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Title: Automated Critical Peak Pricing Field Tests: Program Descriptionand Results

Abstract

California utilities have been exploring the use of critical peak prices (CPP) to help reduce needle peaks in customer end-use loads. CPP is a form of price-responsive demand response (DR). Recent experience has shown that customers have limited knowledge of how to operate their facilities in order to reduce their electricity costs under CPP (Quantum 2004). While the lack of knowledge about how to develop and implement DR control strategies is a barrier to participation in DR programs like CPP, another barrier is the lack of automation of DR systems. During 2003 and 2004, the PIER Demand Response Research Center (DRRC) conducted a series of tests of fully automated electric demand response (Auto-DR) at 18 facilities. Overall, the average of the site-specific average coincident demand reductions was 8% from a variety of building types and facilities. Many electricity customers have suggested that automation will help them institutionalize their electric demand savings and improve their overall response and DR repeatability. This report focuses on and discusses the specific results of the Automated Critical Peak Pricing (Auto-CPP, a specific type of Auto-DR) tests that took place during 2005, which build on the automated demand response (Auto-DR) research conducted through PIER and themore » DRRC in 2003 and 2004. The long-term goal of this project is to understand the technical opportunities of automating demand response and to remove technical and market impediments to large-scale implementation of automated demand response (Auto-DR) in buildings and industry. A second goal of this research is to understand and identify best practices for DR strategies and opportunities. The specific objectives of the Automated Critical Peak Pricing test were as follows: (1) Demonstrate how an automated notification system for critical peak pricing can be used in large commercial facilities for demand response (DR). (2) Evaluate effectiveness of such a system. (3) Determine how customers will respond to this form of automation for CPP. (4) Evaluate what type of DR shifting and shedding strategies can be automated. (5) Explore how automation of control strategies can increase participation rates and DR saving levels with CPP. (6) Identify optimal demand response control strategies. (7) Determine occupant and tenant response.« less

Authors:
; ; ; ;
Publication Date:
Research Org.:
Ernest Orlando Lawrence Berkeley NationalLaboratory, Berkeley, CA (US)
Sponsoring Org.:
USDOE. Assistant Secretary for Energy Efficiency andRenewable Energy.Office of the Deputy Assistant Secretary for TechnologyDevelopment. Office of the Basic Technologies Program; Pacific Gas andElectric, Calilifornia Institute for Energy Efficiency (CIEE), Universityof California CIEE/PG&E Contract PGZ-0501
OSTI Identifier:
901672
Report Number(s):
LBNL-59351
R&D Project: E21447; BnR: 600303000; TRN: US200716%%409
DOE Contract Number:
DE-AC02-05CH11231
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
32; AUTOMATION; CALIFORNIA; ELECTRICITY; FIELD TESTS; IMPLEMENTATION; MARKET; OCCUPANTS; PRICES

Citation Formats

Piette, Mary Ann, Watson, David, Motegi, Naoya, Kiliccote, Sila, and Xu, Peng. Automated Critical Peak Pricing Field Tests: Program Descriptionand Results. United States: N. p., 2006. Web. doi:10.2172/901672.
Piette, Mary Ann, Watson, David, Motegi, Naoya, Kiliccote, Sila, & Xu, Peng. Automated Critical Peak Pricing Field Tests: Program Descriptionand Results. United States. doi:10.2172/901672.
Piette, Mary Ann, Watson, David, Motegi, Naoya, Kiliccote, Sila, and Xu, Peng. Thu . "Automated Critical Peak Pricing Field Tests: Program Descriptionand Results". United States. doi:10.2172/901672. https://www.osti.gov/servlets/purl/901672.
@article{osti_901672,
title = {Automated Critical Peak Pricing Field Tests: Program Descriptionand Results},
author = {Piette, Mary Ann and Watson, David and Motegi, Naoya and Kiliccote, Sila and Xu, Peng},
abstractNote = {California utilities have been exploring the use of critical peak prices (CPP) to help reduce needle peaks in customer end-use loads. CPP is a form of price-responsive demand response (DR). Recent experience has shown that customers have limited knowledge of how to operate their facilities in order to reduce their electricity costs under CPP (Quantum 2004). While the lack of knowledge about how to develop and implement DR control strategies is a barrier to participation in DR programs like CPP, another barrier is the lack of automation of DR systems. During 2003 and 2004, the PIER Demand Response Research Center (DRRC) conducted a series of tests of fully automated electric demand response (Auto-DR) at 18 facilities. Overall, the average of the site-specific average coincident demand reductions was 8% from a variety of building types and facilities. Many electricity customers have suggested that automation will help them institutionalize their electric demand savings and improve their overall response and DR repeatability. This report focuses on and discusses the specific results of the Automated Critical Peak Pricing (Auto-CPP, a specific type of Auto-DR) tests that took place during 2005, which build on the automated demand response (Auto-DR) research conducted through PIER and the DRRC in 2003 and 2004. The long-term goal of this project is to understand the technical opportunities of automating demand response and to remove technical and market impediments to large-scale implementation of automated demand response (Auto-DR) in buildings and industry. A second goal of this research is to understand and identify best practices for DR strategies and opportunities. The specific objectives of the Automated Critical Peak Pricing test were as follows: (1) Demonstrate how an automated notification system for critical peak pricing can be used in large commercial facilities for demand response (DR). (2) Evaluate effectiveness of such a system. (3) Determine how customers will respond to this form of automation for CPP. (4) Evaluate what type of DR shifting and shedding strategies can be automated. (5) Explore how automation of control strategies can increase participation rates and DR saving levels with CPP. (6) Identify optimal demand response control strategies. (7) Determine occupant and tenant response.},
doi = {10.2172/901672},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Apr 06 00:00:00 EDT 2006},
month = {Thu Apr 06 00:00:00 EDT 2006}
}

