Detecting Current Transformer Measurement Errors Using Double Decomposition Method

Detecting Current Transformer Measurement Errors Using Double Decomposition Method

Current transformer (CT) ensures the safe and stable operation of the power system by monitoring, measuring and protecting the current in the power grid. However, the CT measurement errors undermine the fairness of power trading. A double decomposition method is proposed to locate the abnormal phase...

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Bibliographic Details
Main Authors: Bolun Du, Yinglong Diao, Huan Wang, Xiujuan Zeng, Tong Liu, Yiyi Peng
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Current transformer
measurement errors
variational mode decomposition
wavelet decomposition
T-distributed stochastic neighbor embedding
kernel density estimation
Online Access:https://ieeexplore.ieee.org/document/11031411/
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Summary:Current transformer (CT) ensures the safe and stable operation of the power system by monitoring, measuring and protecting the current in the power grid. However, the CT measurement errors undermine the fairness of power trading. A double decomposition method is proposed to locate the abnormal phase and detect the CT measurement error in this study. Firstly, a variational mode decomposition (VMD) is used to decompose the measured CT secondary side phase currents to generate residuals. Meanwhile, wavelet decomposition is applied to decompose the residuals in multiple layers, and the approximate coefficient set of each phase is screened. Then, t-distributed stochastic neighbor embedding (t-SNE) is utilized to extract CT deterioration feature from the approximate coefficient set. Finally, the CT measurement error overrun threshold is calculated by means of kernel density estimation (KDE) to locate the abnormal phase and detect the CT measurement errors. In China Electric Power Research Institute, the proposed CT measurement error detection method can accurately locate the abnormal phase of CT and detect the 0.2% ratio difference threshold in the verification experiment. In the follow-up study, the proposed method in the study will be verified and supplemented based on CT data in the real distribution network environment.
ISSN:2169-3536

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