In the last decades due to progress in technology of production and efficiency of energy consumption, low quality energy such as coal has been replaced by high quality energy such as electricity. Electricity as a vital input in various sectors especially in agriculture plays a crucially important role in production. Therefore, estimation of consumption and well-timed supply of required electricity in the agriculture sector could increase production. In this study, by utilizing the Particle Swarm Optimization (PSO) algorithm, we first simulate the electricity demand function in the form of linear and exponentials functions for period of 1978-2006 and then we choose the best model according to the existing criteria. The electricity demand is considered as a function of the real price of the electricity in the sector, augmented cost, number of subscribers, and consumption of previous period. Findings of the study demonstrated that the electricity demand had a direct relationship with real price of electricity and indirect relationship with augmented cost, number of subscribers, and consumption in previous period.
b, M., GH, A., K, A., & A, H. (2014). Simulating Electricity Demand Function in the Agriculture Sector: Application of Particle Swarm Optimization Algorithm. Agricultural Economics Research, 6(22), 1-11.
MLA
m. b; A. GH; A. K; H. A. "Simulating Electricity Demand Function in the Agriculture Sector: Application of Particle Swarm Optimization Algorithm". Agricultural Economics Research, 6, 22, 2014, 1-11.
HARVARD
b, M., GH, A., K, A., A, H. (2014). 'Simulating Electricity Demand Function in the Agriculture Sector: Application of Particle Swarm Optimization Algorithm', Agricultural Economics Research, 6(22), pp. 1-11.
VANCOUVER
b, M., GH, A., K, A., A, H. Simulating Electricity Demand Function in the Agriculture Sector: Application of Particle Swarm Optimization Algorithm. Agricultural Economics Research, 2014; 6(22): 1-11.
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