Sustainable Renewable Energy Portfolio Selection Under Uncertainty: A Fuzzy AHP-TOPSIS Model
The transition to renewable energy sources is fundamental to achieving sustainable development goals and addressing climate change. However, selecting the optimal renewable energy portfolio remains a complex decision problem involving multiple conflicting criteria under conditions of uncertainty. Despite the growing adoption of MCDM methods, comprehensive frameworks integrating uncertainty handling with multi-dimensional sustainability assessment remain limited. This study develops a hybrid multi-criteria decision-making framework integrating Fuzzy Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution for renewable energy portfolio selection. The Fuzzy AHP method is employed to determine criteria weights under uncertainty, while TOPSIS ranks alternative energy sources. The framework encompasses economic, environmental, technical, and social dimensions to ensure comprehensive sustainability assessment. The findings contribute to green economics literature by providing a systematic decision-support tool for energy planners and policymakers, enabling more informed and transparent renewable energy investment decisions.