springer #12;Contents 1 Automated Analysis of Spatial Grids: MotivationValliappa Lakshmanan Automating the Analysis of Spatial Grids A Practitioner's Guide to Data Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.5 Challenges in Automated Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1

Lakshmanan, Valliappa

365

automation: Topics by E-print Network  

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

Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

366

Integrated, Automated Distributed Generation Technologies Demonstration  

SciTech Connect (OSTI)

The purpose of the NETL Project was to develop a diverse combination of distributed renewable generation technologies and controls and demonstrate how the renewable generation could help manage substation peak demand at the ATK Promontory plant site. The Promontory plant site is located in the northwestern Utah desert approximately 25 miles west of Brigham City, Utah. The plant encompasses 20,000 acres and has over 500 buildings. The ATK Promontory plant primarily manufactures solid propellant rocket motors for both commercial and government launch systems. The original project objectives focused on distributed generation; a 100 kW (kilowatt) wind turbine, a 100 kW new technology waste heat generation unit, a 500 kW energy storage system, and an intelligent system-wide automation system to monitor and control the renewable energy devices then release the stored energy during the peak demand time. The original goal was to reduce peak demand from the electrical utility company, Rocky Mountain Power (RMP), by 3.4%. For a period of time we also sought to integrate our energy storage requirements with a flywheel storage system (500 kW) proposed for the Promontory/RMP Substation. Ultimately the flywheel storage system could not meet our project timetable, so the storage requirement was switched to a battery storage system (300 kW.) A secondary objective was to design/install a bi-directional customer/utility gateway application for real-time visibility and communications between RMP, and ATK. This objective was not achieved because of technical issues with RMP, ATK Information Technology Department’s stringent requirements based on being a rocket motor manufacturing facility, and budget constraints. Of the original objectives, the following were achieved: • Installation of a 100 kW wind turbine. • Installation of a 300 kW battery storage system. • Integrated control system installed to offset electrical demand by releasing stored energy from renewable sources during peak hours of the day. Control system also monitors the wind turbine and battery storage system health, power output, and issues critical alarms. Of the original objectives, the following were not achieved: • 100 kW new technology waste heat generation unit. • Bi-directional customer/utility gateway for real time visibility and communications between RMP and ATK. • 3.4% reduction in peak demand. 1.7% reduction in peak demand was realized instead.

Jensen, Kevin

2014-09-30T23:59:59.000Z

367

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

368

Projecting Electricity Demand in 2050  

SciTech Connect (OSTI)

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.

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

2014-07-01T23:59:59.000Z

369

Water demand management in Kuwait  

E-Print Network [OSTI]

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 ...

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

2006-01-01T23:59:59.000Z

370

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect (OSTI)

With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

Sparn, B.; Jin, X.; Earle, L.

2013-10-01T23:59:59.000Z

371

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network [OSTI]

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

McKane, Aimee T.

2009-01-01T23:59:59.000Z

372

INTEGRATION OF PV IN DEMAND RESPONSE  

E-Print Network [OSTI]

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

Perez, Richard R.

373

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

374

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

375

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

376

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

377

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

378

Assessment of Demand Response and Advanced Metering  

E-Print Network [OSTI]

#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

Tesfatsion, Leigh

379

Automated fiber pigtailing machine  

DOE Patents [OSTI]

The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectronic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems. 26 figs.

Strand, O.T.; Lowry, M.E.

1999-01-05T23:59:59.000Z

380

Methods for Multisweep Automation  

SciTech Connect (OSTI)

Sweeping has become the workhorse algorithm for creating conforming hexahedral meshes of complex models. This paper describes progress on the automatic, robust generation of MultiSwept meshes in CUBIT. MultiSweeping extends the class of volumes that may be swept to include those with multiple source and multiple target surfaces. While not yet perfect, CUBIT's MultiSweeping has recently become more reliable, and been extended to assemblies of volumes. Sweep Forging automates the process of making a volume (multi) sweepable: Sweep Verification takes the given source and target surfaces, and automatically classifies curve and vertex types so that sweep layers are well formed and progress from sources to targets.

