徐方维, 郑鸿儒, 王川, et al. Online Insulation Identification of Transmission Cable in Offshore Wind Farm Based on Harmonic Current Amplification[J]. 2026, 46(1): 272-282.
DOI:
徐方维, 郑鸿儒, 王川, et al. Online Insulation Identification of Transmission Cable in Offshore Wind Farm Based on Harmonic Current Amplification[J]. 2026, 46(1): 272-282. DOI: 10.13334/j.0258-8013.pcsee.241510.
Online Insulation Identification of Transmission Cable in Offshore Wind Farm Based on Harmonic Current Amplification
Existing methods for cable insulation condition identification using signals such as partial discharges and DC leakage currents in cables are constrained by the weakness of the measurement signals
which makes it difficult to be effectively applied in practice. This paper proposes a novel method to identify the insulation condition of transmission cables in offshore wind farm online based on the correlation between the amplification factor of the harmonic currents (i.e.
the ratio of the amplitude of the harmonic currents at both ends of the cable) and the cable insulation condition. It has been found that within the nominal cross-section and length of offshore wind farm transmission cable and the possible grid strength at the grid connection point
the current amplification factors corresponding to some harmonics below the 25th order are highly sensitive to cable insulation parameters. Given this perspective
the correlation function between the harmonic current amplification factor and the insulation parameter of the cable is constructed
then a set of overdetermined equations is established based on the harmonic measurement data at different moments
and finally
the insulation parameter is solved by using the Levenberg-Marquardt algorithm. Compared with the existing methods
the proposed method only uses harmonic measurements
which is easy to obtain
and practical cases verify the effectiveness of the method.
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Related Author
GE Xiaolin
YAN Xin
FU Yang
SHEN Wentao
WEI Shurong
ZHENG Xiaoxia
WANG Shuyang
ZHOU Zexin
Related Institution
College of Automation Engineering, Shanghai University of Electric Power, Yangpu District
Electric Power Engineering School, Shanghai University of Electric Power, Yangpu District
Engineering Research Center of Offshore Wind Technology Ministry of Education (Shanghai University of Electric Power), Yangpu District
State Grid Zhejiang Electric Power Co., Ltd. Research Institute
State Key Laboratory of Power Grid Safety (China Electrical Power Research Institute), Haidian District