Technical Report:

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  • During 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) performed a technology evaluation for the Pacific Gas and Electric Company (PG&E) Emerging Technologies Programs. This report summarizes the design, deployment, and results from the 2006 Automated Critical Peak Pricing Program (Auto-CPP). The program was designed to evaluate the feasibility of deploying automation systems that allow customers to participate in critical peak pricing (CPP) with a fully-automated response. The 2006 program was in operation during the entire six-month CPP period from May through October. The methodology for this field study included site recruitment, control strategy development,more » automation system deployment, and evaluation of sites' participation in actual CPP events through the summer of 2006. LBNL recruited sites in PG&E's territory in northern California through contacts from PG&E account managers, conferences, and industry meetings. Each site contact signed a memorandum of understanding with LBNL that outlined the activities needed to participate in the Auto-CPP program. Each facility worked with LBNL to select and implement control strategies for demand response and developed automation system designs based on existing Internet connectivity and building control systems. Once the automation systems were installed, LBNL conducted communications tests to ensure that the Demand Response Automation Server (DRAS) correctly provided and logged the continuous communications of the CPP signals with the energy management and control system (EMCS) for each site. LBNL also observed and evaluated Demand Response (DR) shed strategies to ensure proper commissioning of controls. The communication system allowed sites to receive day-ahead as well as day-of signals for pre-cooling, a DR strategy used at a few sites. Measurement of demand response was conducted using two different baseline models for estimating peak load savings. One was the CPP baseline model, which is based on the site electricity consumption from noon to 6 p.m. for the three days with highest consumption of the previous ten non-weekend days; it is not normalized for weather. The second model, the LBNL adjusted outside air temperature (OAT) regression baseline model, is based on OAT data and site electricity consumption from the previous ten days, and it is adjusted using weather regressions from the fifteen-minute electric load data during each event day. These baseline models were used to evaluate the demand reduction during each DR event for each site. The aggregated response from all sites for each event was also estimated using both baseline models. The evaluation research also included surveying the facility managers regarding any problems or issues that arose during the DR events. Questions covered occupant comfort, controls issues, and other potential problems. This 2006 Auto-CPP study included an assessment of the CPP economics for each site. This consisted of summing all of the credits on non-CPP days and subtracting the charges on CPP days. Estimates of the CPP economics without the demand response control strategies were also developed.« less
  • DOE decided to co-fund ten utilities to undertake eleven experimentally-designed Consumer Behavior Studies (CBS) that proposed to examine a wide range of the topics of interest to the electric utility industry. Each chosen utility was to design, implement and evaluate their own study in order to address questions of interest both to itself and to its applicable regulatory authority, whose approval was generally necessary for the study to proceed. The DOE Office of Energy Delivery and Electricity Reliability (OE), however, did set guidelines, both in the FOA and subsequently during the contracting period, for what would constitute an acceptable studymore » under the Grant. To assist in ensuring these guidelines were adhered to, OE requested that LBNL act as project manager for these Consumer Behavior Studies to achieve consistency of experimental design and adherence to data collection and reporting protocols across the ten utilities. As part of its role, LBNL formed technical advisory groups (TAG) to separately assist each of the utilities by providing technical assistance in all aspects of the design, implementation and evaluation of their studies. LBNL was also given a unique opportunity to perform a comprehensive, cross-study analysis that uses the customer-level interval meter and demographic data made available by these utilities due to SGIG-imposed reporting requirements, in order to analyze critical policy issues associated with AMI-enabled rates and control/information technology. LBNL will publish the results of these analyses in a series of research reports, of which this is one, that attempt to address critical policy issues relating to a variety of topics including customer acceptance, retention and load response to time-based rates and various forms of enabling control and information technologies. This report extends the existing empirical literature on the experiences of low-income customers exposed to critical peak pricing, and provides the first glimpses into the experiences of the elderly and those who reported being chronically ill. Specifically, we analyzed two of the time-based rate consumer behavior studies, which were co-funded by the Department of Energy as part of the Smart Grid Investment Grant program.« less
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