电力系统连锁故障快速预测方法研究

近年来,电力系统大停电事故时有发生,而连锁故障是导致其发生的重要诱因,快速、准确地预测连锁故障可能的发展路径对预防大停电事故的发生具有重要的指导意义。针对过载主导型的连锁故障发展模式,充分利用连锁故障的前后因果关联性特点,定义关联性指标,提出基于故障路径树的连锁故障快速预测方法。该方法采用模糊聚类算法对关联性指标进行分类,选取关联性指标最高的一类支路为下级故障环节,在有效减少计算量的同时,改进了现有预测方法的不足。最后,对IEEE39节点系统进行仿真分析,仿真结果验证了所提预测方法的快速性和正确性。

A Research on Fast Forecasting for Power System Cascading Failures

In recent years, the large-scale blackouts in power system have occurred occasionally , and the cascading failures become an important cause leading to it .So it is of important guiding significance for the prevention of large-scale blackouts to quickly and accurately forecast the cascading failure possible paths .As for the overload oriented de-velopment model of cascading failures featured by relevance between adjacent failure links , relevance indicator is de-fined , and a method of fast forecasting for power system cascading failures based on failure path tree is proposed .The method uses fuzzy C-means to classify the relevance indicator , selecting the branches with the highest value of rele-vance indicator as the next failure branch .It effectively reduces the computational load , and overcomes the shortcom-ings of existing methods .Finally, the simulation results of IEEE 39 nodes prove the rapidity and correctness of the proposed forecasting method .