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

Abstract

Abstract 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 2  = 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.