Sustainable assessment of renewable energy microgrid architectures using a probabilistic hesitant fuzzy MCDM approach.

The selection of an optimal microgrid architecture is critical for advancing sustainable and resilient energy systems, particularly in remote or off-grid regions. This study introduces a novel hybrid multi-criteria decision-making (MCDM) framework that synergistically combines the Analytic Hierarchy Process (AHP) for determining criterion weights with the Additive Ratio Assessment (ARAS) method for ranking competing microgrid configurations. To effectively address the ambiguity and variability inherent in expert evaluations, the proposed model is embedded within the Probabilistic Pythagorean Hesitant Fuzzy Set (PPyHFS) environment. This allows for a nuanced representation of expert judgments by incorporating degrees of membership, non-membership, hesitation, and their associated probabilities. Seven distinct microgrid alternatives–ranging from conventional solar photovoltaic (PV) systems to advanced hybrid configurations such as hydrogen-integrated and pico-hydro models–are systematically evaluated against key sustainability criteria, including cost-effectiveness, operational reliability, environmental impact, scalability, and technological maturity. The integration of PPyHFS into the AHP–ARAS structure enhances decision-making robustness under uncertainty. Results identify the Hydrogen-based Microgrid as the most favorable configuration, followed by the Wind + Solar Hybrid and Solar PV + Biogas Hybrid systems. The proposed framework serves as a comprehensive and adaptable decision-support tool for energy planners, engineers, and policymakers engaged in the design and deployment of next-generation sustainable microgrid solutions.