Uncertainty in baseline regression modeling and in determination of retrofit savings
- Drexel Univ., Philadelphia, PA (United States). Civil and Architectural Engineering Dept.
- Univ. of Dayton, OH (United States). Mechanical Engineering Dept.
- Sam Houston State Univ., Huntsville, TX (United States). Dept. of Mathematical and Informational Services
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.
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 665311
- Journal Information:
- Journal of Solar Energy Engineering, Vol. 120, Issue 3; Other Information: PBD: Aug 1998
- Country of Publication:
- United States
- Language:
- English
Similar Records
A regression-based approach to estimating retrofit savings using the Building Performance Database
Multivariate regression modeling