Short-Term Electric Power Load Forecasting Based on Neural Network Model

The effect of weather factors and special events on electric power load are investigated. A load forecasting model based on Radial Basis Function (RBF)is presented the temperature and precipitation are applied to RBF's training process. This optimizing algorithm can improve the credibility and reliability of network training. A practical software package has been formed and applied, which improves the precision of short-term load forecastin. The effectiveness of the model has been verified by actual operation.