摘要
现有的针对继电保护信息不完整情况下的故障诊断与不可观测保护状态识别(FSE-SIUPR)的数学模型不能处理警报信息的时序特性,而这种特性对于弥补继电保护信息的不足、快速而准确地诊断故障并评价保护和断路器的动作行为具有重要作用.在此背景下,文中首先基于时序约束网络理论,发展了一种能够充分利用警报信息时序特性的FSE-SIUPR的集成数学优化模型,该模型能够从时序上解释整个故障演变过程,并识别出一些不可观测保护的状态.之后,采用禁忌搜索(Tabu)算法对优化模型进行求解,并用一个实际电力系统的故障场景对所提出的模型进行了验证.
In recent years,some models have been proposed for the fault section estimation and state identification of unobserved protective relays（FSE-SIUPR） under the condition of incomplete state information of protective relays.In these models,the temporal alarm information from a faulted power system is not well explored although it is very helpful in compensating the incomplete state information of protective relays,quickly achieving definite fault diagnosis results and evaluating the operating status of protective relays and circuit breakers in complicated fault scenarios.In order to solve this problem,an integrated optimization mathematical model for the FSE-SIUPR,which takes full advantage of the temporal characteristics of alarm messages,is developed in the framework of the well-established temporal constraint network.With this model,the fault evolution procedure can be explained and some states of unobserved protective relays identified.The model is then solved by means of the Tabu search（TS） and finally verified by test results of fault scenarios in a practical power system.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2012年第11期19-28,共10页
Journal of South China University of Technology(Natural Science Edition)
基金
国家科技支撑计划资助项目(2011BAA07B02)
南方电网公司科技资助项目(K201029.2
K-ZB2011-012)
关键词
电力系统
故障诊断
保护状态识别
警报时序信息
power system
fault section estimation
protective state identification
temporal alarm information
