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Research on Management Efficiency Optimization of HVDC Power Supply System Based on Genetic Algorithm
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Jun WU1, Guohui MU1, Wenjun LIU1, Mengqi LI2
Journal of Power Supply | 2025, 23(1) : 181 - 187
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Journal of Power Supply | 2025, 23(1): 181-187
• Power System •
Research on Management Efficiency Optimization of HVDC Power Supply System Based on Genetic Algorithm
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Jun WU1, Guohui MU1, Wenjun LIU1, Mengqi LI2
Affiliations
  • 1 State Grid Zhejiang Ningbo Fenghua Power Supply Company, Ningbo 315500, China
  • 2 School of Economics and Management, Northeast Electric Power University, Jilin 132012, China
Published: 2025-01-30 doi: 10.13234/j.issn.2095-2805.2025.1.181
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The power supply load of a high voltage direct current (HVDC) power supply system is prone to be affected by signal interruption, which will result in the unstable operation of power supply system. To effectively improve the management efficiency of power supply system, an optimization method for the management efficiency of HVDC power supply system based on genetic algorithm is proposed. The optimization of management efficiency is transformed into the problem of load distribution, and a load distribution control strategy of efficiency optimization is adopted to reasonably distribute the load current in the HVDC power supply system. The genetic algorithm is used to optimize the management efficiency of the HVDC power supply system, so as to optimize its management efficiency. Experimental results show that the system management efficiency can be adjusted through the independent operation of dual power supplies, thereby improving the efficiency of power supply system. In addition, the running time of this method was maintained at 90-120 s, the optimization time was short, and the efficiency was high.

High voltage direct current (HVDC)  /  power supply system  /  management efficiency  /  genetic algorithm  /  load distribution
Jun WU, Guohui MU, Wenjun LIU, Mengqi LI. Research on Management Efficiency Optimization of HVDC Power Supply System Based on Genetic Algorithm[J]. Journal of Power Supply, 2025 , 23 (1) : 181 -187 . DOI: 10.13234/j.issn.2095-2805.2025.1.181
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Year 2025 volume 23 Issue 1
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Article Info
doi: 10.13234/j.issn.2095-2805.2025.1.181
  • Receive Date：2022-03-04
  • Online Date：2025-07-09
  • Published：2025-01-30
Article Data
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History
  • Received：2022-03-04
  • Accepted：2022-04-06
Affiliations
    1 State Grid Zhejiang Ningbo Fenghua Power Supply Company, Ningbo 315500, China
    2 School of Economics and Management, Northeast Electric Power University, Jilin 132012, China
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