| Condition Based Maintenance (CBM) has been widely used in power system with the development of equipment condition monitoring, prediction and fault diagnosis. Compared with Corrective Maintenance and Preventive Maintenance, CBM can prolong equipment service life and improve the reliability and economy of the power system operation.In the context of CBM, most of current research decides equipment maintenance time based on individual equipment condition which can improve the reliability and economy of equipment operation. However, it may not give the best result for the system as dependence between different equipment are not considered. The dependence between equipment in power system are functional dependence, economic dependence and stochastic dependence. Maintenance performed without considering the dependence will suffer greater loss. Hence, it is crucial to optimize the cost of the whole system rather than individual equipment to fully benefit from CBM. This thesis focuses on the dependence between power equipment and conducts thorough research on power system CBM. The main contributions are as follows.(1) Existing power system CBM decision-making models are inconsistent with reality as they do not take opportunistic maintenance into account after equipment fails. To solve this problem, power system CBM decision-making model is proposed based on correlation sets decomposition. According to the functional dependence between different power equipment, definition of correlation sets is given. Then, the availability of the correlation set is deduced considering scheduled maintenance and opportunistic maintenance in the forward period using the renewal process theory. Furthermore, the mathematical expression of system maintenance risk and failure risk are given to reflect the inherent link between equipment maintenance and system operation. Finally, the system CBM decision-making model is developed, the goal of which is minimizing the sum of system maintenance risk and failure risk. Practical case studies demonstrate the ability of the proposed model for improving the reliability and economy of the power system operation.(2) Selective opportunistic maintenance strategy is proposed based on the study mentioned above. For correlation sets composed of several equipement, impacts of different opportunistic maintenance combination on power system operation are not the same because of different equipment maintenance durations. Therefore, optimal equipment opportunistic maintenance strategy should be decided to achieve maximum system operation efficiency based on the analysis of different opportunistic maintenance combination and actual system operation mode. This research formulates the mathematical expression of equipment risk and system operation risk considering selective opportunistic maintenance strategy. Based on that, power system CBM decision-making model is developed. As this model selects equipment opportunistic maintenance strategy according to actual composition of correlation sets and system operation mode, it can further integrate CBM and system maintenance decision-making, and also extend the concept of opportunistic maintenance.(3) The study mentioned above concentrates on equipment deterioration failure. However, there exist two types of failure (abrupt failure and deterioration failure) for power equipment. To investigate the impact of failure dependence on equipment maintenance decision, opportunistic maintenance decision-making model for power equipment is built up considering the handling of abrupt failure. In consideration of equipment failure rules, this model constructs the equipment state transition process using Markov process. Furthermore, according to the functional dependence, economic dependence and stochastic dependence, mathematical expression of equipment risk and system operation risk are deduced based on opportunistic maintenance strategy to realize organic coordination of the maintenance action of different failures. Finally, the equipment opportunistic maintenance decision-making model is built up to minimize the sum of equipment risk and system operation risk. The efficiency of this model is demonstrated by some practical examples. This model provides necessary foundation for optimizing equipment maintenance strategies.(4) A CBM based inspection model for power equipment considering opportunistic maintenance is proposed since opportunistic maintenance between abrupt failure and deterioration failure may have a great impact on equipment inspection strategy. In this model, Markov process is used to describe equipment transition process in which the equipment transfer time is supposed to follow exponential distribution. Then, equipment risk and system operation risk are given considering the changes of inspection frequency, opportunistic maintenance strategy and preventive maintenance strategy. The impacts of changing inspection frequency, opportunistic maintenance strategy and preventive maintenance strategy on system operation are analyzed. Finally, equipment risk and system operation risk are minimized to optimize equipment maintenance strategies. Test results prove that this model can describe equipment transition process effectively and optimize equipment maintenance strategies. |
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