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https://hdl.handle.net/11499/4837
Title: | Forecasting total and industrial sector electricity demand based on genetic algorithm approach: Turkey case study | Authors: | Öztürk, Harun Kemal Ceylan, Halim |
Keywords: | Electricity consumption Electricity projection Genetic algorithm Turkey's electricity Economics Electric power utilization Error analysis Genetic algorithms Mathematical models Project management Genetic algorithm electricity demand model Gross national product Electric load management electricity Eastern Hemisphere Eurasia Turkey World |
Abstract: | 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 algorithm 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 © 2005 John Wiley & Sons, Ltd. | URI: | https://hdl.handle.net/11499/4837 https://doi.org/10.1002/er.1092 |
ISSN: | 0363-907X |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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