Energy demand estimation based on two-different genetic algorithm approaches

被引：51

作者：

Canyurt, OE

Ceylan, H

Ozturk, HK

Hepbasli, A ^{[1
]}

机构：

[1] Ege Univ, Fac Engn, Dept Mech Engn, TR-35100 Izmir, Turkey

[2] Pamukkale Univ, Fac Engn, Dept Mech Engn, Camlik, Denizli, Turkey

来源：

ENERGY SOURCES | 2004年 / 26卷 / 14期

关键词：

energy; energy demand; energy modeling; energy planning; future projections; genetic algorithm; Turkey;

D O I：

10.1080/00908310490441610

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Energy modeling is a subject of widespread current interest among engineers and scientists concerned with problems of energy production and consumption. Energy planning is not possible without a reasonable knowledge of past and present energy consumption and likely future demands. In this study, two forms of the energy demand equations are developed in order to improve energy demand estimation efficiency for future projections based on the genetic algorithm (GA) notion. The genetic algorithm energy demand (GAEDM) model is used to estimate Turkey's future energy demand based on gross domestic product, population, import, and export figures. Both equations proposed here are non-linear, of which one is exponential and the other is quadratic. The quadratic form of the GAEDM model provided a slightly better fit solution to the observed data and can be used with a high correlation coefficient for Turkey's future energy projections. It is expected that this study will be helpful in developing highly applicable and productive planning for energy policies.

引用

页码：1313 / 1320

页数：8