Multi-model MCDM framework for sustainable renewable energy selection in India: integrating CRITIC-EDAS-CODAS-CoCoSo
Shankha Shubhra Goswami, T. Tapankumar, Neelima Naik, J. Gowrishankar, Nilesh Bhosle, Amrita Singh, G T Raju, D. Nagesh, A. Johnson Santhosh
Abstract
The global boom in the importance of renewable energy (RE) resources has accelerated the transition from traditional energy sources to sustainable alternatives. Selecting an optimum RE power plant is a complex task influenced by geographical factors, climatic differences, and regional peculiarities. Furthermore, incorporating numerous conflicting criteria, such as technical, economic, environmental, and social variables, complicates the decision-making process, rendering it a multi-criteria decision making (MCDM) problem. This research aims to solve the current complicated decision-making process by utilizing the CRITIC integrated EDAS-CODAS-CoCoSo MCDM framework, specifically focusing on selecting the most suitable RE power plant to be developed in the Indian environment. Within the MCDM system, a case study was analyzed using five unique RE sources, namely geothermal, solar, wind, hydro, and biomass. The evaluation was based on six competing elements classified into three broad categories: mechanical features, economic considerations, and environmental implications. The CRiteria Importance Through Intercriteria Correlation method (CRITIC) was initially used to determine the objective criteria weights, which were subsequently integrated into the Evaluation based on Distance from Average Solution (EDAS), COmbinative Distance-based ASsessment (CODAS), and Combined Compromise Solution (CoCoSo) methodologies to determine the preference ranking order of the alternatives. The data indicate that hydroelectric power plants are the most ideal alternative, followed by solar electricity, while geothermal and biomass are the least favorable among the considered RE sources. This study analyzes the rankings of the three deployed MCDM models and checks their stability using a sensitivity analysis. Another feature of the final results shows that EDAS and CoCoSo perform slightly better than CODAS in terms of ranking efficiency. The in-depth study of these findings provides crucial insights and direction for policymakers and stakeholders in India’s renewable energy sector. Clinical trial number: Not applicable.