Estimation of the acceptable risk level of emergency situation in the electric power engineering system using fuzzy models

Purpose. The development of a model for assessing the level of permissible risk of an emergency situation in the power system in the conditions of fuzzy input data, heterogeneity of the criteria for risk assessment, the absence of analytical links between them and the subjectivity of expert knowledge of decision makers. Methodology. To solve this problem, methods and models of fuzzy logic are used which give satisfactory analytical result in the conditions of uncertainty of the input information and the absence of analytical connections between the individual parameters and characteristics of the object. The proposed fuzzy models are constructed using the Fuzzy Output Algorithm of Mamdani. Findings. The result obtained by the fuzzy model gives the opportunity to assess reliably the acceptable level of risk of an emergency situation in the grid. Based on the magnitude of the risk, it is possible to make informed decisions regarding the expediency (or impracticability) of applying measures to reduce this risk. This enables the organization of preventive management of the risk of an emergency situation in the grid and the use of effective measures to reduce it. Originality. The article is devised a fuzzy model for estimating the permissible risk level of an emergency situation in the electric power system, which takes into account such criteria as the minimum possible level of risk, the influence of meteorological conditions and errors of operational and operational personnel of power systems. In this case, it is possible to take into account the main factors influencing the reliability of the grid functioning, to assess the risk level of an emergency situation.. Practical value. The fuzzy models developed in the article provide an opportunity to carry out an express assessment of the level of permissible risk of an emergency situation in the conditions of limited data and evaluation criteria, to conduct a comparative analysis of the obtained result with the magnitude of the actual risk of an accident in the on-line mode and to make a decision as to the appropriateness of its reduction