电力系统N-K故障的风险评估方法

历次大停电事故表明，由简单故障触发的连锁故障会对电力系统造成灾难性的后果。识别和分析可能对电力系统造成大面积停电的严重N-K故障是进行电网安全评价和制定防御措施的必要步骤。文中在分析大停电演变过程的基础上，提出了一种电力系统N-K故障的风险评价方法：考虑故障间的相互影响和继电保护的隐藏故障，计及元件运行状态变化对其故障概率的影响，基于贝叶斯网络给出了N-K故障的概率计算模型；详细模拟了实际电力系统连锁故障过程中的控制措施，建立了计及电压稳定约束的最优控制模型，提出了N-K故障严重程度的确定方法；最后提出了N-K故障风险指标的计算方法。利用Python语言对PSS/E进行了二次开发，实现了所提方法，并以IEEE 30节点测试系统为例，识别出该系统中的严重N-K故障，验证了方法的正确性。

Risk Assessment Method of Power System N-K Contingencies

All previous blackouts show that cascading failures caused by simple faults can lead to disastrous consequences. Identification and analysis on severe N-K contingency that may lead to large-area blackouts is an absolutely necessary procedure for power system security assessment and establishment of defensive measures. On the basis of analyzing the evolutionary process of blackout, a method to assess the risk of power system N-K contingency is proposed, that is, considering the interaction of failures and the hidden failures of protective relaying as well as taking the impacts of element operation condition variation on its fault probability into account, based on Bayesian network a probability calculation model of N-K contingency is given; then the control measures during cascading failure process in actual power system are simulated in detail and an optimal control model in which the voltage stability constraints are taken into account is built, and a method to determine the severity of N-K failures is put forward; finally, an approach to calculate the risk index of N-K contingency is given. By use of Python language the PSS/E is re-developed, thus the proposed method is realized. Taking IEEE 30-bus system for example, the severe N-K contingency in it is identified and the correctness of the proposed method is validated.