802 / 2019-04-29 15:23:51
Fault Phase Identification Method Based on Convolutional Neural Network for Double Circuit Transmission Lines
convolutional neural network; double circuit transmission lines on the same tower; distance protection; fault phase identification; fault data.
Draft Accepted
Yiming Zhu / School of Electrical Engineering, University of Jinan, Jinan 250022, China
Yiqing Liu / School of Electrical Engineering, University of Jinan, Jinan 250022, China
Kai Wu / School of Electrical Engineering, University of Jinan, Jinan 250022, China
Model-driven distance protection cannot correctly identify the fault phases when it is applied to the DCTL (double circuit transmission lines on the same tower). This paper proposes a fault phase identification method based on CNN (convolutional neural network). The performance of the proposed method is verified by a larger number of fault data, and the results show that the proposed method can effectively identify the fault phases of the DCTL.
Important Date
  • Conference Date

    Oct 21

    2019

    to

    Oct 24

    2019

  • Oct 13 2019

    Abstract Notification of Acceptance

  • Oct 13 2019

    Draft paper submission deadline

  • Oct 14 2019

    Draft Paper Acceptance Notification

  • Oct 24 2019

    Registration deadline

  • Oct 29 2019

    Final Paper Deadline

Organized By
Xi'an Jiaotong University
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