Evaluation of Green Energy Alternatives Using an Interval-Valued Pythagorean Fuzzy Methodology

Increasing apprehension regarding climate change, resource scarcity, and ecological deterioration has propelled the global momentum toward sustainable energy development. In this context, green energy has become an essential part of the shift away from fossil fuels and toward a future with lower carbon emissions. However, choosing the best green energy source for a certain application or specific area is a difficult task with many facets requiring consideration. Green energy solutions necessitate careful evaluation of a wide range of qualitative criteria in contrast to traditional energy sources. We put forward a hybrid fuzzy Multi-Criteria Decision-Making (MCDM) method using interval valued Pythagorean fuzzy numbers in this paper. The possibility degree method is used in the suggested approach to derive the weights of the evaluation criteria. Next, the matrix of decisions is created, and the preferred alternative is selected by entropy theory and cosine similarity theorem. Ultimately, our goal is to develop innovative, reliable techniques using these various theorems. Combining the advantages of each approach improves decision-making proceses as they increase precision and resilience and streamline the ability to handle complicated data in a variety of situations. We utilized the proposed method to evaluate green energy alternatives in Sweden to demonstrate applicability. A sensitivity analysis of the results is conducted to test how changes in input parameters affect the final ranking. Finally, a comparison analysis is provided.