柔性直流配電網(wǎng)中接地故障檢測技術(shù)研究

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DOI：10.15938/j. emc.2025.04.006

中圖分類號：TM77 文獻標志碼：A 文章編號：1007-449X（2025）04-0054-11

Research on fault detection technology of flexible DC distribution network

ZHENG Feng1，LU Jiawen1，LIN Yanzhen2，LIANG Ning （1.School of Electrical Engineering and Automation，F(xiàn)uzhou University，F(xiàn)uzhou ，China; 2. State Grid Fujian Electric Power Co.，Ltd.，F(xiàn)uzhou ，China; 3.Faculty of Electric Power Enginering，Kunming Universityof Science and Technology，Kunming 65050o，China）

Abstract：To solve the problems of flexible DC power distribution system，including flexible operations， multiple fault types，and dificulty in fault identification，a fault detection method based on K-L divergence optimization variational mode decomposition （VMD） and convolution neural network （CNN） combined with Inception was proposed. Firstly，K-L VMD method was used to extract the feature component of the time-domain waveform of the positive transient voltage atthe fault point，and the identification criterion was constructed using the feature modal component. Then，CNN training was performed on the sampled data to obtain the optimal parameters of the model. Finally，a 10kV two-end DC distribution network structure based on modular multilevel converter （MMC）was built using the simulation platform to verify effctiveness of the proposed method. Simulation experiments show that K-L divergence optimization variational mode decomposition has good generalization ability and anti-interference ability to the simulation data. The proposed fault detection method is effective and has strong sensitivity to the identification of various fault types and can accurately identify the fault types.

Keywords：flexible DC distribution network； K-L divergence optimization； variational modal decomposi-tion；convolutional neural network ； fault detection；modular multilevel converter

0引言

隨著光伏和儲能等分布式電源的快速發(fā)展，交流配電網(wǎng)正面臨著供電走廊緊張、線路損耗大以及電能質(zhì)量差等一系列問題。（剩余15821字）