Power Network Fault Location Using Traveling Waves and Continuous Wavelet Transform

doi:10.1109/PESGM48719.2022.9916846

	Power Network Fault Location Using Traveling Waves and Continuous Wavelet Transform
	Xu, Yun'an1 ; Liu, Yu1 ; Xing, Yiqi1 ; Nie, Yuan1 ; Huang, Wentao 2
	2022-07-21
会议录名称	2022 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM)
ISSN	1944-9925
发表状态	已发表
DOI	10.1109/PESGM48719.2022.9916846
摘要	Faults in a power network will cause propagation of traveling waves within the network. This paper proposes a new traveling wave based fault location method in a power network. For each terminal, the arrival time of the first wavefronts at the terminal is captured, to avoid the impact of complex reflections within the network. To accurately capture the arrival time and to reduce the impact of measurement noises, the tool of continuous wavelet transform (CWT) is adopted. The coefficients from CWT are normalized for each frequency, and the peak of the coefficient summation of different frequencies corresponds to the arrival time of wavefronts. With the arrival time information of traveling waves and line network parameters, the accurate fault section and fault location are determined. Simulation results show that, with measurement noises, the fault location accuracy of the proposed CWT based method is higher in comparison to methods with discretized wavelet transform (DWT), for various fault locations, types and transition resistances.
关键词	traveling wave power network fault location continuous wavelet transform
会议地点	Denver, CO, USA
会议日期	17-21 July 2022
URL	查看原文
收录类别	EI
语种	英语
来源库	IEEE
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/251930
专题	信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_刘宇组
通讯作者	Liu, Yu
作者单位	1.Shanghaitech University, School of Information Science and Technology, Shanghai; 201210, China; 2.Shanghai Jiao Tong University, Department of Electrical Power Engineering, Shanghai; 200240, China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Xu, Yun'an,Liu, Yu,Xing, Yiqi,et al. Power Network Fault Location Using Traveling Waves and Continuous Wavelet Transform[C],2022.