SHEPHERD,JASON F.; MITCHELL,SCOTT A.; KNUPP,PATRICK; WHITE,DAVID R.

2000-09-14T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Automated fiber pigtailing machine  

DOE Patents [OSTI]

The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectonic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems.

Strand, Oliver T. (Castro Valley, CA); Lowry, Mark E. (Castro Valley, CA)

1999-01-01T23:59:59.000Z

382

The alchemy of demand response: turning demand into supply  

SciTech Connect (OSTI)

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)

Rochlin, Cliff

2009-11-15T23:59:59.000Z

383

Global energy demand to 2060  

SciTech Connect (OSTI)

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.

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

1989-01-01T23:59:59.000Z

384

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

E-Print Network [OSTI]

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

Boutaba, Raouf

385

Robust automated knowledge capture.  

SciTech Connect (OSTI)

This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

2011-10-01T23:59:59.000Z

386

Communication in automation, including networking and wireless  

E-Print Network [OSTI]

Communication in automation, including networking and wireless Nicholas Kottenstette and Panos J and networking in automation is given. Digital communication fundamentals are reviewed and networked control are presented. 1 Introduction 1.1 Why communication is necessary in automated systems Automated systems use

Antsaklis, Panos

387

ABV-A Low Speed Automation Project to Study the Technical Feasibility of Fully Automated Driving  

E-Print Network [OSTI]

on vehicle automation since many years. From 1987 to 1995 the European Commission funded the 800 million concepts of vehicles designed as fully automated vehicles [1]. Beyond its fully automation ability Automated Highway System Consortium (NAHSC) that demonstrated about 20 automated vehicles in Demo'97 on I-15

Paris-Sud XI, Université de

388

Towards Automated Service Composition using Policy Ontology in Building Automation System  

E-Print Network [OSTI]

Towards Automated Service Composition using Policy Ontology in Building Automation System Son N.crespi}@it-sudparis.eu Abstract--Automated service composition is critical for suc- cessfully implementing Building Automation-service composition; semantic web; policy; ontol- ogy; building automation system; I. INTRODUCTION In building

Paris-Sud XI, Université de

389

Assisting Mexico in Developing Energy Supply and Demand Projections | Open  

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 Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWendeGuo Feng Bio EnergyInstituteFunding Jump to:

390

Network-Driven Demand Side Management Website | 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 hasInformation Earth's HeatMexico: EnergyMithunCenter Jump to:2 Rules,NellisAntilles:

391

ranking of utilities by demand charge? | OpenEI Community  

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 NoPublic Utilities Address: 160 East 300 South Place:ReferenceEditWisconsin:YBR SolarZe-geniot Home Noranking of

392

Property:DemandRateStructure | 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 hasInformationInyoCoolingTowerWaterUseSummerConsumed Jump to:DOEInvolve Jump to:DtAddDefinition

393

Property:FlatDemandStructure | 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 revisionEnvReviewNonInvasiveExploration Jump to:FieldProcedures Jump to:FirstWellTemp Jump to: navigation,

394

Estimating Demand Response Market Potential | 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,Law and PolicyEssex County is a county

395

Demand charge schedule data | OpenEI Community  

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 Home Page on Office of InspectorConcentrating Solar Power Basics (The following text09-0018-CXBasin JumpTexas Elec

396

Demand response medium sized industry consumers (Smart Grid Project) | Open  

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 Home Page on Office of InspectorConcentrating Solar Power Basics (The following text09-0018-CXBasin JumpTexas ElecEnergy

397

Hydrogen Demand and Resource Assessment Tool | 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: navigation,Ohio:GreerHiCalifornia: Energy ResourcesPark,isHydro orHydroelectricA)

398

EnergySolve Demand Response | 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 NoPublic Utilities Address:011-DNA Jump37. It isInformation Contracts (ESPC) WebinarEnergyConnectEnergySolve

399

Real-time Pricing Demand Response in Operations  

SciTech Connect (OSTI)

