Ensemble Weights-Based Geospatial Model for Optimal Allocation of Wind Turbines: A Case Study in Wasit, Iraq

Abstract

Accurate spatial decision-making models are increasingly needed for wind energy planning as the globe rushes towards carbon-neutral energy. This research aims to improve existing decision-making approaches by proposing an ensemble weight-based model for mapping the spatial suitability of onshore wind systems. The model addressed three weighting scenarios: subjective weighting derived from the Analytical Hierarchy Process (AHP), objective weighting derived from the Entropy Weighting Method (EWM), and Artificial Intelligence (AI) weighting based on real-world experiences. The weight sources were harnessed in weighted and fuzzy overlays in a GIS context to create multiple suitability indices. The model was applied to the Wasit governorate in Iraq, considering 10 evaluation criteria and 6 restrictions. The results highlight the dominance of techno-economic considerations, with wind speed being an important factor in all weighting scenarios. Suitability indices suggest that the western, central, and southern areas of Wasit are most suitable for wind farms, with ideal sites identified south of Al-Hay, south of Sheikh Saad, and west of Al-Kut, covering an area of 756 km2 and potentially providing more than 3.5 GW of clean electricity. The findings could encourage wind energy investment in developing countries like Iraq.