Uncertainty in Baseline Regression Modeling and in Determination of Retrofit Savings

[+] Author and Article Information
T. A. Reddy

Drexel University, Civil and Architectural Engineering Department, Philadelphia, PA

J. K. Kissock

University of Dayton, Mechanical Engineering Department, Dayton, OH

D. K. Ruch

Sam Houston State University, Department of Mathematical and Informational Sciences, Huntsville, TX

J. Sol. Energy Eng 120(3), 185-192 (Aug 01, 1998) (8 pages) doi:10.1115/1.2888068 History: Received March 01, 1996; Revised May 01, 1998; Online February 14, 2008


The objective of this paper is to discuss the various sources of uncertainty inherent in the estimation of actual measured energy savings from baseline regression models, and to present pertinent statistical concepts and formulae to determine this uncertainty. Regression models of energy use in commercial buildings are not of the “standard” type addressed in textbooks because of the changepoint behavior of the models and the effect of patterned and non-constant variance residuals (largely as a result of changes in operating modes of the building and the HVAC system). This paper also addresses such issues as how model prediction is impacted by both improper model residuals and models identified from data periods which do not encompass the entire range of variation of both climatic conditions and the different building operating modes.

Copyright © 1998 by The American Society of Mechanical Engineers
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