Abstract—Dynamic pricing schemes have been implemented in commercial and industrial application settings, and recently they are getting attention for application to residential customers. Time-of-use and critical-peak-pricing rates are in place in various regions and are being piloted in many more. These programs are proving themselves useful for balancing energy during peak periods; however, real-time (5 minute) pricing signals combined with automation in end-use systems have the potential to deliver even more benefits to operators and consumers. Besides system peak shaving, a real-time pricing system can contribute demand response based on the locational marginal price of electricity, reduce load in response to a generator outage, and respond to local distribution system capacity limiting situations. The US Department of Energy (DOE) is teaming with a mid-west electricity service provider to run a distribution feeder-based retail electricity market that negotiates with residential automation equipment and clears every 5 minutes, thus providing a signal for lowering or raising electric consumption based on operational objectives of economic efficiency and reliability. This paper outlines the capability of the real-time pricing system and the operational scenarios being tested as the system is rolled-out starting in the first half of 2012.

Widergren, Steven E.; Marinovici, Maria C.; Berliner, Teri; Graves, Alan

2012-07-26T23:59:59.000Z

400

Fuse Control for Demand Side Management: A Stochastic Pricing Analysis  

E-Print Network [OSTI]

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

Oren, Shmuel S.

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Demand Response Providing Ancillary Services  

E-Print Network [OSTI]

Wholesale Markets Presentation by Jason MacDonald Grid Integration Group, Lawrence Berkeley National;Contents · Introduction ­ Wholesale Markets and AS ­ Why DR for AS? ­ Market Clearing Price · Value/RTOs · ISO/RTOs are balancing authorities that run open wholesale markets for both energy and Ancillary

402

Industrial Equipment Demand and Duty Factors  

E-Print Network [OSTI]

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...

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

403

Automated Assembly Using Feature Localization  

E-Print Network [OSTI]

Automated assembly of mechanical devices is studies by researching methods of operating assembly equipment in a variable manner; that is, systems which may be configured to perform many different assembly operations ...

Gordon, Steven Jeffrey

1986-12-01T23:59:59.000Z

404

Aspects of automation mode confusion  

E-Print Network [OSTI]

Complex systems such as commercial aircraft are difficult for operators to manage. Designers, intending to simplify the interface between the operator and the system, have introduced automation to assist the operator. In ...

Wheeler, Paul H. (Paul Harrison)

2007-01-01T23:59:59.000Z

405

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...

406

Wireless Demand Response Controls for HVAC Systems  

E-Print Network [OSTI]

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

Federspiel, Clifford

2010-01-01T23:59:59.000Z

407

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

408

Aggregate Model for Heterogeneous Thermostatically Controlled Loads with Demand Response  

SciTech Connect (OSTI)

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.

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

2012-07-22T23:59:59.000Z

409

Automation of Termination: Abstracting CCG through MWG Automation of Termination: Abstracting Calling  

E-Print Network [OSTI]

Automation of Termination: Abstracting CCG through MWG Automation of Termination: Abstracting of Termination: Abstracting CCG through MWG Motivation Termination analysis is a fundamental topic in computer science. While classical results state the undecidability of various termination problems, automated

Ayala-Rincón, Mauricio

410

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

411

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

412

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

413

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

414

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

415

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

416

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

417

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

418

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

419

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

420

Modeling Energy Demand Aggregators for Residential Consumers  

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Transportation Energy: Supply, Demand and the Future  

E-Print Network [OSTI]

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

Saldin, Dilano

422

Demand Side Bidding. Final Report  

SciTech Connect (OSTI)

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.

Spahn, Andrew

2003-12-31T23:59:59.000Z

423

Demand Response Valuation Frameworks Paper  

SciTech Connect (OSTI)

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.

Heffner, Grayson

2009-02-01T23:59:59.000Z

424

Open Access: From Myth to Paradox  

ScienceCinema (OSTI)

True open access to scientific publications not only gives readers the possibility to read articles without paying subscription, but also makes the material available for automated ingestion and harvesting by 3rd parties. Once articles and associated data become universally treatable as computable objects, openly available to 3rd party aggregators and value-added services, what new services can we expect, and how will they change the way that researchers interact with their scholarly communications infrastructure? I will discuss straightforward applications of existing ideas and services, including citation analysis, collaborative filtering, external database linkages, interoperability, and other forms of automated markup, and speculate on the sociology of the next generation of users.

