| 引用本文: | 吴 浩,李群湛,易 东.基于广域状态信息和模糊C均值聚类的电网故障区域判别[J].电力自动化设备,2013,33(7): |
| WU Hao,LI Qunzhan,YI Dong.Faulty region identification based on wide-area state information and fuzzy C-means clustering[J].Electric Power Automation Equipment,2013,33(7): |
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| 摘要: |
| 结合电网广域状态信息，提出一种基于模糊C均值（FCM）聚类的电网故障区域判别新方法。该方法利用线路智能电子装置（IED）采集相应保护的动作信息、方向元件状态信息、断路器状态信息等，并以电网各线路IED状态信息作为FCM的聚类对象。给出电网关联IED的定义，利用故障判别算法把故障元件关联IED归为一类，同方向区外故障IED归为一类。大量仿真表明，该方法容错性能好，运行速度快，判别准确率高，即使部分信息不准确，也能正确判断故障区域。 |
| 关键词: 电力系统 广域状态信息 模糊C均值聚类 线路IED 故障区域判别 故障分析 |
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| 基金项目:人工智能四川省重点实验室项目（2010RY005， 2011RZY02，2011RYY08）；四川省教育厅项目（11ZB100） |
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| Faulty region identification based on wide-area state information and fuzzy C-means clustering |
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WU Hao1,2, LI Qunzhan1, YI Dong1
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1.Electrical Engineering Institute，Southwest Jiaotong University，Chengdu 610031，China;2.College of Automation and Electronic Information，Sichuan University of Science & Engineering，Zigong 643000，China
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| Abstract: |
| Combined with the wide-area state information of power grid，a method of faulty region identification based on FCM（Fuzzy C-Means） clustering is proposed，which uses the line IEDs（Intelligent Electronic Devices） to acquire the information of corresponding protection action，direction component state and circuit breaker state. It takes the information as the object of FCM clustering，gives the definition of grid-associated IED，and applies the fault discrimination algorithm to classify the IEDs associated with faulty component and the IEDs associated with external fault at same direction. Simulations show that，the proposed method，with better fault-tolerant performance，faster operation speed and higher accuracy of discrimination，can correctly identify the faulty area even when partial state information is inaccurate. |
| Key words: electric power systems wide-area state information fuzzy C-means clustering line IED faulty area identification failure analysis |
