CAJ | 학술논문

为有效解决分区故障诊断关于互连区域间联络线的诊断问题，提出了基于径向基函数神经网络和模糊积分融合的大电网故障诊断方法。该方法通过网络重叠分区将大电网划分为若干区域，故障发生后根据警报信息选择性触发警报信息所在区域对应的区域径向基函数神经网络诊断模块，然后利用模糊积分关联融合相连区域关于联络线的诊断输出，实现对联络线的故障诊断。该方法不仅可以诊断各区域内部发生的故障，而且能够有效地诊断区域间联络线发生的故障。算例仿真结果表明：该方法简单、有效，能弥补现有电网分区故障诊断方法在联络线故障诊断方面存在的不足，且能够处理各种复杂故障情况，具有良好的故障容错能力。
위유효해결분구고장진단관우호련구역간련락선적진단문제，제출료기우경향기함수신경망락화모호적분융합적대전망고장진단방법。해방법통과망락중첩분구장대전망화분위약간구역，고장발생후근거경보신식선택성촉발경보신식소재구역대응적구역경향기함수신경망락진단모괴，연후이용모호적분관련융합상련구역관우련락선적진단수출，실현대련락선적고장진단。해방법불부가이진단각구역내부발생적고장，이차능구유효지진단구역간련락선발생적고장。산례방진결과표명：해방법간단、유효，능미보현유전망분구고장진단방법재련락선고장진단방면존재적불족，차능구처리각충복잡고장정황，구유량호적고장용착능력。
This paper presented an effective method for fault diagnosis of large-scale power grids based on radial basis function(RBF) neural network and fuzzy integral fusion. The study aims at effectively solving the diagnosis problem about the tie lines connecting regional sub-grids in the divisional fault diagnosis scheme. An overlapping network division method was proposed to divide a large-scale power grid into several sub-grids. When faults occur, regional RBF neural network diagnostic modules corresponding to different sub-grids are selectively triggered according to local alarm information which implies the faults exist in the sub-grids. Then faults of tie lines can be diagnosed by applying fuzzy integral to fuse the diagnostic outputs of two connected sub-grids about the tie lines. The method can not only be efficient in diagnosing the faults within local regions, but also in diagnosing the faults of tie lines well. The simulation results show that the proposed method is simple, efficient and can make up for the shortcoming of existing divisional fault diagnosis methods in diagnosis of tie lines. Moreover, it can diagnose different complex faults with good fault tolerance capability.