Paul Ginsparg

2010-01-08T23:59:59.000Z

425

Energy demand and population changes  

SciTech Connect (OSTI)

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.

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

1980-12-01T23:59:59.000Z

426

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

E-Print Network [OSTI]

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

Li, Baochun

427

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

E-Print Network [OSTI]

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

Sastry, S. Shankar

428

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

429

Rates and technologies for mass-market demand response  

E-Print Network [OSTI]

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

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

2002-01-01T23:59:59.000Z

430

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network [OSTI]

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

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

431

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

E-Print Network [OSTI]

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

Cappers, Peter

2009-01-01T23:59:59.000Z

432

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network [OSTI]

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

McKane, Aimee T.

2009-01-01T23:59:59.000Z

433

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

434

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network [OSTI]

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

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

435

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network [OSTI]

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

Kiliccote, Sila

2014-01-01T23:59:59.000Z

436

Using Temporal Information in an Automated Classification of Summer, Marginal Ice Zone Imagery*  

E-Print Network [OSTI]

Using Temporal Information in an Automated Classification of Summer, Marginal Ice Zone Imagery, even with the human eye. BackScatter instability causu the intensities of the fiistyear ice, multiyear ice, and open water classes to intermix, thus making an intensity-based classification invalid

Kansas, University of

437

Automation in image cytometry : continuous HCS and kinetic image cytometry  

E-Print Network [OSTI]

OF CALIFORNIA, SAN DIEGO Automation in Image Cytometry:xiv Abstract of Dissertation Automation in Image Cytometry:

Charlot, David J.

2012-01-01T23:59:59.000Z

438

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

regulation and load following are even more important (Etoscheduling and dispatch, load following, system protection,of wind: Regulation, Load Following, Reactive Supply and

Watson, David S.

2013-01-01T23:59:59.000Z

439

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

renewables such as wind and solar power are intermittent andShort- Term Power Fluctuation of Wind Turbines:Analyzing

Watson, David S.

2013-01-01T23:59:59.000Z

440

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

white wine production instead of the more energy intensiveand dairy and wine processors. The energy loads in these

Lekov, Alex

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

for defrosting/compressor cooling or in frigid climates withthermosiphon compressor cooling, premium-efficiency motors,

Lekov, Alex

2009-01-01T23:59:59.000Z

442

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

LBNL. Integrating Renewable Resources in California and thethe Integration of Renewable Resources David S. Watson,the Integration of Renewable Resources. California Energy

Watson, David S.

2013-01-01T23:59:59.000Z

443

Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings  

E-Print Network [OSTI]

following participants, vendors and the reviewers:  Paul sites, enabled by eight vendors, participated in at least technologies provided by vendors can receive and translate 

Page, Janie

2012-01-01T23:59:59.000Z

444

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

Molander, Samuel Golding, Kevin Sullivan, Walt Johnson,Molander, Samuel Golding, Kevin Sullivan, Walt Johnson,

Watson, David S.

2013-01-01T23:59:59.000Z

445

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

costs of grid scale battery storage. However, AutoDR inthermal generation and battery storage technologies, anturbines is grid scale battery storage. However, storage is

Watson, David S.

2013-01-01T23:59:59.000Z

446

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

and interior lighting electricity consumption by building orstatewide hourly electricity consumption estimates forof refrigeration electricity consumption between cold (32-55

Watson, David S.

2013-01-01T23:59:59.000Z

447

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

Piette, LBNL. Integrating Renewable Resources in Californiaprocurement from eligible renewable energy resources to 33%to Enable the Integration of Renewable Resources David S.

Watson, David S.

2013-01-01T23:59:59.000Z

448

Automated Demand Response: The Missing Link in the Electricity Value Chain  

E-Print Network [OSTI]

set-points or pre-cooling cold storage areas and over-warehouse can include cold storage space pre-cooling,off equipment, increasing cold storage area temperature set

McKane, Aimee

2010-01-01T23:59:59.000Z

449

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

Saving Strategies for Cold Storage Facilities." Process-Refrigeration Systems for Cold Storage. Pacific Gas andDR Strategies for Cold Storage - Barriers to Implementation.

