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电力系统连锁故障快速预测方法研究 被引量:5

Research on fast forecasting method for power system cascading failures
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摘要 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。 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 largescale blackouts to quickly and accurately forecast the cascading failure possible paths. As for the overload oriented development model of cascading failures featured by relevance between adjacent failure links,relevance indicator is defined,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 relevance indicator as the next failure branch. It effectively reduces the computational load,and overcomes the shortcomings of existing methods. Finally,the simulation results of IEEE 39 nodes prove the rapidity and correctness of the proposed forecasting method.
出处 《电测与仪表》 北大核心 2016年第23期45-50,共6页 Electrical Measurement & Instrumentation
关键词 电力系统 大停电事故 连锁故障 关联性指标 加权模糊C均值聚类 连锁故障路径树 power system large-scale blackouts cascading failures relevance indicator weighted fuzzy C-means cascading failure path tree
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