IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v229y2024ics0960148124007572.html
   My bibliography  Save this article

Location selection for solar power plants by using support vector machines: Adıyaman province, Turkey

Author

Listed:
  • Bostancı, Bülent
  • Kaynak, Tolga
  • Çapkurt, Zeynep

Abstract

The demand for natural resources and energy is increasing daily due to increasing trade and production opportunities resulting from population increase and globalization. The rising demand for energy and the uneven distribution of non-renewable energy have spurred a growing interest in renewable energy. Solar power has been preferred as a significant source of energy in power production in Turkey due to its geographical location, and this has brought the need for selecting suitable areas for the establishment of Solar Power Plants (SPP) in the provinces of the country that are rich in terms of solar power potential. The research focuses on identifying suitable areas for SPP in Adiyaman province, utilizing Geographical Information Systems (GIS) and Remote Sensing (RS). The spatial database incorporates 13 criteria affecting SPP establishment, and the study employs the Support Vector Machines (SVM) method for analysis. The results indicate that approximately 67 % of Adiyaman province is not suitable for SPP, while 8 % is deemed ideal at a moderate degree, 10 % is convenient, and 15 % is the most suitable. Establishing the SPPs planned in Adiyaman province in the most appropriate areas will ensure that more energy is obtained and significantly contribute to the province's economy, environment, and society.

Suggested Citation

  • Bostancı, Bülent & Kaynak, Tolga & Çapkurt, Zeynep, 2024. "Location selection for solar power plants by using support vector machines: Adıyaman province, Turkey," Renewable Energy, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:renene:v:229:y:2024:i:c:s0960148124007572
    DOI: 10.1016/j.renene.2024.120689
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124007572
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.120689?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:renene:v:229:y:2024:i:c:s0960148124007572. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.journals.elsevier.com/renewable-energy .

    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.