The energy demand estimation for Turkey using differential evolution algorithm

被引:0
作者
MEHMET BESKIRLI
HUSEYIN HAKLI
HALIFE KODAZ
机构
[1] Selcuk University,Department of Computer Engineering
来源
Sādhanā | 2017年 / 42卷
关键词
Differential evolution algorithm; optimization; energy demand; estimation; Turkey;
D O I
暂无
中图分类号
学科分类号
摘要
The energy demand estimation commands great importance for both developing and developed countries in terms of the economy and country resources. In this study, the differential evolution algorithm (DE) was used to forecast the long-term energy demand in Turkey. In addition to being employed for solving regular optimization problems, DE is also a global, meta-heuristic algorithm that enables fast, reliable and operative stochastic searches based on population. Considering the correlation between the increase in certain economic indicators in Turkey and the increase of energy consumption, two equations were used—one applying the linear form and the other the quadratic form. Turkey’s long-term energy demand from 2012 to 2031 was estimated through the DE method in three different scenarios and in terms of the gross domestic product, import, export and population. To prove the success of the DE method in addressing the energy demand problem, the DE method was compared to other methods found in the literature. Results showed that the proposed DE method was more successful than the other methods. Furthermore, the future projections of energy demand obtained using the proposed method were compared to the indicators of energy demand estimated and observed by the Ministry of Energy and Natural Resources.
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页码:1705 / 1715
页数:10
相关论文
共 88 条
[1]  
Erdogdu E(2007)Electricity demand analysis using cointegration and ARIMA modelling: a case study of Turkey Energy Policy 35 1129-1146
[2]  
Kıran MS(2012)A novel hybrid approach based on particle swarm optimization and ant colony algorithm to forecast energy demand of Turkey Energy Convers. Manage. 53 75-83
[3]  
Özceylan E(2008)Improvement of energy demand forecasts using swarm intelligence: the case of Turkey with projections to 2025 Energy Policy 36 1937-1944
[4]  
Gündüz M(2007)ARIMA forecasting of primary energy demand by fuel in Turkey Energy Policy 35 1701-1708
[5]  
Paksoy T(2002)Forecasting the primary energy demand in Turkey and analysis of cyclic patterns Energy Convers. Manage. 43 473-487
[6]  
Ünler A(2004)Electric energy demand of Turkey for the year 2050 Energy Sources 26 1157-1164
[7]  
Ediger VŞ(2016)Forecasting Turkey’s natural gas consumption by using time series methods Eur. J. Econ. Polit. Stud. 3 1-21
[8]  
Akar S(2009)Turkey’s energy demand Curr. Res. J. Soc. Sci. 1 123-128
[9]  
Ediger VŞ(2011)Industrial electricity demand for Turkey: a structural time series analysis Energy Econ. 33 426-436
[10]  
Tatlıdil H(2007)Prospects for future projections of the basic energy sources in Turkey Energy Sources Part B 2 183-201