Modeling and Simulation of Time Domain Reflectometry Signals on a Real Network for Use in Fault Classification and Location

被引:3
|
作者
Fornas, Javier Granado [1 ]
Jaraba, Elias Herrero [2 ]
Bludszuweit, Hans [1 ]
Garcia, David Cervero [1 ]
Estopinan, Andres Llombart [1 ]
机构
[1] CIRCE Fdn Parque Empresarial Dinamiza, Zaragoza 50018, Spain
[2] Univ Zaragoza, Dept Elect Engn & Commun, Zaragoza 50018, Spain
基金
欧盟地平线“2020”;
关键词
Distribution networks; Fault location; Load modeling; Databases; Couplers; PSCAD; Data models; Fault classification; fault location; transmission lines; time-domain pulse reflectometry; modelling networks; distribution networks; DISTRIBUTION-SYSTEMS; LINES;
D O I
10.1109/ACCESS.2023.3253772
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Today, the classification and location of faults in electrical networks remains a topic of great interest. Faults are a major issue, mainly due to the time spent to detect, locate, and repair the cause of the fault. To reduce time and associated costs, automatic fault classification and location is gaining great interest. State-of-the-art techniques to classify and locate faults are mainly based on line-impedance measurements or the detection of the traveling wave produced by the event caused by the fault itself. In contrast, this paper describes the methodology for creating a database and a model for a complex distribution network. Both objectives are covered under the paradigm of the time-domain pulse reflectometry (TDR) principle. By using this technique, large distances can be monitored on a line with a single device. Thus, in this way a database is shared and created from the results of simulations of a real and complex distribution network modeled in the PSCAD(TM) software, which have been validated with measurements from an experimental test setup. Experimental validations have shown that the combination of the TDR technique with the modeling of a real network (including the real injector and the network coupling filter from the prototype) provides high-quality signals that are very similar and reliable to the real ones. In this sense, it is intended firstly that this model and its corresponding data will serve as a basis for further processing by any of the existing state-of-the-art techniques. And secondly, to become a valid alternative to the already well-known Test Feeders but adapted to work groups not used to the electrical world but to the environment of pure data processing.
引用
收藏
页码:23596 / 23619
页数:24
相关论文
共 50 条
  • [1] Application of Deconvolution for Wire Fault Location Using Time Domain Reflectometry
    Shi, Qinghai
    Kanoun, Olfa
    2012 IEEE SENSORS PROCEEDINGS, 2012, : 1380 - 1383
  • [2] Analysis of spread spectrum time domain reflectometry for wire fault location
    Smith, P
    Furse, C
    Gunther, J
    IEEE SENSORS JOURNAL, 2005, 5 (06) : 1469 - 1478
  • [3] CHAOS TIME-DOMAIN REFLECTOMETRY FOR FAULT LOCATION ON LIVE WIRES
    Xu, Hang
    Li, Jingxia
    Liu, Li
    Wang, Bingjie
    Zhang, Jianguo
    Wang, Yuncai
    JOURNAL OF APPLIED ANALYSIS AND COMPUTATION, 2015, 5 (02): : 243 - 250
  • [4] A New Algorithm for Wire Fault Location Using Time-Domain Reflectometry
    Shi, Qinghai
    Kanoun, Olfa
    IEEE SENSORS JOURNAL, 2014, 14 (04) : 1171 - 1178
  • [5] Spread Spectrum Time Domain Reflectometry (SSTDR) Digital Twin Simulation of Photovoltaic Systems for Fault Detection and Location
    Kingston, Samuel R.
    Flamme, Cody La
    Saleh, Mashad U.
    Ellis, Hunter
    Benoit, Evan
    Edun, Ayobami
    Scarpulla, Michael A.
    Furse, Cynthia M.
    Harley, Joel B.
    Progress In Electromagnetics Research B, 2021, 94 : 105 - 126
  • [6] On Line Wire Diagnosis using Multicarrier Time Domain Reflectometry for Fault Location
    Lelong, Adrien
    Carrion, Marc O.
    2009 IEEE SENSORS, VOLS 1-3, 2009, : 751 - 754
  • [7] The model of the power lines fault location method using time domain reflectometry
    Shagiev, R. I.
    Karpov, A. V.
    Kalabanov, S. A.
    INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGIES IN BUSINESS AND INDUSTRY 2016, 2017, 803
  • [8] Active Fault Location in Distribution Network using Time-Frequency Reflectometry
    Ghaderi, Amin
    Mohammadpour, Hossein Ali
    Ginn, Herbert
    2015 IEEE POWER AND ENERGY CONFERENCE AT ILLINOIS (PECI), 2015,
  • [9] Soft Fault Identification in Electrical Network Using Time Domain Reflectometry and Neural Network
    Laib, A.
    Melit, M.
    Nekhoul, B.
    Drissi, K. El Khamlichi
    Kerroum, K.
    ADVANCED CONTROL ENGINEERING METHODS IN ELECTRICAL ENGINEERING SYSTEMS, 2019, 522 : 365 - 376
  • [10] Estimation of fault location on a power line using the time-frequency domain reflectometry
    Doo, Seung-Ho
    Kwak, Ki-Seok
    Park, Jin-Bae
    Transactions of the Korean Institute of Electrical Engineers, 2008, 57 (02): : 268 - 275