A Review and Taxonomy on Fault Analysis in Transmission Power Systems

被引:5
作者
Al Mtawa, Yaser [1 ]
Haque, Anwar [2 ]
Halabi, Talal [3 ]
机构
[1] Univ Winnipeg, Dept Appl Comp Sci, Winnipeg, MB R3B 2E9, Canada
[2] Western Univ, Dept Comp Sci, London, ON N6A 5B7, Canada
[3] Laval Univ, Dept Comp Sci & Software Engn, Quebec City, PQ G1V 0A6, Canada
关键词
power system; smart grid; fault analysis; fault identification; fault detection; fault localization; SUPPORT VECTOR MACHINE; KALMAN FILTER; LOCATION TECHNIQUE; GENETIC-ALGORITHM; BAYESIAN NETWORKS; NEURAL-NETWORK; SHORT-CIRCUIT; CLASSIFICATION; LINES; MODEL;
D O I
10.3390/computation10090144
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Enhancing resiliency in a power grid system is one of the core mandates of electrical distribution companies to provide high-level service. The power resiliency research community has proposed numerous schemes, to detect, classify, and localize fault events. However, the literature still lacks a comprehensive taxonomy of these schemes which can help advance future research. This study aims to provide a compact yet comprehensive review of the state-of-the-art solutions to fault analysis in transmission power systems. We discuss fault types and several fault-analysis methodologies adopted by relevant research works, propose a novel framework to classify these works, and highlight their strengths and limitations. We anticipate that this brief review would be helpful as a literature review and benefit the research community in choosing suitable techniques for fault analysis.
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收藏
页数:19
相关论文
共 104 条
  • [1] Abass A.Z., 2021, J ROBOT CONTROL, V2, P134
  • [2] IoT-Enabled Smart Energy Grid: Applications and Challenges
    Abir, S. M. Abu Adnan
    Anwar, Adnan
    Choi, Jinho
    Kayes, A. S. M.
    [J]. IEEE ACCESS, 2021, 9 : 50961 - 50981
  • [3] Hurricane Sandy: Lessons Learned, Again
    Abramson, David M.
    Redlener, Irwin
    [J]. DISASTER MEDICINE AND PUBLIC HEALTH PREPAREDNESS, 2012, 6 (04) : 328 - 329
  • [4] A novel fault classification technique for double-circuit lines based on a combined unsupervised/supervised neural network
    Aggarwal, RK
    Xuan, QY
    Dunn, RW
    Johns, AT
    Bennett, A
    [J]. IEEE TRANSACTIONS ON POWER DELIVERY, 1999, 14 (04) : 1250 - 1256
  • [5] Reliability-based fault analysis models with industrial applications: A systematic literature review
    Ahmed, Qadeer
    Raza, Syed Asif
    Al-Anazi, Dahham M.
    [J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2021, 37 (04) : 1307 - 1333
  • [6] Al Mtawa Y., 2021, P 2021 INT WIRELESS, P1569
  • [7] Al Mtawa Y, 2016, IEEE WCNC
  • [8] Identifying Bounds on Sensing Coverage Holes in IoT Deployments
    Al Mtawa, Yaser
    Hassanein, Hossam S.
    Nasser, Nidal
    [J]. 2015 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2015,
  • [9] Decision tree analysis to identify harmful contingencies and estimate blackout indices for predicting system vulnerability
    Aliyan, Ehsan
    Aghamohammadi, Mohammadreza
    Kia, Mohsen
    Heidari, Alireza
    Shafie-khah, Miadreza
    Catalao, Joao P. S.
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2020, 178
  • [10] [Anonymous], 2002, P IEEE INT C PRIV SE