Abstract
Because stochastic fault cases (i.e., opportunistic maintenance strategy) of the equipment are not considered in the condition-based maintenance decision of the system, which will deviate from the actual situation, a system condition-based maintenance scheduling model considering opportunistic maintenance strategy is proposed in this paper. To implement the system maintenance strategies, the correlation set is formulated by considering the relationship among different equipment. According to renewal process theory, the availability of the correlation set considering planned maintenance and opportunity maintenance is deduced and the maintenance strategy of the system is realized. Then, to reflect the relationship between equipment maintenance and system operation, a system state scheduling model aiming at minimizing the sum of maintenance risk and failure risk as well as considering system resource constraints is proposed, thus obtaining the optimal maintenance schedule based on system state. Finally, a simple test system and IEEE-RTS79 node system are employed to demonstrate the feasibility and effectiveness of the proposed maintenance model, and it also verified that the proposed model can be integrated into the power system condition-based maintenance theory.
Highlights
Mathematical Problems in Engineering complex system can be categorized into three groups: structural dependence, economic dependence, and stochastic dependence [7]. erefore, the individual performance of equipment and the correlation between types of equipment need to be considered, when equipment maintenance strategy is formulated, and for a power system, the differences of equipment maintenance schedule must be properly handled [8,9,10]
Based on the correlation set, the mathematical model of system maintenance risk and failure risk is deduced; we present a system maintenance scheduling model, which aims to minimize the sum of maintenance risk and failure risk while taking system resource constraint, to derive the optimal system condition-based maintenance scheduling. e case study results illustrate the feasibility and validity of the proposed maintenance model, and this model can be integrated into the theory of CBM for power systems, which will have a prospect of practical engineering application
E equipment maintenance risk and failure risk are deduced by considering the following n + 1 cases: (1) If the correlation set reliably runs to the scheduled maintenance time tm, the equipment maintenance risk is the individual loss of equipment caused by scheduled maintenance, which can be expressed as n
Summary
Correlation set is defined as the collection of equipment satisfying the following relevance during the system operation. According to the actuating logic of relay protection [25,26,27,28], the failure of any equipment in the correlation set (e.g., an active equipment failure occurs) will cause the whole correlation set to stop operating after the switching operation (fault removal and fault recovery). (1) Enumerate the single failure of each primary equipment i in the system, and consider the actions of the relay protection device, so as to determine the equipment set that the system exits operation after the switching operation, and it is marked as AGi, establishing the mapping relationship between equipment i and the outage set. After completing the ergodic process for all equipment of the system in accordance with the above decision-making principles, the system can be decomposed into correlation set and take the correlation set as a unit to make maintenance decisions
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