Lekov, Alex

2009-01-01T23:59:59.000Z

450

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network [OSTI]

Refrigerated Warehouse – Cold Storage** UnrefrigeratedStorage Refrigerated Warehouse – Cold Storage Unrefrigeratedavailability varies for cold storage (32-55°F) vs. frozen

Watson, David S.

2013-01-01T23:59:59.000Z

451

Automated Demand Response: The Missing Link in the Electricity Value Chain  

E-Print Network [OSTI]

Missing Link in the Electricity Value Chain Aimee McKane,Missing Link in the Electricity Value Chain Aimee McKane,grid reliability and lower electricity use during periods of

McKane, Aimee

2010-01-01T23:59:59.000Z

452

Automated Demand Response: The Missing Link in the Electricity Value Chain  

E-Print Network [OSTI]

Missing Link in the Electricity Value Chain Aimee McKane*,Missing Link in the Electricity Value Chain Aimee McKane,grid reliability and lower electricity use during periods of

McKane, Aimee

2010-01-01T23:59:59.000Z

453

Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings  

E-Print Network [OSTI]

With the roll out of smart meters to this customer group, data collection.   Smart Meters provided data at  fifteen?

Page, Janie

2012-01-01T23:59:59.000Z

454

Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings  

E-Print Network [OSTI]

Sebastopol  .. temperature at the Sebastopol site . Rosa Convenience store Sebastopol Restaurant Novato Small

Page, Janie

2012-01-01T23:59:59.000Z

455

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network [OSTI]

Best Practices Guide. Walla Walla, WA, Cascade Energy Engineering, Inc. , Northwest Energy EfficiencyBest Practices Guide. Walla Walla, WA, Cascade Energy Engineering, Inc. , Northwest Energy EfficiencyBest Practices Guide. Walla Walla, WA, Cascade Energy Engineering, Inc. , Northwest Energy Efficiency

Lekov, Alex

2009-01-01T23:59:59.000Z

456

FEMP Presents Its Newest On-Demand eTraining Course on Building Automation  

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 Office of Inspector General Office of Audit|Department ofof Energy Offers Training on the Five Phases toSystems |

457

Automated Demand Response Benefits California Utilities and Commercial & Industrial Customers  

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:YearRound-Up fromDepartmentTie Ltd: Scope ChangeL-01-06 AuditAugust 5, 2010AutoDepartment U.S.

458

On Demand Surveillance Service in Vehicular Cloud  

E-Print Network [OSTI]

Toward Vehicular Service Cloud . . . . . . . . . . . . . . .4.2 Open Mobile Cloud Requirement . . . . .3.1 Mobile Cloud

Weng, Jui-Ting

2013-01-01T23:59:59.000Z

459

Electricity Demand and Energy Consumption Management System  

E-Print Network [OSTI]

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...

Sarmiento, Juan Ojeda

2008-01-01T23:59:59.000Z

460

INTRODUCTION Sophisticated automation is becoming ubiq-  

E-Print Network [OSTI]

INTRODUCTION Sophisticated automation is becoming ubiq- uitous, appearing in work environments as di- verse as aviation, maritime operations, process control, motor vehicle operation, and informa- tion retrieval. Automation is technology that actively selects data, transforms information, makes

Lee, John D.

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Disciplined agility for process control & automation  

E-Print Network [OSTI]

Process automation vendors must consider agility as a basis to gain a competitive edge in innovation. Process Automation systems can impact the operating cost of manufacturing equipment, the safe control of large quantities ...

Tibazarwa, Augustine

2009-01-01T23:59:59.000Z

462

Technical University of Denmark rsted DTU Automation  

E-Print Network [OSTI]

Technical University of Denmark �rsted · DTU Automation Project: SICAM - SIngle Conversion stage based SICAM using an LC-network Petar Ljusev, MSc., Ph.D. student, �rsted · DTU Automation e-mail: pl

463

The Automation Of Proof By Mathematical Induction   

E-Print Network [OSTI]

This paper is a chapter of the Handbook of Automated Reasoning edited by Voronkov and Robinson. It describes techniques for automated reasoning in theories containing rules of mathematical induction. Firstly, inductive reasoning is defined and its...

