Estimating and improving electricity demand function in residential sector with imprecise data by fuzzy regression

Ali Azadeh, Morteza Saberi, Seyed Farid Ghaderi and Anahita Gitiforouz

International Journal of Mathematics in Operational Research, 2010, vol. 2, issue 4, 405-423

Abstract: This paper presents a fuzzy regression approach for estimation of electricity demand in residential sector with imprecise data. 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, and so on. 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. A review of a fuzzy linear regression is presented in which the centre 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. Finally, an estimation of electricity demand function in residential sector for three different values of h is presented.

Keywords: electricity demand; residential sectors; fuzzy regression; mathematical programming; fuzzy logic; electricity consumption; Iran; imprecise data. (search for similar items in EconPapers)
Date: 2010
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