An enhanced fuzzy decision making approach for the assessment of sustainable energy storage systems. (March 2023) - Narayanamoorthy, Samayan; Brainy, J.V.; Shalwala, Raed A.; Alsenani, Theyab R.; Ahmadian, Ali; Kang, Daekook
Abstract: The relevance of energy storage technology is necessitated by the paradigm shift towards renewable resources for power generation, as these resources are unpredictable and probabilistic in nature, making it difficult to respond quickly to demand fluctuations. The idea of linear diophantine hesitant fuzzy sets (LDHFS) have been introduced in this study as a fusion of linear diophantine fuzzy sets (LDFS) and dual hesitant fuzzy sets (DHFS), in which the satisfaction and dissatisfaction grades, as well as the control parameters, are written in hesitant fuzzy sets (HFS), allowing decision makers to analyse a vast number of objects and options when analysing a scenario. Moreover, the LDHF-SOWIA-MAIRCA model was used to ascertain the LDHFS's usefulness in selecting an appropriate energy storage technology for India. The five storage alternatives are evaluated in terms of technology, cost, environmental impact, performance, and social impact. The BESS fared better than the other ESSs using the developed framework. The proposed model's flexibility is evaluated in light of the comparison and sensitivity analysis. According to the findings of the sensitive analysis, the model is dependent on the weights of the criterion. Furthermore, it is clear from the comparison study that the LDHFS-based methodology may be adapted to deal with complex scenarios, including a range of criteria. Highlights: A novel concept of linear diophantine hesitant fuzzy sets is proposed. A hybrid LDHF-SOWIA-MAIRCA model is developed. The problem of choosing a sustainable energy storage system is examined. The efficiency of the developed model is validated.