Simulation of Electricity Demand Function in Agricultural Sector: An Application of Genetic Algorithm (Case Study: Electricity-Fed Wells of Iran)
Author(s) -
Hossein Sadeghi,
Samaneh Astaneh,
Mohammadhadi Hajian,
Shahdokht Azadi
Publication year - 2014
Publication title -
current world environment
Language(s) - English
Resource type - Journals
eISSN - 2320-8031
pISSN - 0973-4929
DOI - 10.12944/cwe.9.3.10
Subject(s) - electricity , agriculture , genetic algorithm , function (biology) , engineering , environmental science , algorithm , computer science , electrical engineering , mathematical optimization , mathematics , biology , ecology , evolutionary biology
Due to several problems arisen from consumption of gas oil, it is necessary to electricity substitute fossil fuels in agriculture wells in Iran. Problems such as lack of opportune and adequate supply of fuel, air and soil pollution, noise pollution and huge costs of installation, operation and maintenance imply the necessity of replacing gas oil systems by electricity-consuming ones in agriculture sector of Iran.However, it is essential to study on the demand of electricity, nowadays, substituting other energy sources.As waterwells are the main electricity consumersin agriculture sector, the estimation of energy demand function would be beneficial for policy makers to achieve their goals. The present paper investigates on energy demand function in agriculture sector of Iran. Genetic algorithm techniques are appliedto estimate electricity demand in agricultural sector in three forms: linear, quadratic and exponential equations. Based on the conventional criteria, the exponential model is selected as the best model for estimation. Furthermore, electricity demandof agricultural sector is forecasted under three scenarios for years next three years.
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