计及信息畸变影响的电网故障诊断分级优化方法

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Abstract Recent optimization-based fault section estimation methods for power systems can be categorized as consistency diagnostic methods or parsimonious covering diagnostic methods. The two kinds of methods may reach wrong diagnosis results in complex scenerios in which maloperation of protections and alarm aberrance exist. To overcome their drawbacks, a multi-objective gradual optimization method was built by combining the merits of the two methods. The proposed method took turns to make the consistency diagnosis based on all the alarm and the protection alarm repectively, and then the parsimonious covering diagnosis. By simple calculation of the diagnosis results, several kinds of fault section candidates are listed according to their fault probability. Case studies show that the method presented can accurately locate the faulty element in the aforementioned complex scenerios but also give a detailed evaluation of the operation of protections. To reduce the heavy calculation load caused by multiplicity of characteristic alarms, a method to construct adaptive characteristic alarms is proposed. Specefic approaches to confine and list various state vectors are provided based on the outage area, which make the diagnosis process much faster.

Key words： Power system fault diagnosis optimization model information aberrance variable temporal order figure outage area

Received: 20 March 2008 Published: 17 February 2014

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TM734

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	Articles by authors
	Mei Nian
	Shi Dongyuan
	Li Yinhong
	Duan Xianzhong

Cite this article:

Mei Nian,Shi Dongyuan,Li Yinhong等. Power System Fault Diagnosis Based on Gradual Optimization in Consideration of Alarm Information Aberrance[J]. Transactions of China Electrotechnical Society, 2009, 24(9): 178-185.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2009/V24/I9/178

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作者简介:梅念女, 1982年生, 博士研究生, 研究方向为人工智能在电力系统中的应用、电力系统继电保护及电力系统故障诊断。石东源男, 1974年生, 副教授, 研究方向为信息化电力系统相关理论及支撑软件技术。