Gaussian process modeling for measurement and verification of building energy savings

Abstract:

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 pbkp_redictive 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. © 2012 Elsevier B.V. All rights reserved.

Año de publicación:

2012

Keywords:

• Performance-based contracts
• Retrofit analysis
• Gaussian process modeling
• Measurement and verification
• UNCERTAINTY

Fuente:

scopus