Annual Electricity Demand Prediction for Iranian Agriculture Sector Using ANN and PSO

Abstract

In this study, we used PSO algorithm and ANN to predict annual electricity consumption in Iranian agriculture sector. The economic indicators used in this paper are price, value added, number of customers and consumption in the previous periods. To predict the future values, a linear- logarithmic model of electrical energy demand is considered. The PSO algorithm applied in this study has been tuned for all its parameters and the best coefficients with minimum error are identified, while all parameter values are tested concurrently. Consumption in the previous periods has been used for testing estimated model. The estimation errors of PSO algorithm are less than that of estimated by genetic algorithm and regression method. In addition, ANN is used to forecast each independent variable and then electricity consumption is forecasted up to year 2010. Electricity consumption in Iranian agriculture sector from 1981 to 2005 is considered as the case for this study.