Forecasting total and industrial sector electricity demand based on genetic algorithm approach: Turkey case study

被引:30
作者
Ozturk, HK [1 ]
Ceylan, H [1 ]
机构
[1] Pamukkale Univ, Fac Engn, TR-20017 Denizli, Turkey
关键词
electricity consumption; electricity projection; genetic algorithm; Turkey's electricity;
D O I
10.1002/er.1092
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
This study deals with estimation of the total and industrial sector electricity consumption based on genetic algorithm (GA) approach, and then proposes two scenarios to project future consumptions. Total electricity consumption is estimated based on gross national product (GNP), population, import and export figures of Turkey. Industrial sector electricity is calculated based on the GNP, import and export figures. Three forms of the genetic algorithin electricity demand (GAED) models for the total and two forms for the industrial electricity consumption are developed. The best-fit GAED model in terms of total minimum relative average errors between observed and estimated values is selected for future demand estimation. 'High- and low-growth scenarios' are proposed for predicting the future electricity consumption. Results showed that the GAED estimates the electricity demand in comparison with the other electricity demand projections. The GAED model plans electricity demand of Turkey until 2020. Copyright (c) 2005 John Wiley & Sons, Ltd.
引用
收藏
页码:829 / 840
页数:12
相关论文
共 30 条
[1]  
[Anonymous], 1989, GENETIC ALGORITHM SE
[2]  
[Anonymous], 1996, DEVEL THEORE APPL ME
[3]  
[Anonymous], ADAPTATIONS NATURAL
[4]   Forecasting loads and prices in competitive power markets [J].
Bunn, DW .
PROCEEDINGS OF THE IEEE, 2000, 88 (02) :163-169
[5]   Energy demand estimation based on two-different genetic algorithm approaches [J].
Canyurt, OE ;
Ceylan, H ;
Ozturk, HK ;
Hepbasli, A .
ENERGY SOURCES, 2004, 26 (14) :1313-1320
[6]   Estimating energy demand of Turkey based on economic indicators using genetic algorithm approach [J].
Ceylan, H ;
Ozturk, HK .
ENERGY CONVERSION AND MANAGEMENT, 2004, 45 (15-16) :2525-2537
[7]   Traffic signal timing optimisation based on genetic algorithm approach, including drivers' routing [J].
Ceylan, H ;
Bell, MGH .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2004, 38 (04) :329-342
[8]  
CEYLAN H, 2003, 1 INT EN EX ENV S, P527
[9]   A study of sectoral energy consumption in Hong Kong (1984-97) with special emphasis on the household sector [J].
Chow, LCH .
ENERGY POLICY, 2001, 29 (13) :1099-1110
[10]  
Dincer I, 1997, INT J ENERG RES, V21, P153, DOI 10.1002/(SICI)1099-114X(199702)21:2<153::AID-ER227>3.0.CO