Wavelet neural network embedded expert system used in short-term load forecasting

Abstract

The wavelet neural network has been widely used as a new load forecasting method. This paper has analyzed wavelet neural network which consists with wavelet and artificial neural network. Summarize historical load data to fine the long-term variation, gain the empirical knowledge from professionals, and form a series of rules to simulate a human expert reasoning and judging process, which is the expert system. Finally, use expert system to correct data in wavelet neural network, and predicted results can be obtained. The case study, about the load forecasting of a city grid, is very well embedded in the wavelet neural network expert system approach, and the prediction accuracy has get improved as well.