Innovative GIS and Remote Sensing Approaches for Revealing Hidden Wind Energy Hotspots and Optimizing Wind Farm Siting

Ensuring a sustainable and renewable energy supply is a critical challenge for developing nations. This study aims to identify optimal locations for wind power development in the Kurdistan Region (KRG) of Iraq by integrating remote sensing, geographic information systems (GISs), and multicriteria decision-making (MCDM) techniques, including Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The results indicate that ~21% of the study area (8277 km²) demonstrates excellent and good potential for wind power generation, with a total estimated capacity exceeding 48,000 MW. Furthermore, 3332 sites with individual generation capacities of over 3 MW were identified, showcasing substantial opportunities for large-scale wind farm development. The analysis revealed wind speeds ranging from 7 to 14 m/s in the most suitable areas, ensuring optimal energy production. This research introduces a novel framework that integrates advanced spatial analysis with MCDM methods to optimize wind farm siting, considering critical factors such as wind resource assessment, site characteristics, environmental and social impacts, geotechnical constraints, and infrastructure availability. The findings suggest that the KRG has the potential to produce 42.9 TWh of electricity annually, which could save ~5.8 million tons of natural gas and reduce 16 million tons of CO₂ emissions each year. These results highlight the region’s potential to emerge as a regional hub for wind energy, contributing significantly to global efforts in reducing fossil fuel dependency and mitigating climate change. This study provides a robust scientific foundation for policymakers and planners, offering a comprehensive and accurate assessment of wind energy potential. By integrating multiple decision-making models and high-resolution spatial data, this research enhances the reliability and applicability of its findings, serving as a valuable tool for sustainable energy development.