System for Prediction of the Technical Condition of Electric Power Equipment

This paper analyzes the method of neuro-fuzzy modeling for forecasting the technical condition of elements of the electric power system. The model contains the following elements: a simulation model of a solar power plant, a simulation model of a wind generator, a simulation model of a synchronous generator acting as a thermal station. A special Fuzzy extension logic toolbox tool system was used to perform the simulation, designed to evaluate the quality of the synchronous generator. The received estimates of the technical condition of the equipment are processed using an adaptive neuro-fuzzy inference system (ANFIS), resulting in a forecast of the technical condition of the equipment at a given time interval. Simulation of real systems by fuzzy models is based on the fact that fuzzy models of Sugeno type and Mamdani type are universal approximators of functions. The built model can be used in the design of renewable energy facilities, as well as in the development and testing of control and monitoring system algorithms. The system for evaluating and forecasting the condition of equipment using a fuzzy logic apparatus can be used to support decision-making by the operator of the power plant when determining the need for repair and replacement of equipment.