Chinese Journal of Ship Research, Volume. 20, Issue 2, 89(2025)

Fault location method for island and reef distributed power supply system based on immune model and improved immune algorithm

Weibo LI1,2, Maojie ZHANG1, Chenghu XU1, Hao ZHANG1, and Hualiang FANG3
Author Affiliations
  • 1School of Automation, Wuhan University of Technology, Wuhan 430070, China
  • 2College of Electrical Engineering, Northwest Minzu University, Lanzhou 730124, China
  • 3School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
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    Objective

    In order to improve the rapidity and accuracy of fault location for island and reef power supply systems composed of multiple distributed power sources, a fault location method based on an immune model and improved immune algorithm is proposed.

    Methods

    First, the immune model is used to divide the island and reef power supply system into several cell sections containing monitoring points. According to the monitored fault current signal, the cell section where the fault point is located is determined in order to minimize the fault determination range. The fault points of the cell section are then coded and the antibody population is generated by the improved immune algorithm, enabling the fault section to be quickly and accurately located for a second time, thus greatly reducing the calculation load.

    Results

    According to the Matlab simulation results of a typical island and reef power supply system, the immune model and improved immune algorithm combination can realize rapid fault location under various fault conditions, with such advantages as high positioning accuracy, light calculation load and fast solution speed.

    Conclusion

    The results of this study can provide useful references for the design of island and reef power supply systems.

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    Weibo LI, Maojie ZHANG, Chenghu XU, Hao ZHANG, Hualiang FANG. Fault location method for island and reef distributed power supply system based on immune model and improved immune algorithm[J]. Chinese Journal of Ship Research, 2025, 20(2): 89

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    Paper Information

    Category: Ship Intelligent O&M, and Fault Diagnosis

    Received: Oct. 17, 2023

    Accepted: --

    Published Online: May. 15, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.03598

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