Full Description

For measurement and verification (MV) of energy savings in buildings, we propose an approach based on Gaussian Process (GP) modeling that can represent nonlinear energy behavior, multivariable interactions, and time correlations while quantifying uncertainty associated with predictions. We applied GP modeling to determine energy savings from BuildingIQs energy management system deployed at the Advanced Photon Source Office building at Argonne. The case study demonstrates the potential strengths of GP models for MV and explores the importance of dataset characteristics and explanatory variables for the reliability of analysis results. The case study illustrates the capability of GP modeling to predict hourly dynamic behavior, exploiting the possibility to reduce uncertainty in energy-use predictions using measured data with finer time resolutions. The proposed MV approach is amendable to automation in energy management systems and continuous monitoring of energy performance.

Citation: ASHRAE Conference Papers, Denver, CO

Product Details

Published: 2013 Number of Pages: 8File Size: 1 file , 400 KB Product Code(s): D-DE-13-C031