Search published articles


Showing 1 results for Zolfaghari

Hossein Sadeghi, Mahdi Zolfaghari , Mohamad Heydarizade,
Volume 22, Issue 1 (IJIEPR 2011)
Abstract

  This paper aimed at estimation of the per capita consumption of electricity in residential sector based on economic indicators in Iran. The Genetic Algorithm Electricity Demand Model (GAEDM) was developed based on the past data using the genetic algorithm approach (GAA). The economic indicators used during the model development include: gross domestic product (GDP) in terms of per capita and real price of electricity and natural gas in residential sector. Three forms of GAEDM were developed to estimate the electricity demand. The developed models were validated with actual data, and the best estimated model was selected on base of evaluation criteria. The results showed that the exponential form had more precision to estimate the electricity demand than two other models. Finally, the future estimation of electricity demand was projected between 2009 and 2025 by three forms of the equations linear, quadratic and exponential under different scenarios .



Page 1 from 1     

© 2019 All Rights Reserved | International Journal of Industrial Engineering & Production Research

Designed & Developed by : Yektaweb