Short Term Load Forecasting Based On Brain Emotional Predictor

Using a precise short-term load forecasting (STLF) reduces the operating costs and increases reliability of power system operations. In this paper, a brain emotional prediction (BEP) method is used for STLF. The ability of the method is verified in a practical power system, using its electricity demand data. An algorithm is developed to choose the BEP input data base on the type of the forecasted day, in order to increase the performance of the proposed method. The simulation results confirm the ability of the proposed method for short-term load forecasting.

Keywords:

short-term load forecasting , brain emotional predictor (BEP) , adaptive neuro fuzzy inference system (ANFIS) , artificial neural network (ANN)