Abstract
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 differ- ent 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 (1967-2006) and partly for testing the models (2007-2010). 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
Highlights
The world is in an unstable condition in the area of energy consumption and production (Oecd/Iea 2014)
Our results show that particle swarm optimization energy demand (PSO-DEM) exponential model with inputs & Aliyeh Kazemi aliyehkazemi@ut.ac.ir & Mahboobeh Nazari nazari1980azar@yahoo.com; ma.nazar@avicenna.ac.ir
This study presents the application of the PSO and GA methods for estimation and prediction of energy demand in residential and commercial sectors in Iran
Summary
The world is in an unstable condition in the area of energy consumption and production (Oecd/Iea 2014). Iran’s four main energy-consuming sectors include: transport, industry, residential–commercial and agriculture; the consumption rates of each of these four sectors according to 2012 balance sheet of Iran were 47.6, 48.2, 64.4 and 7.5 million tons of crude oil equivalent, respectively (Moe [3]). Consumed energies in the residential and commercial sectors include: crude oil and oil productions, natural gas, coal, combustible renewable resources and electricity; the consumption rate for each sector has been computed to be 8.39, 46.13, 0.01, 1.31 and 8.58, respectively. These values show a 9.5 % growth. The nonlinear indices on the one hand and the demand for energy on the other hand have triggered the process of seeking intelligent solutions such as genetic algorithm, particle swarm optimization algorithm, fuzzybased regression and neural networks [6]
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