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Prediction of Iran's annual electricity demand: Artificial intelligence approaches
, Article 11th International Conference on Innovations in Information Technology, 1 November 2015 through 3 November 2015 ; 2015 , Pages 373-377 ; 9781467385114 (ISBN) ; Jalili, M ; Davari, H ; Maknoon, R ; Ismail L ; GE Software; IBM; UAE University (UAEU) ; Sharif University of Technolgoy
Institute of Electrical and Electronics Engineers Inc
Abstract
Accurate prediction of electricity demand is essential for planning, policy making and resource allocation in national level. In this manuscript, we applied a number of artificial intelligence methods to predict macro-scale electricity consumption rates in Iran. To this end, three socio-economic and three environmental factors were considered as inputs to the prediction models. We used data for the period 1967-2013 in order to predict the power demand in the years 2014-2018. Experimental results showed that the path coefficient analysis model with linear coefficients had the best performance among the models considered in this study. The outcome of this research can help the policy makers to...