A CHANGE-POINT PRINCIPAL COMPONENT ANALYSIS (CP PCA) METHOD FOR PREDICTING ENERGY USAGE IN COMMERCIAL BUILDINGS - THE PCA MODEL/

A new method for predicting daily whole-building electricity usage in a commercial building has been developed. This method utilizes a Princ ipal Component Analysis (PCA) of intercorrelated influencing parameter s (e.g., dry-bulb temperature, solar radiation and humidity) to predic t electricity consumption in conjunction with a change-point model. Th is paper describes the PCA procedure and presents the results of its a pplication in conjunction with a change-point regression, to predict w hole-building electricity consumption for a commercial grocery store. Comparison of the results with a traditional Multiple Linear Regressio n (MLR) analysis indicates that a change-point, Principal Component An alysis (CP/PCA) appears to produce a more reliable and physically plau sible model than an MLR analysis and offers more insight into the envi ronmental and operational driving forces that influence energy consump tion in a commercial building. It is thought that the method will be u seful for determining conservation retrofit savings from pre-retrofit and post-retrofit consumption data for commercial buildings. A compani on paper presents the development of the four-parameter change-point m odel and a comparison to the Princeton Scorekeeping Method (PRISM) (Ru ch and Claridge, 1991).