Fuzzy Logic and T-Test for Load Forecasting

Abstract

The forecasting models based on regression function have the analytic form with proving that there is some rule expressing the correlation between forecasting value and other related fators. In reality, forecasted load is not always in linear form of factors, such as: temperature, population, GDP or historical load data. This paper applied fuzzy rules to approximate the relationship between loads and other factors using the subtractive clustering. The implementation is carried out for one substation in Ho Chi Minh city. Results show that the proposed approach gives better accuracycy of forecasting, and the effort of finding crisp function for forecasting is not helping to have better results.