Long Term Electricity Demand Forecasting in Turkey Using Artificial Neural Networks

被引：39

作者：

Cunkas, M. ^{[1
]}

Altun, A. A. ^{[1
]}

机构：

[1] Selcuk Univ, Dept Elect & Comp Educ, Konya, Turkey

来源：

ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY | 2010年 / 5卷 / 03期

关键词：

artificial neural networks; economic factors; load forecasting; Turkey; ENERGY DEMAND;

D O I：

10.1080/15567240802533542

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 article presents an approach for Turkey's long-term electricity demand forecasting. Two Artificial Neural Network structures, three-layered back-propagation and a recurrent neural network are designed and tested for this purpose. Predictions are done for the years 2008 to 2014. Since long-term forecasting is mainly influenced by economic factors, this study focuses on economic data. The proposed approach produces lower percent errors, especially in the recurrent neural network. The forecast results by artificial neural networks are also compared with official forecasts.

引用

页码：279 / 289

页数：11

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