Fuzzy Multiple Linear Regression for the Short Term Load Forecast

In predicting the hourly demand for energy trading, the weather forecast error makes the usage of the exact values of certain predictor variables (such as temperature) very difficult. Therefore, the fuzzy input variables are often used. This paper presents a new way of using the fuzzy inputs in linear regression in forecasting hourly consumption for the day-ahead period. Unlike the present approach to the fuzzy linear regression, where the regression coefficients have been fuzzified, in this model the degrees of membership to the fuzzy sets are used as additional predictor variables