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

Publication Type

Conference Paper

Authors

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

Tertiary Author

Han, Junqiao

Abstract

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 explanatoryvariables.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.

Journal

IEEE-PES/IAS Conference on Sustainable Alternative Energy

Year of Publication

2009