| ±800kV直流输电线路故障定位的单端电压自然频率方法 |
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| 引用本文： | 束洪春,田鑫萃,张广斌,刘可真,孙士云.±800kV直流输电线路故障定位的单端电压自然频率方法[J].中国电机工程学报,2011,31(25). |
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| 作者姓名： | 束洪春 田鑫萃 张广斌 刘可真 孙士云 |
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| 作者单位： | 1. 昆明理工大学电力工程学院,云南省昆明市,650051
2. 哈尔滨工业大学电气工程与自动化学院,黑龙江省哈尔滨市,150001 |
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| 基金项目： | 国家自然科学基金项目(50977039,50847043,90610024,50467002,50347026); 云南省科技攻关项目(2003GG10,2005F0005Z)~~ |
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| 摘 要： | 输电线路故障行波频谱与故障距离之间存在数学关系，故利用故障行波频谱可以实现故障测距。直流输电线路两端平波电抗器和直流滤波器构成了直流输电系统实体物理边界，它对于行波高频部分呈近似开路特性，其反射系数接近于1，使得量测端时域波形呈周期性。对于行波低频部分，直流滤波器的频率特性使量测端的行波极性会发生翻转，致使时域波形的相角偏移，在频域上表现为自然频率的偏移。此外，故障电压行波于非对称短路点发生线模与零模行波相互交叉透射，致使故障电压自然频率“混叠”。鉴此，利用人工神经网络（artificial neural network，ANN）的非线性函数逼近拟合能力，选择故障电压自然频率的主频及其2倍频的幅值和频率作为样本属性，对神经网络进行训练、测试来确立直流输电线路故障定位的ANN模型。大量的PSCAD数字试验表明，基于自然频率和ANN的UHVDC线路故障测距方法可行、有效。
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| 关 键 词： | 特高压直流输电 自然频率 实体物理边界 故障测距 人工神经网络 |
Fault Location for ±800 kV HVDC Transmission Lines Using Natural Frequency of Single Terminal Voltage Data |
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| SHU Hongchun,TIAN Xincui,ZHANG Guangbin,LIU Kezhen,SUN Shiyun.Fault Location for ±800 kV HVDC Transmission Lines Using Natural Frequency of Single Terminal Voltage Data[J].Proceedings of the CSEE,2011,31(25). |
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| Authors: | SHU Hongchun TIAN Xincui ZHANG Guangbin LIU Kezhen SUN Shiyun |
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| Affiliation: | SHU Hongchun1,TIAN Xincui1,ZHANG Guangbin2,LIU Kezhen2,SUN Shiyun2(1.Faculty of Electric Power Engineering,Kunming University of Science and Technology,Kunming 650051,Yunnan Province,China,2.School of Electrical Engineering and Automation,Harbin Institute of Technology,Harbin 150001,Heilongjiang Province,China) |
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| Abstract: | The spectra of fault induced traveling wave is related to the fault distance,therefore the spectra of fault induced traveling wave can be utilized for fault location.A boundary existing in the DC system consisting of DC filter and smoothing reactor is almost the open-circuit to the high frequency signals and the reflection coefficient of the boundary is similar to one.Consequently,the wave measured at relay is a periodic signal.However,the polarity of traveling wave will be changed while hitting the DC filt... |
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| Keywords: | UHVDC natural frequency entity physical boundary fault loacation artificial neural network(ANN) |
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