Fuzzy expert systems: an application to short-term load forecasting

An expert system using fuzzy set theory is presented for short-term load forecasting. Since most statistical methods for short-term load forecasting rely heavily on weather variables and statistical models, errors may appear in the forecasted hourly loads due to uncertainties in weather variables and statistical models. Thus, to have better accuracy, the operators in many utilities try to update the forecasted loads in real time using the records of the past few hours and their heuristic rules. In the paper, an expert system to perform this updating function is developed. Experienced operators' heuristic rules are imbedded in the knowledge base. The uncertainties in weather variables and statistical models are dealt with using the fuzzy-set theory. To demonstrate the effectiveness of the proposed fuzzy expert system, short-term load forecasting is performed on the Taiwan power system. Test results indicate that the fuzzy expert system is very effective in improving the accuracy of the forecast hourly loads.