Neutrosophic reliability assessment of smart grid power generation system using universal generating function under Weibull distribution

Reliability is essential for each complex system. The key objective of the present study is to use a neutrosophic framework to handle data uncertainty in reliability modeling of power generation systems in smart grids. Numerous traditional approaches are capable of characterizing epistemic uncertainty, yet each owns respective limitations. To overcome the limitation of classical model problem, a novel approach as neutrosophic set is introduced, utilizing single valued triangular neutrosophic number (SVTNN). Also, it is integrated with universal generating function(UGF) and Weibull distribution to capture uncertainty more efficiently in reliability modeling of power generation system. Power generation system is made up by eight components in which “fuel supply” unit is parallel to “renewable sources” unit and “power conditioning” unit is parallel to “energy storage” unit. System behaviour is observed by numerical results of reliability and mean time to failure in neutrosophic environments at various time instants under data uncertainty. The innovation of proposed work is combination of neutrosophic sets with U.G.F and weibull based reliability framework to handle uncertainty effectively by comparing with conventional fuzzy approaches. A comparative analysis which based on reduction study and reliability by triangular fuzzy number (TFN), is performed in this study. A sensitivity analysis is also performed. The comparative analysis as uncertainty b1111ands highlighted graphically. The conclusion of current study is neutrosophic reliability framework effectively capturing uncertainty, indeterminacy, and falsity as compared to traditional reliability framework or fuzzy based approaches in power generation system.