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Suitability of Photovoltaic Power Station Sites Based on Particle Swarm Optimization Model of Fuzzy Hierarchical Analysis—Taking Qujing City of Yunnan Province as Example

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  • Fangbin Zhou

    (School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China
    Engineering Laboratory of Special Information Technology of Highway Geological Disaster Early Warning in Hunan Province, Changsha University of Science & Technology, Changsha 410114, China)

  • Yun Xiao

    (School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China)

  • Tianyi Yao

    (School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China)

  • Feng Xie

    (School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China)

  • Junwei Bian

    (School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China)

Abstract

With the global shift in energy systems and the growing adoption of renewable energy, photovoltaic power generation has become widely implemented worldwide as a clean and efficient energy source. Therefore, scientific and rational locating methods for photovoltaic power stations has become essential. This study employs a particle swarm optimization (PSO) model based on the fuzzy analytic hierarchy process (FAHP) for evaluating the site-suitability of photovoltaic power stations. Taking Qujing City in Yunnan Province as an example, this study comprehensively considered 13 factors in three categories: meteorology, physical geography, and location. In addition, such topographic factors as planar curvature, profile curvature, and LSW were added to the physical geography factors for consideration. In previous studies, less attention has been paid to these factors. Spatial analysis and data integration of influencer factors in the study area were carried out in geographic information system (GIS) technology, with weights assigned for each factor in combination with a fuzzy analytic hierarchy process, but a low consistency effect was delivered. To optimize the consistency effect, the particle swarm optimization algorithm was introduced, and weights with good consistency effects were obtained. Based on such weights, the suitability evaluation was carried out to select photovoltaic power stations. The evaluation results were compared with those obtained from the fuzzy analytic hierarchy process and the genetic algorithm (GA) optimization model based on FAHP and were further verified in the area of the photovoltaic power stations built. It is demonstrated that the accuracy rate of the suitability of Qujing photovoltaic power station site selection based on the particle swarm optimization model of the fuzzy analytic hierarchy process was the highest at 99.3%.

Suggested Citation

  • Fangbin Zhou & Yun Xiao & Tianyi Yao & Feng Xie & Junwei Bian, 2025. "Suitability of Photovoltaic Power Station Sites Based on Particle Swarm Optimization Model of Fuzzy Hierarchical Analysis—Taking Qujing City of Yunnan Province as Example," Energies, MDPI, vol. 18(5), pages 1-22, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:5:p:1124-:d:1599255
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    References listed on IDEAS

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    1. Gherboudj, Imen & Ghedira, Hosni, 2016. "Assessment of solar energy potential over the United Arab Emirates using remote sensing and weather forecast data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1210-1224.
    2. Al Garni, Hassan Z. & Awasthi, Anjali, 2017. "Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia," Applied Energy, Elsevier, vol. 206(C), pages 1225-1240.
    3. Benalcazar, Pablo & Komorowska, Aleksandra & Kamiński, Jacek, 2024. "A GIS-based method for assessing the economics of utility-scale photovoltaic systems," Applied Energy, Elsevier, vol. 353(PA).
    4. Ghasemi, Golara & Noorollahi, Younes & Alavi, Hamed & Marzband, Mousa & Shahbazi, Mahmoud, 2019. "Theoretical and technical potential evaluation of solar power generation in Iran," Renewable Energy, Elsevier, vol. 138(C), pages 1250-1261.
    5. Raza, Muhammad Ali & Yousif, Muhammad & Hassan, Muhammad & Numan, Muhammad & Abbas Kazmi, Syed Ali, 2023. "Site suitability for solar and wind energy in developing countries using combination of GIS- AHP; a case study of Pakistan," Renewable Energy, Elsevier, vol. 206(C), pages 180-191.
    6. Islam, Md. Rabiul & Aziz, Md. Tareq & Alauddin, Mohammed & Kader, Zarjes & Islam, Md. Rakibul, 2024. "Site suitability assessment for solar power plants in Bangladesh: A GIS-based analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) approach," Renewable Energy, Elsevier, vol. 220(C).
    7. Aly, Ahmed & Jensen, Steen Solvang & Pedersen, Anders Branth, 2017. "Solar power potential of Tanzania: Identifying CSP and PV hot spots through a GIS multicriteria decision making analysis," Renewable Energy, Elsevier, vol. 113(C), pages 159-175.
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