Reliability evaluation of repairable systems using various fuzzy-based methods - A substation automation case study

This paper focuses on material that is required for the practical application of fuzzy reliability; impacts of repair and data uncertainty. For this purpose, a holistic solution is presented to measure and manage the degree of uncertainty in the reliability indices of repairable systems. First, a flexible form of Markov Processes (MPs) namely Equivalent Transition Rate (ETR) is introduced in order to obtain an analytical formalism. Second, we delve deeply into the issues of fuzzy arithmetic by providing an intuitive, methodic and computational discussion of feasible approaches; Standard Fuzzy Arithmetic (SFA), Intermediate Variables (IMVs) and Taylor Series (TS). Specific emphasis is then placed upon Fuzzy Transformation Method (FTM). Third, we evaluate the performance of proposed techniques in case of a reliability problem involving fuzzy complexity. Consequently, the reader is given useful insights into the nature of fuzzy computations and practical impediments when measuring uncertain data. Given materials and methods, current paper provides a broad perspective by evaluating the reliability characteristics of a repairable Substation Automation System (SAS) that is one of the fundamental elements in Smart Grids (SGs). In this regard, quantitative results and diagrammatic outputs are supported by a detailed analysis under different assumptions. Our findings demonstrate that fuzzy outputs are computationally tractable and properly estimated. Besides, this investigation shows how the objective SAS can respond to the variations in reliability data. The framework proposed here encourages the continuation of the work towards more applications in electric power components and systems. As far as we know, there are no studies on these techniques, results and remarks.