D. Datta, S.A. Tassou, D. Marriott
Year:
1997
Bibliographic info:
Belgium, Proceedings of Clima 2000 Conference, held Brussels, August 30th to September 2nd 1997

It has been shown by previous researchers that Artificial Neural Networks (ANNs) not only be used to predict energy more reliably than traditional simulation models and regression techniques but can also from the basis for a predictive controller of thermal systems such as HVAC equipment. This work is directed towards the identification of the important inputs (independent variables) to facilitate on-line prediction and thereby implement refrigeration and HVAC system diagnostics, process control, optimisation and energy management in retail food stores. This paper presents preliminary results on the prediction of electricity consumption with different independent input variables in a supermarket. The paper also compares the prediction performance of neural networks with the more traditional multiple regression techniques.