Development of a model for determining a priority sequence of power transformers out of service

Abstract

The research is devoted to the development of a model and algorithm for making decisions on determining the priority of power transformers out of service. Reducing the reliability of EPS operation, caused by the objectively existing aging of power transformer equipment, requires consideration of equipment significance when planning the power transformers out of service. For this purpose, it is proposed to use the theory of fuzzy sets and the Pareto method. The result of solving the optimization problem for multicriteria analysis is a vector of the best alternatives, built on the principle of dominance. The developed algorithm of complex simulation of the EPS state and technical condition of the power transformer for making decisions on the determination of priority of power transformers out of service allows for effective decision-making. The results of probabilistic and statistical simulation of EES states using the Monte Carlo method allow us to take into account the probabilistic nature of emergency situations in the EPS when determining its weakest elements that require priority replacement. The advantage of the proposed approach is taking into account the technical condition of electrical equipment for risk assessment of the EPS emergency situation. A comparative analysis of ranking results of power transformers based on the risk assessment of the EPS emergency situation confirmed the high efficiency of planning of EPS states when solving the problems of preventive control. The developed model will be used for further research and development of the algorithm for making effective decisions regarding the operation strategy of the power transformer and preventive control of the subsystem operation of the electric power system. The obtained results of complex simulation of the EPS state and technical condition of the power transformer give grounds to assert the possibility of software implementation of operation risk analysis of the electric power system for power supply companies.