Long-term electricity demand forecast by combining interpretive-structural modeling methods and system dynamics

Electricity demand is continuously increasing in developed and developing countries. The accurate estimation of power consumption in the long-term horizon is of great importance for planning in the field of power generation and the management of the demand section. The use of a single model to forecast the consumption of all economic sectors leads to many errors, due to the different sectors consuming electricity in each country, as well as the difference in indicators and their changes in each sector. Hence, new research has highly considered the use of the decomposition approach of different consumer sectors. In this regard, identifying the fundamental factors of each sector and implementing the relationships between factors in an integrated platform for estimation are the two main issues in this area. The present study proposed a combination of interpretive-structural modeling and system dynamics (ISMSD). This method can evaluate scenarios and design policies to help decision makers. According to this methodology, Iran's electricity demand has been estimated as a developing country. The results of the evaluation highlighted the high accuracy of this method in prediction. Finally, the impact of energy subsidy targeting on Iran’s electricity demand was investigated in three scenarios.