Dynamic maintenance strategies for multiple transformers with Markov models

Intelligent substations in smart grids can provide more information about operating states of transformers by advanced sensors and monitoring units. According to information, operators can identify health conditions of transformers more accurately to determine maintenance strategies more reasonably. Maintenance of transformers can enhance the health condition and improve the reliability of a power system. However, maintenance introduces additional costs into total operating costs. A sophisticated maintenance strategy should be a tradeoff between maintenance costs and reliability enhancement. Based on monitoring information, a dynamic coordinated maintenance strategy for multiple transformers is proposed in this paper. First, a Markov model of an individual transformer is built to demonstrate its deterioration processes. Based on deterioration processes of an individual transformer, deterioration processes of a system with multiple transformers are built. Besides internal deterioration processes of components, external conditions, e.g., weather conditions and availability of servicemen and auxiliary equipment, are also considered in the model. Then, an optimization model is built. A series of dynamic coordinated maintenance strategies can be provided by the proposed optimization model, which is solved by a backward induction algorithm. A test system is used to demonstrate efficiency and accuracy of the method proposed in this paper.