Journal
ENERGY AND BUILDINGS
Volume 53, Issue -, Pages 7-18Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2012.06.024
Keywords
Gaussian process modeling; Measurement and verification; Performance-based contracts; Retrofit analysis; Uncertainty
Funding
- U.S. Department of Energy [DE-AC02-06CH11357]
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We present a Gaussian process (GP) modeling framework to determine energy savings and uncertainty levels in measurement and verification (M&V) practices. Existing M&V guidelines provide savings calculation procedures based on linear regression techniques that are limited in their predictive and uncertainty estimation capabilities. We demonstrate that, unlike linear regression, GP models can capture complex nonlinear and multivariable interactions as well as multiresolution trends of energy behavior. In addition, because GP models are developed under a Bayesian setting, they can capture different sources of uncertainty in a more systematic way. We demonstrate that these capabilities can ultimately lead to significantly less expensive M&V practices. We illustrate the developments using simulated and real data settings. (c) 2012 Elsevier B.V. All rights reserved.
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