Energy supply security is one of the strategic issues of all states. In Iran, about 35 % of the total energy is consumed by the residential and commercial sectors. According to the importance of residential and commercial sectors in energy consumption, this paper develops different models to analyze energy demand of residential and commercial sectors. The GA and PSO energy demand estimation models (GA-DEM, PSO-GEM), a suitable model for this study, is used to estimate future energy demand of the sectors. Energy demand of these sectors has been estimated in two various forms, exponential and linear models. These sectors consumption in Iran from 1967 to 2010 is considered as the case of this study. The available data are partly used for finding the optimal, or near-optimal values of the coefficient parameters and partly for testing the models (2007)(2008)(2009)(2010). Our results show that PSO-DEM exponential model with inputs including, value added of all economic sectors, value of made buildings, the population and the electrical and fuel appliance price index using the mean absolute percentage error on test data is the most suitable model. Finally, based on the best scenario, the energy demand of residential and commercial sectors is estimated 1718 mega barrel of crude oil equivalent (MBOE) (1 barrel = 0.159 m 3 ) up to the year 2032.

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Energy supply security is one of the strategic issues of all states. Beside the energy supply management, the section that has received less attention is energy demand management. According to importance of residential and commercial sectors in energy consumption, in the present study energy demand of these sectors is estimated using linear and exponential functions and the coefficients are obtained from PSO algorithms. 72 different scenarios with various inputs are investigated. Data from the years 1968 to 2011 are used to develop the models and select the suitable scenario. Results show that an exponential model developed based on particle swarm optimization algorithm has had the best performance. Based on the best scenario the energy demand of residential and commercial sectors is estimated 1718 Mega barrel of crude oil equivalent up to the year 2032.

Purpose This paper aims to select the best scenario for energy demand forecast of residential and commercial sectors in Iran by using particle swarm optimization algorithm. Design/methodology/approach In this study, using variables affecting energy demand of residential and commercial sectors in Iran, the future status of energy demand in these sectors is predicted. Using the particle swarm optimization algorithm, both linear and exponential forms of energy demand equations were studied under 72 different scenarios with various variables. The data from 1968 to 2011 were applied for model development and the appropriate scenario choice. Findings An exponential model with inputs including total value added minus that of the oil sector, value of made buildings, total number of households and consumer energy price index is the most suitable model. Finally, energy demand of residential and commercial sectors is estimated up to the year 2032. Results show that the energy demand of the sectors will achieve a level of about 1,718 million barrels of oil equivalent per year by 2032. Originality/value To the best of our knowledge in this study a suitable model is selected for energy demand forecast of residential and commercial sectors by evaluation of various models with different variables as inputs.