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<p>In response to global energy depletion, this study addresses the critical challenge of selecting optimal wind farm sites in Kuwait, a key pillar of the “New Kuwait” 2035 vision for 15% renewable energy integration. A robust, hybrid Multi-Criteria Decision-Making (MCDM) framework was developed, integrating Fuzzy Analytical Hierarchy Process (FAHP) with Entropy-based objective weighting and Type-2 Fuzzy logic within a GIS environment. This approach effectively mitigates expert subjectivity and manages the high “Footprint of Uncertainty” inherent in complex desert environments. Twenty-six technical, environmental, and socioeconomic criteria—including wind power density, proximity to the national grid, and oil field restrictions—were analyzed at a modern utility-scale hub height of 100 m. The spatial results identified approximately 1444 km² (8.6%) of Kuwait’s territory as ' Highly Suitable’ for wind development, primarily concentrated in the western (Al-Jahra) and northern (Al-Abali) corridors. Validation against existing Shagaya Renewable Energy Park and Global Wind Atlas data confirmed a strong spatial correlation (R<sup>2</sup> = 0.84). The identified zones represent a potential generation capacity of 2500&#xa0;MW, providing a data-driven roadmap for national energy planners to meet sustainability targets while minimizing land-use conflicts with oil production and urban expansion.</p>

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Integrating fuzzy AHP and geo-spatial modeling for wind farm suitability assessment in Kuwait

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月3日

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  • Mohamed A. Atalla,
  • Ayad M. Fadhil Al-Quraishi,
  • Elsayed A. Badawy Ataalla,
  • Ali Shebl,
  • Árpád Csámer,
  • Wael M. Al-Metwaly

摘要

In response to global energy depletion, this study addresses the critical challenge of selecting optimal wind farm sites in Kuwait, a key pillar of the “New Kuwait” 2035 vision for 15% renewable energy integration. A robust, hybrid Multi-Criteria Decision-Making (MCDM) framework was developed, integrating Fuzzy Analytical Hierarchy Process (FAHP) with Entropy-based objective weighting and Type-2 Fuzzy logic within a GIS environment. This approach effectively mitigates expert subjectivity and manages the high “Footprint of Uncertainty” inherent in complex desert environments. Twenty-six technical, environmental, and socioeconomic criteria—including wind power density, proximity to the national grid, and oil field restrictions—were analyzed at a modern utility-scale hub height of 100 m. The spatial results identified approximately 1444 km² (8.6%) of Kuwait’s territory as ' Highly Suitable’ for wind development, primarily concentrated in the western (Al-Jahra) and northern (Al-Abali) corridors. Validation against existing Shagaya Renewable Energy Park and Global Wind Atlas data confirmed a strong spatial correlation (R2 = 0.84). The identified zones represent a potential generation capacity of 2500 MW, providing a data-driven roadmap for national energy planners to meet sustainability targets while minimizing land-use conflicts with oil production and urban expansion.