An enhanced fuzzy decision making approach for the assessment of sustainable energy storage systems

Samayan Narayanamoorthy, J. V. Brainy, Raed A. Shalwala, Theyab R. Alsenani, Ali Ahmadian, Daekook Kang

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

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.

Original languageEnglish
Article number100962
JournalSustainable Energy, Grids and Networks
Volume33
DOIs
StatePublished - Mar 2023

Keywords

  • Dual hesitant fuzzy sets
  • Energy storage systems
  • Integrated decision model
  • Linear diophantine hesitant fuzzy sets

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