Bundy, Alan

464

An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for  

E-Print Network [OSTI]

An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for Co). In addition, an automated vehicle should also self-assess its own perception abilities, and not only perceive this idea, cybercars were designed as fully automated vehicles [3], thought since its inception as a new

Paris-Sud XI, Université de

465

TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 1 Automated Guiding Task of a Flexible Micropart  

E-Print Network [OSTI]

TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 1 Automated Guiding Task of a Flexible Micropart Lutz, Member, IEEE Abstract--This paper studies automated tasks based on hybrid force/position control of automated guiding task are presented. Note to Practitioners -- This article's motivation is the need of very

Paris-Sud XI, Université de

466

Transport Research Arena Europe 2010, Brussels Towards Highly Automated Driving  

E-Print Network [OSTI]

of HAVEit is to develop and investigate vehicle automation beyond ADAS systems, especially highly automated automated vehicles In 2010, two lines of research and development exist in the domain of ground vehicle automation: Either the automation is driving the vehicle fully automated without a human driver

Paris-Sud XI, Université de

467

Industrial Demand-Side Management in Texas  

E-Print Network [OSTI]

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...

Jaussaud, D.

468

Automated Tuning of Optimization Software Parameters  

E-Print Network [OSTI]

Automated Tuning of Optimization Software Parameters. University of Pittsburgh Department of Industrial Engineering. Technical Report 2007-7. Mustafa Baz ...

2007-10-29T23:59:59.000Z

469

Scalable Distributed Automation System: Scalable Real-time Decentralized Volt/VAR Control  

SciTech Connect (OSTI)

GENI Project: Caltech is developing a distributed automation system that allows distributed generators—solar panels, wind farms, thermal co-generation systems—to effectively manage their own power. To date, the main stumbling block for distributed automation systems has been the inability to develop software that can handle more than 100,000 distributed generators and be implemented in real time. Caltech’s software could allow millions of generators to self-manage through local sensing, computation, and communication. Taken together, localized algorithms can support certain global objectives, such as maintaining the balance of energy supply and demand, regulating voltage and frequency, and minimizing cost. An automated, grid-wide power control system would ease the integration of renewable energy sources like solar power into the grid by quickly transmitting power when it is created, eliminating the energy loss associated with the lack of renewable energy storage capacity of the grid.

None

2012-03-01T23:59:59.000Z

470

Maximum-Demand Rectangular Location Problem  

E-Print Network [OSTI]

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

Manish Bansal

2014-10-01T23:59:59.000Z

471

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

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

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

472

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

473

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....

474

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

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,

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

475

Wireless Demand Response Controls for HVAC Systems  

E-Print Network [OSTI]

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

Federspiel, Clifford

2010-01-01T23:59:59.000Z

476

Retail Demand Response in Southwest Power Pool  

E-Print Network [OSTI]

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

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

477

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...

478

Robust newsvendor problem with autoregressive demand  

E-Print Network [OSTI]

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

2014-05-19T23:59:59.000Z

479

Optimization of Demand Response Through Peak Shaving  

E-Print Network [OSTI]

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 ...

2013-06-19T23:59:59.000Z

480

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "open automated demand" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

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

Goldman, Charles

2010-01-01T23:59:59.000Z

482

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...

483

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...

