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Accurate Fault Location of Multi Terminal DC Distribution Network Based on Improved Red Fox Optimization Algorithm
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Yan XU, Qi-zun TANG*, Zi-qi YAO, Jia-yi SUN
Science Technology and Engineering | 2025, 25(17) : 7197 - 7207
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Science Technology and Engineering | 2025, 25(17): 7197-7207
Papers-Electrical Technology
Accurate Fault Location of Multi Terminal DC Distribution Network Based on Improved Red Fox Optimization Algorithm
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Yan XU, Qi-zun TANG*, Zi-qi YAO, Jia-yi SUN
Affiliations
  • State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, China
Published: 2025-06-18 doi: 10.12404/j.issn.1671-1815.2405254
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With the development of DC (direct current ) distribution networks and the large-scale integration of distributed energy storage and photovoltaics into the distribution network, the structure of the distribution network has undergone revolutionary changes. After a short circuit fault occurs in the DC distribution network, the short circuit voltage drops sharply, the short circuit current rises rapidly, and the stability of the power system operation is disrupted. To address this issue, a model for inter pole and single pole short circuit faults in DC systems was proposed. Firstly, by sampling voltage data at both ends of the DC line, the voltage equation was written, and the transition resistance was eliminated. Then, a fitness function was constructed, and the adaptive optimization red fox algorithm with faster convergence speed and higher positioning accuracy was used to calculate the distance from the fault point to the protection installation site for fault location in the DC distribution network. Based on the red fox algorithm, combined with the isolation forest algorithm to remove abnormal data, the algorithm performance and accuracy were improved by improving adjustable feedback factors and introducing genetic crossover operators. When the sampling frequency is low, the accuracy of fault localization is improved through adaptive interpolation. Simulation verification was conducted in Simulink, and the results show that the method has strong resistance to transition resistance, small positioning error, is not affected by system parameters, and can effectively reduce the impact of low sampling frequency on fault localization, and has good robustness.

DC distribution network  /  fault location  /  parameter identification  /  DC system  /  accurate positioning  /  isolation forest  /  improved red fox optimization
Yan XU, Qi-zun TANG, Zi-qi YAO, Jia-yi SUN. Accurate Fault Location of Multi Terminal DC Distribution Network Based on Improved Red Fox Optimization Algorithm[J]. Science Technology and Engineering, 2025 , 25 (17) : 7197 -7207 . DOI: 10.12404/j.issn.1671-1815.2405254
Year 2025 volume 25 Issue 17
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doi: 10.12404/j.issn.1671-1815.2405254
  • Receive Date:2024-07-12
  • Online Date:2025-12-15
  • Published:2025-06-18
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  • Received:2024-07-12
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    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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