Short-term power load forecasting based on autocorrelation function optimization

Reliable, short-term load forecasting by computer has been a topic of considerable interest. In this paper, a method to accomplish this that automatically adapts to changing conditions, requiring very little human intervention, is on-line, and is reliable, Is presented. It makes use of time-series models, automatically adjusting the model parameters, to forecast the load. One thing that is unique in this method is the autocorrelation optimization used for incorporating daily and weekly periodicities.