基于马尔科夫链的变压器维护策略优化模型

Optimal Modeling of Maintenance Strategy of Transformers Based on Markov Chain

变压器设备长时间运行会造成系统故障风险的增大,降低电网的安全稳定性.为减少因变压器设备劣化造成的安全性问题及经济损失,在变压器运行期间需要对其进行维护.由于维护会增加系统的运行费用,有必要制定一个可以权衡系统运行费用和安全性的维护策略.将变压器设备的状态用马尔科夫模型表示,通过该模型预测未来时间段内变压器状态的概率.在此基础上建立考虑维护费用、维修费用以及潜在随机失负荷的维护策略优化模型,并通过Monte Carlo以及最优潮流计算潜在随机失负荷量.为了缩短优化计算所需时间,采用遍历消减法求解该优化模型.算例分析说明了所建立优化模型的可行性和有效性.

The fault risk of transformers tends to increase after operating for a long time, which undermines the security and stability of the power grid. In order to improve the security and reduce the economic loss caused by transformer degradation, maintenance of transformers is crucial to operation. Since the maintenance brings an additional cost to the system operation cost, it is necessary to formulate a maintenance strategy that makes a trade-off between maintenance cost increase and system security improvement. This paper describes the transformer states transition with the Markov model, based on which the state probability of transformers in the future periods is forecast. An optimization model for the maintenance strategy is developed, which takes account of maintenance cost, repair cost and potential stochastic load loss. Monte Carlo and optimal power flow （ OPF） methods are applied to calculate the potential stochastic load loss. Aimed at guaranteeing a reasonable computing time, a traversal elimination approach is proposed for constructing an optimization model. The case study demonstrates the validity and effectiveness of this model.