Fuzzy Reliability Assessment of Photovoltaic Power Plant System with Generalized Intuitionistic Fuzzy Sets

The constant exploitation of nonrenewable resources has led to the depletion of these resources, thus amplifying the usage of renewable sources and renewable energy systems, which has further led to the need for reliability assessment of these renewable energy systems. However, standard reliability modeling only uses the exact values for a system’s assessment, even though no system in the actual world works with absolute precision. This imprecision or ambiguity could be due to a lack of knowledge about the system, insufficient data or human errors; hence, the concept of fuzzy theory has proven to be incredibly useful in dealing with such circumstances in the past few decades due to its ability to express this uncertainty in exact quantitative terms. Therefore, this particular work proposes a novel technique for reliability assessment by using generalized intuitionistic fuzzy sets (GIFS) to represent fuzzy variables, and the reliability function is obtained using the universal generating function approach where the failure rates follow the fuzzy exponential distribution. The motivation for using GIFS instead of traditional fuzzy sets lies in the fact that the traditional fuzzy sets can only consider the positive aspect, whereas GIFS can consider both its positive and negative aspects. Finally, the proposed approach is applied to the system of a photovoltaic power plant and its fuzzy reliability, mean time to failure and the sensitivity of fuzzy reliability are evaluated for different cases of failure rates and the attained results are compared.