Experimental testing of the artificial neural network based protection of power transformers

被引:114
|
作者
Zaman, MR [1 ]
Rahman, MA [1 ]
机构
[1] Mem Univ Newfoundland, Fac Engn & Appl Sci, St Johns, NF A1B 3X5, Canada
关键词
D O I
10.1109/61.660922
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This work presents a novel technique to distinguish between magnetizing inrush and internal fault currents of a power transformer. The proposed differential algorithm is based on artificial neural network (ANN) and unlike the existing relaying techniques, this method is independent of the harmonic contents of the differential current. a novel neural network is designed and trained using back-propagation algorithm with experimental data. After training the network, simulation and on-line tests are carried out to evaluate the performance of the ANN based algorithm under different fault and energization conditions. Both simulation and experimental, results are quite satisfactory.
引用
收藏
页码:510 / 517
页数:8
相关论文
共 50 条
  • [21] Artificial Neural Network Based Load Blinder for Distance Protection
    Zadeh, H. Khorashadi
    Li, Z.
    2008 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, VOLS 1-11, 2008, : 4205 - 4210
  • [22] An Artificial Neural Network Based Technique for Protection of HVDC Grids
    Abu-Elanien, Ahmed E. B.
    2019 IEEE PES GTD GRAND INTERNATIONAL CONFERENCE AND EXPOSITION ASIA (GTD ASIA), 2019, : 1004 - 1009
  • [23] Reactive Power Compensation Based on Artificial Neural Network
    Bayindir, Ramazan
    Sagiroglu, Seref
    Colak, Ilhami
    JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, 2007, 10 (02): : 129 - 135
  • [24] Power system equivalent based on an artificial neural network
    Pavic, I
    Hebel, Z
    Delimar, M
    ITI 2001: PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY INTERFACES, 2001, : 359 - 365
  • [25] On the Application of Artificial Neural Network for Classification of Incipient Faults in Dissolved Gas Analysis of Power Transformers
    Thango, Bonginkosi A.
    MACHINE LEARNING AND KNOWLEDGE EXTRACTION, 2022, 4 (04): : 839 - 851
  • [26] Artificial Neural Network Technique for Transmission Line Protection on Nigerian Power System
    Uzubi, Uma
    Ekwue, Arthur
    Ejiogu, Emenike
    2017 IEEE PES POWERAFRICA CONFERENCE, 2017, : 52 - 58
  • [27] A Novel Methodology for Power Transformer Differential Protection by incorporating Artificial Neural Network
    Bhatt, Nimish
    Rahi, O. P.
    Bharadwaj, Nitish
    2016 INTERNATIONAL CONFERENCE ON ELECTRICAL POWER AND ENERGY SYSTEMS (ICEPES), 2016, : 68 - 74
  • [28] Virtual Instrument based Fault Classification in Power Transformers using Artificial Neural Networks
    Nanda, Santosh Kumar
    Gopalakrishna, S.
    2013 IEEE 1ST INTERNATIONAL CONFERENCE ON CONDITION ASSESSMENT TECHNIQUES IN ELECTRICAL SYSTEMS (CATCON), 2013, : 169 - 173
  • [29] Fault Diagnosis of Power Transformers Based on Membrane Computing Optimizing Neural Network
    Yuan Zhijian
    Deng Hao
    Liu Wenjun
    GREEN POWER, MATERIALS AND MANUFACTURING TECHNOLOGY AND APPLICATIONS II, 2012, 214 : 740 - +
  • [30] Power Transformers Fault Diagnosis based on fuzzy-RBF neural network
    Duan, Huida
    Yao, Xin
    ADVANCES IN POWER AND ELECTRICAL ENGINEERING, PTS 1 AND 2, 2013, 614-615 : 1303 - 1306