Estimating Electricity Demand in the Agriculture Sector Using Auto-Regressive Distributed Lag Appraoch and Genetic Algorithm (Case Study: Isfahan Province)

M.R. Zare Mehrjerdi(Ph.D.), R. Faramarzi Filabadi, F. Darageh

Abstract
Electricity is an important factor in development of human societies. Regarding that and due to the role of electricity demand in making policies and decisions about production, distribution and supply of this energy carrier and also the importance of such energy as an effective input in agricultural production, it is necessary to investigate the electrical energy market and especially the demand for it. In this paper, we have used two methods, Auto-Regressive distributed lag (ARDL) and Genetic algorithms, first to estimate the electricity demand function in the agriculture sector of Isfahan province and second to analyze the main factors which affect this function. The results show that Genetic algorithms method is more accurate in estimating the electricity demand function. The results of both methods suggest that price policies has no important effects on consumption level, also the most important factor affecting electricity demand in the agriculture sector is the number of subscribers.

JEL Classification: C13, C52, L23, L7

Keywords:
Agriculture Electricity Demand, Genetic Algorithm, ARDL, Isfahan