Metabolic Models about Daily Load Forecasting Based on Adaptive Filtering Algorithm

A novel daily load forecasting method based on adaptive filtering algorithm for short-term daily load is presented.During the forecasting,the history data is dealt with using metabolic theory and the weighted coefficient is given to the result according to the day property,then the result is adfusted on historical date variable to get better accuracy.Furthermore,the AR model for the error is set up and formed the combined model with the adaptive filtering model.The combined model realizes the target of high accuracy without improving the number of the sample data and computing.Simulation results demonstrate the effectiveness of the model and the feasibility of the proposed algorithm.