Multicriteria fuzzy statistical analysis of biogas energy systems dependability

Abstract

The work is devoted to the problems of assessing the dependability of autonomous energy systems with biogas type of electrical generation. The purpose of the work is to develop an intelligent tool for multi-criteria dependability assessment, taking into account the statistical uncertainty of individual indicators. A three-level hierarchy (according to the degree of generalization) of dependability indicators, represented by statistical (at the lower level) and fuzzy linguistic (starting from the second level) variables, has been developed. It is proposed to implement the transition from statistical values of lower-level indicators to numerical values of second-level indicators using an artificial neural network. Fuzzification of second-level indicators was carried out using L. Zadeh’s z-number apparatus, which allows taking into account statistical uncertainty. To determine the integral dependability indicator (top of the hierarchy) based on second-level indicators, it is proposed to use the Mamdani fuzzy inference algorithm. The constructed procedure for determining the level of dependability allows us to obtain data for making scientifically based decisions when operating biogas energy systems.