| 引用本文: | 邢超,高敬业,毕贵红,陈仕龙,蔡旺,王龙.基于多层感知器的LCC-MMC并联型特高压三端混合直流输电线路故障检测方法探讨[J].电力自动化设备,2023,43(3): |
| XING Chao,GAO Jingye,BI Guihong,CHEN Shilong,CAI Wang,WANG Long.Discussion on fault detection method for transmission line of LCC-MMC parallel three-terminal hybrid UHVDC system based on multi-layer perception[J].Electric Power Automation Equipment,2023,43(3): |
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| 摘要: |
| 针对现有故障检测方法存在阈值整定困难、特征量提取过程复杂的问题，提出一种基于多层感知器(MLP)的电网换相换流器和模块化多电平换流器(LCC-MMC)并联型特高压三端混合直流输电线路故障检测方法。首先，分析直流线路昆北侧边界、T区边界、龙门侧边界的频率特性，指出三端直流线路不同区域发生故障时的故障特征差异；其次，通过小波变换对线模电流、线模电压进行多尺度小波分解，提取小波能量，并结合正、负极电压变化量组成故障特征量。然后，将故障特征量作为MLP的输入量、故障区域作为输出量，构建基于MLP的故障区域识别模型；将测量点提取到的故障特征量输入训练完成的模型即可达到故障区域识别的目的。通过大量仿真验证了所提故障检测方法准确率高，且可耐受300 Ω的过渡电阻。 |
| 关键词: 特高压三端混合直流 频率特性 多层感知器 故障特征量 故障检测 |
| DOI：10.16081/j.epae.202209012 |
| 分类号:TM771 |
| 基金项目:国家自然科学基金资助项目(52067009) |
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| Discussion on fault detection method for transmission line of LCC-MMC parallel three-terminal hybrid UHVDC system based on multi-layer perception |
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XING Chao1, GAO Jingye1,2, BI Guihong2, CHEN Shilong2, CAI Wang2, WANG Long2
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1.Electric Power Research Institute of Yunnan Power Grid Co.,Ltd.,Kunming 650217, China;2.College of Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China
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| Abstract: |
| Since existing fault location methods suffer from the deficiencies of difficulty in selecting thresholds and the complex characteristic variables extraction, a fault detection method for line commutated converter-modular multilevel converter(LCC-MMC) parallel three-terminal hybrid ultra high voltage direct current(UHVDC) transmission lines based on multi-layer perception(MLP) is proposed. Firstly, the frequency characteristics of Kunbei-side boundary, T-zone boundary and Longmen-side boundary are analyzed, and the differences of fault characteristics when the fault occurs in different zones of the three-terminal DC line are point out. Secondly, the wavelet energy is extracted by multi-scale wavelet decomposition of line-mode current and line-mode voltage through wavelet transform, and the fault characteristic variables are formed combined with the positive-and negative-pole voltage variations. Then taking the fault characteristic variables as the input of MLP and the fault zone as the output, the fault zone identification model based on MLP is established. Then, fault zone can be identified by inputting fault characteristic variables extracted at measuring points to the trained model. A large number of simulations verify that the proposed method has high fault detection precision and can withstand a transition resistance of 300 Ω. |
| Key words: three-terminal hybrid UHVDC frequency characteristic multi-layer perception fault characteristic variables fault detection |
