The novel augmented Fermatean MCDM perspectives for identifying the optimal renewable energy power plant location

Abstract

The Fermatean fuzzy set has been authorized as a suitable tool for the uncertainty and vagueness of information by augmenting the spatial space of acceptance membership and non-acceptance membership degrees of both intuitionistic and Pythagorean fuzzy sets. Solar energy does not emit any hazardous gases into the atmosphere, making it one of the most effective strategies to reduce global warming in the environment. Under a variety of circumstances, finding a spot for a photovoltaic solar power plant might be difficult. As a result, we experiment with multi-criteria decision-making (MCDM) techniques. We presented a hybrid technique based on the PV-SPSS method based on the Removal Effects of Criteria (MEREC) and Multiple Objective Optimization on the Basis of Ratio Analysis with Full Multiplicative Form (MULTIMOORA) analysis. The MEREC approach is used to calculate the weightage of each attribute, and MULTIMOORA is used to find the ranking of the alternatives. Also, a new rectified generalized score function determines the score value of FFSs. Culmination: the validity of the result is assessed by implementing the existing MCDM approaches and by changing the criterion weight.