基于电网潮流分布在事故前后表现出的特征变化,提出了一种在线故障智能诊断方法。此方法能自适应跟踪电网运行方式并动态选择量测对象和量测数据,在线分析电网潮流分布特征与网络结构变化的关系以预生成故障模式库。当提取的潮流分布特征与故障模式库中的某一模式匹配成功后,即可实现电网故障的在线诊断。算例表明,方法准确高效,具有在线自适应智能诊断的功能,有助于提高把握网络事态和正确应对事故的能力。
Blackouts which happened continually these years around the world show that power system desiderates more effective means of security monitoring and fault diagnosis. A new online fault intelligent diagnosis approach is proposed in this paper, which is based on distributed characteristics of power flow before and after fault. This approach can track operation in an adaptive way, select monitored data and monitored objects dynamically and pre-create the library of fault patterns through analyzing the relationship between distributed characteristics of power flow and the outage of electric power network. While distributed characteristics of power flow matches a pattern in the library, the approach realizes online intelligent diagnosis of the fault. The results of numerical tests have justified that the approach is intelligent, accurate and robust. It can enhance operator' s ability for grasping gird state of affairs and dealing with grid accidents.