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论文中文题名:

 高压直流输电线路的雷击识别研究    

姓名:

 王斐    

学号:

 19306204010    

保密级别:

 公开    

论文语种:

 chi    

学科代码:

 085207    

学科名称:

 工学 - 工程 - 电气工程    

学生类型:

 硕士    

学位级别:

 工程硕士    

学位年度:

 2023    

培养单位:

 西安科技大学    

院系:

 电气与控制工程学院    

专业:

 电气工程    

研究方向:

 电力系统    

第一导师姓名:

 高淑萍    

第一导师单位:

 西安科技大学    

论文提交日期:

 2023-12-21    

论文答辩日期:

 2023-12-13    

论文外文题名:

 Research on lightning strike identification of high-voltage direct current transmission lines    

论文中文关键词:

 高压直流输电线路 ; 雷击识别 ; 故障性雷击 ; 非故障性雷击 ; 神经网络    

论文外文关键词:

 HVDC transmission lines ; Lightning strike identification ; Failure lightning strikes ; Non-faulty lightning strikes ; neural network    

论文中文摘要:

近年来,我国科学技术不断提升,有效地促进了高压直流输电系统的发展。但是我国的高压输电系统运行情况与国外相比还是存在一些差距,安装的线路保护装置还是无法准确寻找故障。因此,当发生雷击时,为了能够降低雷击干扰对线路误触动的几率,提高可靠稳定的保护,更需研究直流线路雷击识别方法。本文基于国内外高压直流线路雷击识别的研究文献资料,对线路中存在的雷击干扰识别问题进行分析,所做研究工作内容如下:

(1)基于PSCAD/EMTDC电磁暂态仿真软件,根据±500kV高压直流系统的典型参数,搭建±500kV高压直流系统的交流系统、换流变压器、换流阀、交直流滤波器、平波电抗器和直流线路等一次侧电气元件模型;建立高压直流输电系统控制系统的仿真模型,并在其基础上中搭建高压直流输电系统雷击电磁暂态仿真模型,实现不同类型雷击故障和雷击干扰的电磁暂态仿真,并针对不同的雷击故障和非故障性雷击情况,分析其暂态特征和故障机理,归纳总结不同情况下波形变化规律。

(2)通过研究发现雷击故障和雷击干扰状况下电压时域变化的特性不同,因此通过改进Elman神经网络,增加一层隐含层,大幅度提高了网络过程中对历史信息处理的敏感度,而且减轻网络了对第一隐含层处理信息的压力,进而大大的提高了对网络信息的分析预测精度。因此可提出基于Elman神经网络高压直流输电线路识别雷击干扰的机理,并设计了相关的识别判据和算法。经过理论分析和仿真验证,该方案可以准确高效地实现故障区段的判断,可以有效识别线路的雷击干扰和雷击故障情况,判断机理清晰,且自适应性强。

(3)通过对输电线路的故障性雷击、非故障雷击和短路故障等暂态信号的小波能量谱分析发现,不同暂态信号在各频段的能量分布存在差异,为此提出了一种基于小波能量谱和BP神经网络理论的输电线路雷击与短路故障的识别方法。仿真结果表明该方法能够准确有效地识别线路上的非故障雷击、故障性雷击和普通短路故障3种暂态行波信号,且对过渡电阻不敏感,自适应性强。

 

 

论文外文摘要:

In recent years, China's science and technology have been continuously improved, which has effectively promoted the development of high-voltage direct current transmission system. However, there are still some gaps in the operation of China's high-voltage transmission system compared with foreign countries, and the installed line protection devices still cannot accurately find faults. Therefore, when lightning strikes occur, in order to reduce the probability of lightning interference on line false touches and improve reliable and stable protection, it is necessary to study the lightning strike identification method of DC line. Based on the research literature of lightning strike identification of high-voltage DC lines at home and abroad, this paper analyzes the lightning interference identification problems in the line, and the work content is as follows:

First, based on the PSCAD/EMTDC electromagnetic transient simulation software, according to the typical parameters of ±500 kV HVDC system, build the primary side electrical component model of the AC system, converter transformer, converter valve, AC and DC filter, flat wave reactor and DC line of ±500 kV HVDC system. establish the simulation model of the control system of HVDC transmission system, and build a lightning transient simulation model of HVDC transmission system on the basis to realize the electromagnetic transient simulation of different types of lightning strike faults and lightning interference, and analyze the transient characteristics and fault mechanism for different lightning fault and non-fault lightning strike situations, and summarize the waveform variation law of transient voltage under different conditions.

Second, it is found that the characteristics of voltage time domain changes under lightning strike fault and lightning interference conditions are different, so by improving the Elman neural network and adding an implied layer, the sensitivity to historical information processing in the network process is greatly improved, and the pressure on the network to process information in the first hidden layer is reduced, and the accuracy of analysis and prediction of network information is greatly improved. Therefore, the mechanism of identifying lightning interference based on Elman neural network HVDC transmission lines can be proposed, and the relevant identification criteria and algorithms can be designed. After theoretical analysis and simulation verification, the scheme can accurately and efficiently realize the judgment of fault sections, effectively identify the lightning interference and lightning fault conditions of the line, and the judgment mechanism is clear and adaptive.

Third, through the analysis of the wavelet energy spectrum of transient signals such as faulty lightning, non-faulty lightning strike and short-circuit fault of transmission line, it is found that the energy distribution of different transient signals in each frequency band is different, so a method for identifying lightning strike and short-circuit fault of transmission line based on wavelet energy spectrum and BP neural network theory is proposed. The simulation results show that the proposed method can accurately and effectively identify three transient traveling wave signals on the line: non-faulty lightning strike, faulty lightning strike and ordinary short-circuit fault, and is insensitive to transition resistance and has strong adaptability.

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中图分类号:

 TM615    

开放日期:

 2023-12-21    

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