Estimating Electricity Demand Function in Residential Sector by Fuzzy Regression

This paper presents a fuzzy regression approach for estimation of electricity demand function in residential sector. Moreover, electricity consumption in residential sector plays an important role in economical decision making process. This is also highlighted by the fact that residential sector has the largest share of consumption among all the other sectors including industrial, business, etc. The importance of fuzzy regression becomes evident by facing imprecise quantities and insufficient amount of data for estimation of energy consumption in residential sector. Fuzzy regression is applied to Iranian residential sectors using for estimation of unknown parameters. A review of a fuzzy linear regression is presented in which the center regression line has the best ability to interpret training data. The interpretation ability of the regression line can be measured by the proposed index of confidence, IC. We discussed that if one is not sure about the collected data, a larger h value to fit the collected data is needed to ensure the better interpretative ability of the regression line. Using sum square of error (SSE) and partial IC, a forward selection procedure for X variables is provided. Finally, an estimation of electricity demand function in residential sector for three different values of h and comparison of these cases is done