Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach
AbstractThis paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Energy Policy.
Volume (Year): 38 (2010)
Issue (Month): 5 (May)
Contact details of provider:
Web page: http://www.elsevier.com/locate/enpol
Electricity demand Turkey Fuzzy logic;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Sanders, I. & Batty, W. J. & Probert, S. D. & Hagino, K. & Aida, S., 1993. "Supply of, and demand for, a resource: Fuzzy logistical optimisation technique," Applied Energy, Elsevier, vol. 46(4), pages 285-302.
- Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
- Erdogdu, Erkan, 2007.
"Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey,"
Elsevier, vol. 35(2), pages 1129-1146, February.
- Erdogdu, Erkan, 2007. "Electricity Demand Analysis Using Cointegration and ARIMA Modelling: A case study of Turkey," MPRA Paper 19099, University Library of Munich, Germany.
- Tunc, Murat & Camdali, Unal & Parmaksizoglu, Cem, 2006. "Comparison of Turkey's electrical energy consumption and production with some European countries and optimization of future electrical power supply investments in Turkey," Energy Policy, Elsevier, vol. 34(1), pages 50-59, January.
- Yoo, Seung-Hoon & Kwak, So-Yoon, 2010. "Electricity consumption and economic growth in seven South American countries," Energy Policy, Elsevier, vol. 38(1), pages 181-188, January.
- Akay, Diyar & Atak, Mehmet, 2007. "Grey prediction with rolling mechanism for electricity demand forecasting of Turkey," Energy, Elsevier, vol. 32(9), pages 1670-1675.
- Mahadevan, Renuka & Asafu-Adjaye, John, 2007. "Energy consumption, economic growth and prices: A reassessment using panel VECM for developed and developing countries," Energy Policy, Elsevier, vol. 35(4), pages 2481-2490, April.
- Hamzacebi, Coskun, 2007. "Forecasting of Turkey's net electricity energy consumption on sectoral bases," Energy Policy, Elsevier, vol. 35(3), pages 2009-2016, March.
- Serhat, Kucukali, 2011. "Risk assessment of river-type hydropower plants using fuzzy logic approach," Energy Policy, Elsevier, vol. 39(10), pages 6683-6688, October.
- Mondal, Md. Alam Hossain & Boie, Wulf & Denich, Manfred, 2010. "Future demand scenarios of Bangladesh power sector," Energy Policy, Elsevier, vol. 38(11), pages 7416-7426, November.
- Rentizelas, Athanasios & Georgakellos, Dimitrios, 2014. "Incorporating life cycle external cost in optimization of the electricity generation mix," Energy Policy, Elsevier, vol. 65(C), pages 134-149.
- Zhu, Suling & Wang, Jianzhou & Zhao, Weigang & Wang, Jujie, 2011. "A seasonal hybrid procedure for electricity demand forecasting in China," Applied Energy, Elsevier, vol. 88(11), pages 3807-3815.
- Zhao, Weigang & Wang, Jianzhou & Lu, Haiyan, 2014. "Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model," Omega, Elsevier, vol. 45(C), pages 80-91.
- Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.