Abstract
To control the thermal storage operation properly, it is necessary to predict the heat load of the next day in advance. The present paper focuses on a load prediction method based on Kalman filter through the comparison of load predictions for two buildings with four kinds of applications of it. It has been made clear that the identified load of the present day, out-door temperature and the forecasted highest outdoor temperature are very effective as the input variables in the cooling load prediction, and that the heat load prediction method based on Kalman filter can follow the heat load trend with sufficient accuracy.