484

Technical Report TRARP1695 Automated Reasoning Project  

E-Print Network [OSTI]

Technical Report TR­ARP­16­95 Automated Reasoning Project Research School of Information Sciences Heuerding Automated Institute for Applied Mathematics Reasoning Project and Computer Science ANU University that contains automated proof procedures based on modal Gentzen systems for numerous propositional (nonclassical

Goré, Rajeev

485

Feasible Path Synthesis for Automated Guided Vehicles  

E-Print Network [OSTI]

Feasible Path Synthesis for Automated Guided Vehicles Reijer Idema 2005 TU Delft FROG Navigation for Automated Guided Vehicles Author: Reijer Idema Supervisors: prof.dr.ir. P. Wesseling (TU Delft) dr.ir. Kees is a manufacturer of Automated Guided Vehicles. They have developed a multitude of vehicles that transport products

Vuik, Kees

486

INTEGRATING AUTOMATION DESIGN INFORMATION WITH XML  

E-Print Network [OSTI]

INTEGRATING AUTOMATION DESIGN INFORMATION WITH XML Mika Viinikkala, Seppo Kuikka Institute of Automation and Control, Tampere University of Technology, P.O. Box 692, 33101 Tampere, Finland Email: mika.viinikkala@tut.fi, seppo.kuikka@tut.fi Keywords: Systems integration, XML, automation design Abstract: This paper presents

487

A DISTRIBUTED AUTOMATION SYSTEM FOR ELECTROPHYSICAL INSTALLATIONS  

E-Print Network [OSTI]

A DISTRIBUTED AUTOMATION SYSTEM FOR ELECTROPHYSICAL INSTALLATIONS V.R. Kozak Budker Institute There was designed a set of devices for automation systems of physical installations. On this basis approach. KEY WORDS Automation, systems, applications, CANBUS, embedded, controller. 1. Introduction Budker

Kozak, Victor R.

488

Comparison lamps automation CTIO 60 inches Echelle  

E-Print Network [OSTI]

Comparison lamps automation CTIO 60 inches Echelle ECH60S5.1 La Serena, December 09, 2009 #12)...............................................................................12 CTIO 60 inches Echelle / Comparison lamps automation, ECH60S5.1 2 #12;Introduction The present document is just a brief summary of the work done automating the 60 inches echelle comparison lamps

Tokovinin, Andrei A.

489

TAMPERE UNIVERSITY OF TECHNOLOGY DEPARTMENT OF AUTOMATION  

E-Print Network [OSTI]

TAMPERE UNIVERSITY OF TECHNOLOGY DEPARTMENT OF AUTOMATION An Intelligent Web Service for Operation 2004 Examiner: Prof. Seppo Kuikka #12;2 Abstract TAMPERE UNIVERSITY OF TECHNOLOGY Automation Degree Program Institute of Automation and Control Jaakkola, Veli-Pekka: An Intelligent Web Service for Operation

490

Comparison lamps automation CTIO 60 inches CHIRON  

E-Print Network [OSTI]

Comparison lamps automation CTIO 60 inches CHIRON CHI60HF5.2 La Serena, March 16, 2011 #12;Table)...............................................................................12 CTIO 60 inches Chiron / Comparison lamps automation, CHI60HF5.2 2 #12;Introduction The present document is just a brief summary of the work done automating the 60 inches chiron comparison lamps

Tokovinin, Andrei A.

491

Electric Water Heater Modeling and Control Strategies for Demand Response  

SciTech Connect (OSTI)

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

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

2012-07-22T23:59:59.000Z

492

Technical Meeting: Data/Communication Standards and Interoperability...  

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

& ISOIEC 14908 (LonMark International) Presentation: Introducing Open Automated Demand Response (OpenADR) (Honeywell) Presentation: Consortium for SEP 2 Interoperability...

493

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network [OSTI]

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

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

494

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...

495

Landscape Planning and Biogeochemistry: Estimating and Analyzing Carbon Sequestration Efficacy In Dryland Open Space.  

E-Print Network [OSTI]

??Despite public demand for climate change mitigation and natural open space conservancy, existing political and design efforts are only beginning to address the declining efficacy… (more)

Huck, Erick Otto

2012-01-01T23:59:59.000Z

496

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

497

DEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT  

E-Print Network [OSTI]

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

Bierlaire, Michel

498

Demand Response and Electric Grid Reliability  

E-Print Network [OSTI]

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...

Wattles, P.

2012-01-01T23:59:59.000Z

499

A Vision of Demand Response - 2016  

SciTech Connect (OSTI)

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)

Levy, Roger

2006-10-15T23:59:59.000Z

500

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