DocumentCode
3730206
Title
Prediction of Iran´s annual electricity demand: Artificial intelligence approaches
Author
Homayoun Hamed Moghadam Rafati;Mahdi Jalili;Hamed Davari;Reza Maknoon
Author_Institution
Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
fYear
2015
Firstpage
373
Lastpage
377
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 better understand the mark needs.
Keywords
"Biological system modeling","Sociology","Predictive models","Mathematical model","Training","Principal component analysis"
Publisher
ieee
Conference_Titel
Innovations in Information Technology (IIT), 2015 11th International Conference on
Print_ISBN
978-1-4673-8509-1
Type
conf
DOI
10.1109/INNOVATIONS.2015.7381570
Filename
7381570
Link To Document