Assessment of renewable energy sources for smart cities' demand satisfaction using multi-hesitant fuzzy linguistic based choquet integral approach. (April 2022) - Krishankumar, Raghunathan; Pamucar, Dragan; Deveci, Muhammat; Aggarwal, Manish; Ravichandran, Kattur Soundarapandian
Abstract: With a sheer commitment to reduce carbon footprint, India refined its strategy towards meeting energy demands by adopting renewable energy policies in smart cities. In an event hosted by the Confederation of Indian Industry, the Chairman of the electricity board claimed that India has reached its renewable energy share of 26% and has rigorous plans to reduce carbon trace to adhere to the commitment made in the Paris Accord. Atal Mission for Rejuvenation and Urban Transformation (AMRUT) is an ambitious plan by India to create and manage smart cities with sustainable development plans. Under this plan, renewable energy usage plays a substantial role and the selection of appropriate energy options is a complex decision problem with competing criteria. Previous studies on renewable energy selection have paid subtle attention towards criteria interrelationships, managing of linguistic expressions, and relative importance of experts. Therefore, in this study, a new decision making approach is developed. Specifically, the hesitant fuzzy linguistic information (HFLI) is adopted. Then, attitudinal Choquet integral (AC) is proposed under HFLI context along with their fundamental properties. Besides, relative importance of criteria and experts are determined by evidence-based Bayesian approach and variance approach under HFLI context, respectively. A ranking algorithm is presented with the CRITIC technique. Finally, a case study in Tamil Nadu illustrates the usefulness of the integrated framework and the comparison provides grounding for the superiority of the framework.