Effective hydropower renewable energy source selection using fuzzy neutrosophic boundary approximate area

Abstract

Small hydropower plants in rural areas are contributing to marginal economic growth and social progress, but their social sustainability assessment is under-studied. Previous studies have shown that no single renewable energy source (RES) can fully meet all sustainability criteria, despite their focus on single-user systems. Scaled renewable energy systems have varying impacts across different systems, involving technical, environmental, social, and economic aspects. This paper proposes a Triangular Fuzzy Neutrosophic Numbers (TFNNs) as an extension of the multi-attributive border approximation area comparison (MABAC) method for hybrid multi-criteria decision-making (MCDM). The proposed method is utilized to assess the selection of hydropower as the most efficient and sustainable renewable energy source for society. Pairwise comparison matrices were used to determine priority vectors and weighted averages of indicators for seven criteria. The evaluation framework analyzed five key dimensions of hydropower plants. The most stable renewable energy source, pumped storage hydropower (60.78%), was found to be followed by run-of-river hydropower (56.39%), impoundment hydropower (50.03%), storage hydropower (39.78%), and offshore hydropower (07.95%). The study offers valuable insights for policymakers and implementer on sustainable electricity solutions for hydropower. Pumped storage hydropower (PSH) improves facility efficiency by ensuring optimal operation of coal and nuclear generators without energy loss. The system can provide a stable and reliable power storage solution for renewable energy sources like wind and solar.