Change-point principal component analysis (CP/PCA) method for predicting energy usage in commercial buildings. The PCA model Academic Article uri icon

abstract

  • A new method for predicting daily whole-building electricity usage in a commercial building has been developed. This method utilizes a Principal Component Analysis (PCA) of intercorrelated influencing parameters (e.g., dry-bulb temperature, solar radiation and humidity) to predict electricity consumption in conjunction with a change-point model. This paper describes the Principal Component Analysis procedure and presents the results of its application in conjunction with a change-point regression, to predict whole-building electricity consumption for a commercial grocery store. Comparison of the results with a traditional Multiple Linear Regression (MLR) analysis indicates that a change-point, Principal Component Analysis (CP/PCA) appears to be a significantly better predictor than a MLR analysis, and offers more insight into the environmental and operational driving forces that influence energy consumption in a commercial building. A companion paper presents the development of the four parameter change-point model and a comparison to the Princeton Scorekeeping Method (PRISM) (Ruch and Claridge 1991).

author list (cited authors)

  • Ruch, D., Chen, L., Haber, J. S., & Claridge, D. E.

publication date

  • January 1991