A novel approach to short-term load forecasting using fuzzy neural networks

An efficient modeling technique based on the fuzzy curve notion is developed in this paper to generate fuzzy models for short-term load forecasting. The suggested forecasting approach proceeds on the following steps: (a) prediction of the load curve extremals (peak and valley loads) using separate fuzzy models; (b) formulation of the representative day based on historical load data; and (c) mapping of the representative day load curve to the forecasted peak values to obtain the predicted day load curves. Very good prediction performance is attained as shown in the simulation results which verify the effectiveness of the modeling technique.