引用本文:张晓彤,陈青,孙梦璇,黄吴镝,王磊,刘博.针对智能变电站二次回路故障的高压断路器故障追踪[J].电力自动化设备,2020,40(0):
ZHANG Xiaotong,CHEN Qing,SUN Mengxuan,HUANG Wudi,WANG Lei,LIU Bo.Fault tracking of high-voltage circuit breakers in case of secondary circuit faults in intelligent substations[J].Electric Power Automation Equipment,2020,40(0):
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针对智能变电站二次回路故障的高压断路器故障追踪
张晓彤1, 陈青1, 孙梦璇1, 黄吴镝1, 王磊2, 刘博3
1.山东大学 电网智能化调度与控制教育部重点实验室,山东 济南 250061;2.国网技术学院,山东 济南 250002;3.北京交通大学 电气工程学院,北京 100044
摘要:
针对相关二次回路故障导致高压断路器不正确动作的情况进行分析,提出了一种基于有向二分图模型的故障追踪方法,从而对高压断路器不正确动作具体原因进行反向追踪。首先根据面向通用对象的变电站事件报文的传递路径将相关二次回路网络分簇为通信网络、保护装置、智能组件及测控装置,并将每一簇作为一个子域。其次利用智能变电站端的相关二次回路异常信息及故障原因之间的逻辑关系,在每个子域内建立基于有向二分图的故障关联模型。最后引入贝叶斯疑似度对故障原因进行计算分析并结合反向推理进行验证,从概率上保证了结果的准确性。案例分析表明,所提故障追踪方法可以及时对高压断路器不正确动作追本溯源,且具有较高的容错性。
关键词:  智能变电站  有向二分图模型  贝叶斯疑似度  反向推理  高压断路器  二次回路  故障追踪
DOI:10.16081/j.epae.202008003
分类号:TM561
基金项目:国家自然科学基金资助项目(51877123)
Fault tracking of high-voltage circuit breakers in case of secondary circuit faults in intelligent substations
ZHANG Xiaotong1, CHEN Qing1, SUN Mengxuan1, HUANG Wudi1, WANG Lei2, LIU Bo3
1.Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education, Shandong University, Jinan 250061, China;2.State Grid of China Technology College, Jinan 250002, China;3.School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Abstract:
The incorrect operation of the high-voltage circuit breaker caused by the secondary circuit fault is analyzed, then a fault tracking method based on the directed bipartite graph model is proposed to backward trace the specific cause of the incorrect action. Firstly, according to the transmission path of GOOSE message, the network is divided into four clusters, i. e. communication network, protection device, intelligent component, and measurement and control device, where each cluster is regarded as a sub-domain. Then based on the logical relationship between the fault causes and abnormal information of the relevant secondary system in smart substation, a fault map based on the directed bipartite graph is established in each sub-domain. Finally, the Bayesian suspected degree is introduced to calculate and analyze the cause of fault and back reasoning is used for verification, which guarantees the accuracy of the result in probability. The case study shows that the proposed fault tracking method can trace the source of the incorrect operation of the high-voltage circuit breaker in time and has high fault tolerance.
Key words:  intelligent substation  directed bipartite graph model  Bayesian suspected degree  back reasoning  high-voltage circuit breaker  secondary circuit  fault tracking

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