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Title: Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance

Abstract

Accurate evaluation of the performance of buildings participating in Demand Response (DR) programs is critical to the adoption and improvement of these programs. Typically, we calculate load sheds during DR events by comparing observed electric demand against counterfactual predictions made using statistical baseline models. Many baseline models exist and these models can produce different shed calculations. Moreover, modelers implementing the same baseline model can make different modeling implementation choices, which may affect shed estimates. In this work, using real data, we analyze the effect of different modeling implementation choices on shed predictions. We focused on five issues: weather data source, resolution of data, methods for determining when buildings are occupied, methods for aligning building data with temperature data, and methods for power outage filtering. Results indicate sensitivity to the weather data source and data filtration methods as well as an immediate potential for automation of methods to choose building occupied modes.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1212092
Report Number(s):
LBNL-5560E
DOE Contract Number:  
DE-AC02-05CH11231
Resource Type:
Conference
Resource Relation:
Conference: ASME 2012 International Mechanical Engineering Congress & Exposition, Houston, TX, November 9-15, 2012
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION

Citation Formats

University of California, Berkeley, Addy, Nathan, Kiliccote, Sila, Mathieu, Johanna, and Callaway, Duncan S. Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance. United States: N. p., 2012. Web.
University of California, Berkeley, Addy, Nathan, Kiliccote, Sila, Mathieu, Johanna, & Callaway, Duncan S. Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance. United States.
University of California, Berkeley, Addy, Nathan, Kiliccote, Sila, Mathieu, Johanna, and Callaway, Duncan S. Wed . "Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance". United States. https://www.osti.gov/servlets/purl/1212092.
@article{osti_1212092,
title = {Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance},
author = {University of California, Berkeley and Addy, Nathan and Kiliccote, Sila and Mathieu, Johanna and Callaway, Duncan S.},
abstractNote = {Accurate evaluation of the performance of buildings participating in Demand Response (DR) programs is critical to the adoption and improvement of these programs. Typically, we calculate load sheds during DR events by comparing observed electric demand against counterfactual predictions made using statistical baseline models. Many baseline models exist and these models can produce different shed calculations. Moreover, modelers implementing the same baseline model can make different modeling implementation choices, which may affect shed estimates. In this work, using real data, we analyze the effect of different modeling implementation choices on shed predictions. We focused on five issues: weather data source, resolution of data, methods for determining when buildings are occupied, methods for aligning building data with temperature data, and methods for power outage filtering. Results indicate sensitivity to the weather data source and data filtration methods as well as an immediate potential for automation of methods to choose building occupied modes.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {6}
}

Conference:
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