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Variance-Empirical Mode Decomposition Method for Fault Detection in MMC-HVDC Transmission Lines
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DOI：10.1002/ese3.70595.png)
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Abstract
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In this paper, a new method for fast and accurate fault detection in HVDC transmission lines based on modular multilevel converters (MMC HVDC) is presented. The proposed method, named variance-based empirical mode decomposition (VEMD), relies on the statistical analysis of the variance of voltage and current signals measured from one side of the line and their decomposition using the empirical mode decomposition algorithm. As an indicator sensitive to sudden changes, variance highlights the transient characteristics caused by the occurrence of a fault, and the decomposition of the signal into oscillatory intrinsic mode functions allows the extraction of hidden frequency components. The performance of the proposed method has been evaluated through extensive simulation in the PSCAD environment and implementation in MATLAB software, as well as practical testing on a hardware system. The results show that the VEMD method is capable of detecting various types of faults, including high-impedance faults up to 200 Ω, at different locations along the transmission line (25% to 90% of the line length). The fault detection time in noise-free conditions is 12.46 ms on average, and in the presence of measurement noise with a signal-to-noise ratio of 40 dB, it is up to 22.25 ms. These results indicate the high accuracy, reasonable speed, noise immunity, and stable performance of the proposed method and demonstrate that the VEMD method can be used as a practical, reliable, communication-link-free solution for protecting MMC-based HVDC transmission lines.
Keywords:
EMD
HVDC lines
MMC-HVDC
power system protection
signal processing
Variance
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