Peak load forecasting in power systems using emotional learning based fuzzy logic

The primary tasks of an electric utility is to predict the load requirements of the power system. Especially important is forecasting of the peak load, since it is the basis for the system state estimation and for technical and economic calculations of the generation and distribution system. To minimize the operating cost, electric supplier will use forecasted load to control the number of running generator unit. This paper is concerned with the prediction of the daily peak value of the load in the power system using emotional learning based fuzzy approach. Emotional learning is a family of intelligent algorithms, which can be used for time series prediction, classification, control and identification. The simulation results show that the proposed method is suitable for forecasting application. This method is relatively simple, and effectively uses historical data to provide load forecasts.