引用本文: | 高厚磊,陈学伟,刘洪正,李 超,冯迎春.基于改进参数检测法的双端非同步数据故障测距算法[J].电力自动化设备,2014,34(9): |
| GAO Houlei,CHEN Xuewei,LIU Hongzheng,LI Chao,FENG Yingchun.Two-terminal asynchronous data fault location algorithm based on improved parameter detection method[J].Electric Power Automation Equipment,2014,34(9): |
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摘要: |
基于输电线路分布参数模型,提出一种基于改进参数检测法的双端非同步数据故障测距算法。该算法利用故障前两端电压、电流数据实时修正非同步角度和线路参数,再利用故障后数据进行故障测距。与拟牛顿法相比,所提算法无需迭代,计算量小;与电压趋势法相比,所提算法不存在伪根判别的问题;与传统参数检测法相比,所提算法能够实时修正非同步角度。基于PSCAD/EMTDC的仿真结果表明,该算法测距精度高,受故障条件和线路换位的影响较小。 |
关键词: 双端故障测距 故障定位 线路 参数检测 非同步数据 线路换位 模型 |
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基金项目:山东省电力公司科技项目(2012A- 82) |
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Two-terminal asynchronous data fault location algorithm based on improved parameter detection method |
GAO Houlei1, CHEN Xuewei2, LIU Hongzheng3, LI Chao3, FENG Yingchun3
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1.Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education,
Shandong University,Ji’nan 250061,China;2.Tangshan Power Supply Company,State Grid Jibei Electric Power Company Limited,Tangshan 063000,China;3.Shandong Electric Power Corporation Maintenance Company,Ji’nan 250021,China
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Abstract: |
According to the distribution parameter model of power transmission line and the asynchronous data of its two terminals,a fault location algorithm based on the improved parameter detection method is proposed,which applies the voltage and current data of two terminals in normal condition to correct the asynchronous angle and line parameter in real time and uses the voltage and current data of two terminals in faulty condition to locate the fault. Compared to the quasi-Newton method,it avoids the iterative operation and has smaller calculation load;compared to the voltage trend method,it avoids the pseudo root discrimination;compared to the traditional parameter detection method,it corrects the asynchronous angle in real time. Simulative results by PSCAD/EMTDC show that,with high location accuracy,the proposed algorithm is slightly influenced by the fault condition and line transposition. |
Key words: two-terminal fault location electric fault location electric lines parameter detection asy-nchronous data line transposition models |