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基于行波解析分析的柔性直流输电线路故障智能检测方法OA北大核心CSTPCD

Intelligent Fault Detection Method for Flexible DC Transmission Lines Based on Prior Experience and of Travelling Wave Expression

中文摘要英文摘要

故障数据匮乏是制约数据驱动故障检测方法应用的重要原因,为解决这一问题,提出一种基于行波解析分析的柔直输电线路故障智能检测方法.根据行波表达式生成训练样本,有效表达区内、外故障行波具有的主要特征.通过构造多层感知器(multi-layer perception,MLP)模型建立该行波特征与故障位置之间的映射关系,进而输出故障检测结果.最后,在PSCAD/EMTDC中搭建双端柔直系统模型,生成仿真样本,对训练后的智能检测模型进行测试.结果表明:该方法不依赖于大量历史故障数据,基于行波解析表达式这一继电保护领域知识提取行波特征,即可准确识别直流线路的区内外故障,并且具有较强的耐受过渡电阻能力,为解决传统模型受制于历史故障数据问题提供了一种可行思路.

The lack of fault data is an important reason restricting the application of data-driven fault detection methods.To solve this problem,this paper propose an intelligent fault detection method of flexible HVDC line based on travelling wave(TW)analysis.Based on the prior experience of TW analytic expression,training samples are generated to effectively express the main characteristics of the internal and external fault TW.A multi-layer perception(MLP)model is constructed to establish the mapping relationship between the wave characteristics and the fault location and then output the fault detection result.Finally,a two-terminal flexible DC transmission system model is built in PSCAD/EMTDC,and the simulation samples are generated to test the trained model.The results show that this method does not rely on a large number of historical fault data.Based on the knowledge in the relay protection field of TW analytic expression,the TW characteristics is extracted and the internal and external faults of the DC line are accurately identified.This method has strong tolerance to fault resistance,and provides a feasible way to solve the problem that the traditional model is subject to historical fault data.

张绮轩;李海锋;梁远升;王钢

华南理工大学 电力学院,广东 广州 510641

动力与电气工程

柔直输电线路暂态等值电路故障行波人工智能故障检测

flexible DC transmission linetransient equivalent circuitfault travelling waveartificial intelligencefault detection

《广东电力》 2024 (005)

计及换流站控制特性的多端混合直流线路故障分析与继电保护研究

84-96 / 13

国家自然科学基金项目(52077082)

10.3969/j.issn.1007-290X.2024.05.009

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