The estimation of the electricity energy demand using particle swarm optimization algorithm: A case study of Turkey

Energy is the most important factor in improving the quality of life and advancing the economic and social progress. Demographic changes directly affect the energy demand. At present the world's population is growing quickly. As of 2015, it was estimated at 7.3 billion. The population and the export of Turkey have been increasing for two decades. Consequently, electricity energy demand of Turkey has been increasing rapidly. This study aims to predict the future electricity energy demand of Turkey. In this paper, the prediction of the electricity demand of Turkey is modeled by using particle swarm optimization algorithm. The data of the gross domestic product, population, import and export are used as input data of the proposed model in the experiments. The GDP, import and export data are taken from the annual reports of the Turkish Ministry of Finance. The population data are taken from the Turkish Statistical Institute. The electricity demand data are taken from the Turkish Electricity Transmission Company. The statistical method R2 and adjusted-R2 are used as the performance criteria. The experimental results show that the generated model is very efficient.