Regional determination of social acceptance of renewable energy types in the transition to clean energy

In recent years, the world has made significant efforts to prevent the climate crisis. The transition to clean energy is one of the main ways to reduce carbon emissions in the energy sector. When planning renewable energy investments, considering the social acceptance factor along with technology and cost factors will support the timely and less problematic progress of investments and lead to correct policies. Therefore, defining social acceptance factors and their role is essential for regionalizing renewable energy types. While this problem can be addressed as multi-criteria decision-making using linguistic expressions, fuzzy set theory is the most appropriate approach for pairwise comparisons. This study proposes the Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) method to determine regional social acceptance rates that meet the defined criteria. The application was made for Turkey, which has significant regional differences, and the effects of regional differences were reflected with expert opinions and linguistic variables from each region. Regional differences were discussed, and their causes were investigated. In addition, the obtained results can play an important role in forming regional renewable energy investment policies.