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The 9th International Energy Conference
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:: Volume 21, Issue 2 (7-2018) ::
IJE 2018, 21(2): 121-144 Back to browse issues page
Comparative Analysis of Short-Term Price Forecasting Models: Iran Electricity Market
Davood Manzoor * , Mahdi Ghaemi-Asl , Ahmad Norouzi
Imam Sadiq University , manzoor@isu.ac.ir
Abstract:   (3127 Views)
As the electricity industry has changed and became more competitive, the electricity price forecasting has become more important. Investors need to estimate future prices in order to take proper strategy to maintain their market share and to maximize their profits. In the economic paradigm, this goal is pursued using econometric models. The validity of these models is judged by their forecasting errors. This paper is an effort to compare the forecasting power of Artificial Neural Network (ANN), Genetic Algorithm (GA) and ARIMA models for hourly electricity prices in Iran electricity market. According to the results, ANNs has the best forecasting performance followed by GA in the second place and ARIMA model in the third place.
Keywords: Iran electricity market, Price forecasting, Time series, Neural Networks, Genetic Algorithm
Full-Text [PDF 1926 kb]   (661 Downloads)    
Type of Study: Research | Subject: Restructure , Privatization and Power Marketing
Received: 2019/04/19 | Accepted: 2019/07/12 | Published: 2019/07/12
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Manzoor D, Ghaemi-Asl M, Norouzi A. Comparative Analysis of Short-Term Price Forecasting Models: Iran Electricity Market. IJE 2018; 21 (2) :121-144
URL: http://necjournals.ir/article-1-1436-en.html


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Volume 21, Issue 2 (7-2018) Back to browse issues page
نشریه انرژی ایران Iranian Journal of Energy
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