A novel maintenance decision making model of power transformers based on reliability and economy assessment

Abstract

The present 'condition-based maintenance decision making' of power transformers will cause large financial losses to electric enterprises, because of not having taken reliability and economy into consideration. To solve this problem, a maintenance decision-making model with the consideration of reliability and economy was established to choose the best maintenance strategy for oil-filled transformers. With the corrected parameters of operating environment and maintenance records, a condition assessment model including DGA test, oil test, and the electrical test was proposed to decide the comprehensive health index of transformers. After establishing the relationship between the fault rate and the comprehensive health index, a reliability evaluation model was formed, which can simulate the impact of different maintenance types. Taking the reliability and economy operation of transformers into consideration, a particle swarm optimization method was developed to solve the optimization model and select the best maintenance strategy according to the current condition of transformers. Two cases were studied and the results demonstrate that the proposed model offers an improved maintenance strategy.