TY - JOUR
T1 - An enhanced fuzzy decision making approach for the assessment of sustainable energy storage systems
AU - Narayanamoorthy, Samayan
AU - Brainy, J. V.
AU - Shalwala, Raed A.
AU - Alsenani, Theyab R.
AU - Ahmadian, Ali
AU - Kang, Daekook
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/3
Y1 - 2023/3
N2 - 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.
AB - 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.
KW - Dual hesitant fuzzy sets
KW - Energy storage systems
KW - Integrated decision model
KW - Linear diophantine hesitant fuzzy sets
UR - http://www.scopus.com/inward/record.url?scp=85143657862&partnerID=8YFLogxK
U2 - 10.1016/j.segan.2022.100962
DO - 10.1016/j.segan.2022.100962
M3 - Article
AN - SCOPUS:85143657862
SN - 2352-4677
VL - 33
JO - Sustainable Energy, Grids and Networks
JF - Sustainable Energy, Grids and Networks
M1 - 100962
ER -