3897 -- On-Line Prediction for Load Profile of an Air-Conditioning System PDF

Describes a load profile prediction algorithm that has recently been developed for use in the optimal operation of cool/heat storage systems. It is highly desirable to devise an on-line prediction technique so that the difference between a predicted load and an actual load is as small as possible. To accomplish this, an autoregressive integrated moving average (ARIMA) model is assumed. The modelling is first done for the past load data. Next, the model predicts load profiles for the next day. The load profiles are updated every hour on the basis of the newly obtained load data. Performance of the load profile prediction algorithm was assessed by recording the cooling load (1987) at an Osaka site. Results show generally good agreement between actual and predicted loads.

KEYWORDS: year 1995, cooling load, heat load, air conditioning, calculating, measuring, comparing, accuracy, algorithms