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Title: Variability in Automated Responses of Commercial Buildings and Industrial Facilities to Dynamic Electricity Prices

Abstract

Changes in the electricity consumption of commercial buildings and industrial facilities (C&I facilities) during Demand Response (DR) events are usually estimated using counterfactual baseline models. Model error makes it difficult to precisely quantify these changes in consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. This paper seeks to understand baseline model error and DR variability in C&I facilities facing dynamic electricity prices. Using a regression-based baseline model, we present a method to compute the error associated with estimates of several DR parameters. We also develop a metric to determine how much observed DR variability results from baseline model error rather than real variability in response. We analyze 38 C&I facilities participating in an automated DR program and find that DR parameter errors are large. Though some facilities exhibit real DR variability, most observed variability results from baseline model error. Therefore, facilities with variable DR parameters may actually respond consistently from event to event. Consequently, in DR programs in which repeatability is valued, individual buildings may be performing better than previously thought. In some cases, however, aggregations of C&I facilities exhibit real DR variability, which could create challenges for power system operation.

Authors:
; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
Environmental Energy Technologies Division
OSTI Identifier:
1051527
Report Number(s):
LBNL-5129E
Journal ID: ISSN 0378-7788
DOE Contract Number:  
DE-AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Energy and Buildings
Additional Journal Information:
Journal Volume: 43; Journal Issue: 12; Journal ID: ISSN 0378-7788
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; demand response, baseline models, load prediction, error analysis, variability, measurement&verification

Citation Formats

Mathieu, Johanna L, Callaway, Duncan S, and Kiliccote, Sila. Variability in Automated Responses of Commercial Buildings and Industrial Facilities to Dynamic Electricity Prices. United States: N. p., 2011. Web. doi:10.1016/j.enbuild.2011.08.020.
Mathieu, Johanna L, Callaway, Duncan S, & Kiliccote, Sila. Variability in Automated Responses of Commercial Buildings and Industrial Facilities to Dynamic Electricity Prices. United States. https://doi.org/10.1016/j.enbuild.2011.08.020
Mathieu, Johanna L, Callaway, Duncan S, and Kiliccote, Sila. 2011. "Variability in Automated Responses of Commercial Buildings and Industrial Facilities to Dynamic Electricity Prices". United States. https://doi.org/10.1016/j.enbuild.2011.08.020. https://www.osti.gov/servlets/purl/1051527.
@article{osti_1051527,
title = {Variability in Automated Responses of Commercial Buildings and Industrial Facilities to Dynamic Electricity Prices},
author = {Mathieu, Johanna L and Callaway, Duncan S and Kiliccote, Sila},
abstractNote = {Changes in the electricity consumption of commercial buildings and industrial facilities (C&I facilities) during Demand Response (DR) events are usually estimated using counterfactual baseline models. Model error makes it difficult to precisely quantify these changes in consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. This paper seeks to understand baseline model error and DR variability in C&I facilities facing dynamic electricity prices. Using a regression-based baseline model, we present a method to compute the error associated with estimates of several DR parameters. We also develop a metric to determine how much observed DR variability results from baseline model error rather than real variability in response. We analyze 38 C&I facilities participating in an automated DR program and find that DR parameter errors are large. Though some facilities exhibit real DR variability, most observed variability results from baseline model error. Therefore, facilities with variable DR parameters may actually respond consistently from event to event. Consequently, in DR programs in which repeatability is valued, individual buildings may be performing better than previously thought. In some cases, however, aggregations of C&I facilities exhibit real DR variability, which could create challenges for power system operation.},
doi = {10.1016/j.enbuild.2011.08.020},
url = {https://www.osti.gov/biblio/1051527}, journal = {Energy and Buildings},
issn = {0378-7788},
number = 12,
volume = 43,
place = {United States},
year = {Tue Aug 16 00:00:00 EDT 2011},
month = {Tue Aug 16 00:00:00 EDT 2011}
}