Short-term load forecasting using radial basis function networks and expert system

Investigating the effect of weather factors and special events on electric power load, a load forecasting model based on RBF (Radial Basis Function) neural networks and expert system is established, and an effective algorithm is also designed. First the load curve for one day was approximated by RBF net using its nonlinear convergence. The expert system was used to make this model work under special disturbance. A practical software package has been formed and applied to some Power Nets of Northwest China Power System, which improves the precision of short-term load forecasting. The effectiveness of the model has been verified by actual operation.