IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v35y2007i3p2009-2016.html
   My bibliography  Save this article

Forecasting of Turkey's net electricity energy consumption on sectoral bases

Author

Listed:
  • Hamzacebi, Coskun

Abstract

No abstract is available for this item.

Suggested Citation

  • Hamzacebi, Coskun, 2007. "Forecasting of Turkey's net electricity energy consumption on sectoral bases," Energy Policy, Elsevier, vol. 35(3), pages 2009-2016, March.
    • Handle: RePEc:eee:enepol:v:35:y:2007:i:3:p:2009-2016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(06)00142-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Madlener, Reinhard & Kumbaroglu, Gurkan & Ediger, Volkan S., 2005. "Modeling technology adoption as an irreversible investment under uncertainty: the case of the Turkish electricity supply industry," Energy Economics, Elsevier, vol. 27(1), pages 139-163, January.
    2. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    3. Sözen, Adnan & Arcaklioglu, Erol & Özkaymak, Mehmet, 2005. "Turkey's net energy consumption," Applied Energy, Elsevier, vol. 81(2), pages 209-221, June.
    4. 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.
    5. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Akay, Diyar & Atak, Mehmet, 2007. "Grey prediction with rolling mechanism for electricity demand forecasting of Turkey," Energy, Elsevier, vol. 32(9), pages 1670-1675.
    2. ToksarI, M. Duran, 2009. "Estimating the net electricity energy generation and demand using the ant colony optimization approach: Case of Turkey," Energy Policy, Elsevier, vol. 37(3), pages 1181-1187, March.
    3. Kucukali, Serhat & Baris, Kemal, 2010. "Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach," Energy Policy, Elsevier, vol. 38(5), pages 2438-2445, May.
    4. Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
    5. Zeng, Yu-Rong & Zeng, Yi & Choi, Beomjin & Wang, Lin, 2017. "Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network," Energy, Elsevier, vol. 127(C), pages 381-396.
    6. Huang, Runya & Huang, Guohe & Cheng, Guanhui & Dong, Cong, 2017. "Regional heuristic interval recourse power system analysis for electricity and environmental systems planning in Eastern China," Resources, Conservation & Recycling, Elsevier, vol. 122(C), pages 185-201.
    7. Leung, Philip C.M. & Lee, Eric W.M., 2013. "Estimation of electrical power consumption in subway station design by intelligent approach," Applied Energy, Elsevier, vol. 101(C), pages 634-643.
    8. Laha, Priyanka & Chakraborty, Basab, 2017. "Energy model – A tool for preventing energy dysfunction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 95-114.
    9. 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.
    10. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    11. Nathalie Spittler & Ganna Gladkykh & Arnaud Diemer & Brynhildur Davidsdottir, 2019. "Understanding the Current Energy Paradigm and Energy System Models for More Sustainable Energy System Development," Post-Print hal-02127724, HAL.
    12. Pye, Steve & Sabio, Nagore & Strachan, Neil, 2015. "An integrated systematic analysis of uncertainties in UK energy transition pathways," Energy Policy, Elsevier, vol. 87(C), pages 673-684.
    13. Santos, Lúcia & Soares, Isabel & Mendes, Carla & Ferreira, Paula, 2014. "Real Options versus Traditional Methods to assess Renewable Energy Projects," Renewable Energy, Elsevier, vol. 68(C), pages 588-594.
    14. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    15. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    16. Ghiassi, M. & Saidane, H. & Zimbra, D.K., 2005. "A dynamic artificial neural network model for forecasting time series events," International Journal of Forecasting, Elsevier, vol. 21(2), pages 341-362.
    17. Barrow, Devon K., 2016. "Forecasting intraday call arrivals using the seasonal moving average method," Journal of Business Research, Elsevier, vol. 69(12), pages 6088-6096.
    18. Jani, D.B. & Mishra, Manish & Sahoo, P.K., 2017. "Application of artificial neural network for predicting performance of solid desiccant cooling systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 352-366.
    19. Nataša Glišović & Miloš Milenković & Nebojša Bojović & Libor Švadlenka & Zoran Avramović, 2016. "A hybrid model for forecasting the volume of passenger flows on Serbian railways," Operational Research, Springer, vol. 16(2), pages 271-285, July.
    20. Ghatrehsamani, Shirin & Ebrahimi, Rahim & Kazi, Salim Newaz & Badarudin Badry, Ahmad & Sadeghinezhad, Emad, 2016. "Optimization model of peach production relevant to input energies – Yield function in Chaharmahal va Bakhtiari province, Iran," Energy, Elsevier, vol. 99(C), pages 315-321.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:35:y:2007:i:3:p:2009-2016. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.