IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v241y2025ics0960148125000023.html
   My bibliography  Save this article

Integrating remote sensing, GIS, and multi-criteria decision making for assessing PV potential in mountainous regions

Author

Listed:
  • Feng, Xiaofan
  • Zhang, Zhengjia
  • Chen, Qi
  • Guo, Zhiling
  • Zhang, Haoran
  • Wang, Mengmeng
  • Gao, Wei
  • Liu, Xiuguo

Abstract

Installing photovoltaic (PV) facilities in mountainous areas can address the challenge of land scarcity in PV development, improve the energy structure, and promote economic growth in rural mountainous regions. In this study, a framework was proposed to assess the feasibility and generation potential of solar PV in mountainous areas by remote sensing (RS), geographic information systems (GIS), and multi-criteria decision-making (MCDM) model. Climatic, geographic, policy, and social factors were integrated into the optimal site selection for PV facilities construction based on the characteristics of mountainous regions. The weight of each criterion was calculated using the ordinal priority approach (OPA) for subsequent land suitability assessment. Furthermore, the impact of ecological and land use policies on the optimal site selection for solar PV power stations have been considered in the proposed framework. The method was applied in Yongren County, Yunnan Province. The study results show that the optimal areas for the construction of PV plants within Yongren County is 85.45 km2. The identified location aligns seamlessly with the current PV facilities, affirming the effectiveness of the approach. Additionally, the estimated power generation potential of the optimal areas is 665 million kWh, which can satisfy the electricity demands of Chuxiong Prefecture. The levelized cost of electricity (LCOE) is 0.3963 RMB/kWh. This work will provide valuable support for the construction of PV power plants in mountainous areas, which will be crucial in reducing carbon emissions and increasing the share of clean energy.

Suggested Citation

  • Feng, Xiaofan & Zhang, Zhengjia & Chen, Qi & Guo, Zhiling & Zhang, Haoran & Wang, Mengmeng & Gao, Wei & Liu, Xiuguo, 2025. "Integrating remote sensing, GIS, and multi-criteria decision making for assessing PV potential in mountainous regions," Renewable Energy, Elsevier, vol. 241(C).
  • Handle: RePEc:eee:renene:v:241:y:2025:i:c:s0960148125000023
    DOI: 10.1016/j.renene.2025.122340
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148125000023
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2025.122340?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:241:y:2025:i:c:s0960148125000023. 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.