EconPapers    
Economics at your fingertips  
 

Electricity estimation using genetic algorithm approach: a case study of Turkey

Harun Kemal Ozturk, Halim Ceylan, Olcay Ersel Canyurt and Arif Hepbasli

Energy, 2005, vol. 30, issue 7, 1003-1012

Abstract: This paper describes the use of stochastic search processes that are the basis of genetic algorithms (GAs), in developing Turkey's electric energy estimation. The industrial sector electricity consumptions and the totals are estimated, based on the basic indicators of the gross national product, population, import and export figures. Two different non-linear estimation models are developed using GA. Developed models are validated with actual data, while future estimation of electricity demand is projected between 2002 and 2025. It may be concluded that the both GAs can possibly be applied to estimate electric energy consumption.

Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (43)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544204003391
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:30:y:2005:i:7:p:1003-1012

DOI: 10.1016/j.energy.2004.08.008

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:30:y:2005:i:7:p:1003-1012