A Decision Tree Based Ultra-high-speed Protection Scheme for Meshed MMC-MTDC Grids with Hybrid Lines

Author:

Gaballah AmrORCID,Abu-Elanien Ahmed E. B.,Megahed Ashraf I.

Abstract

AbstractThe reliable operation of modular multi-level converter based multi-terminal high voltage direct current (MMC-MTDC) grids requires high-speed and selective DC line protection. A single-ended protection technique is proposed for MTDC grids with offshore wind farms and hybrid lines that involve overhead lines and submarine cables in series. Positive and negative poles’ currents at one end of each line section are analyzed using discrete wavelet analysis (DWA). To classify fault type and identify fault zone, a fine decision tree is supplied with an energy index and the envelope slop of detail 1 coefficient (D1) obtained from DWA. Only 0.2 ms following the fault inception are needed for calculating the energy index and the envelope slope to perform relay functions. The approach was tested on a three-terminal two-poles $$\pm$$ ± 400 kV MMC-MTDC model. The simulation results validate the effectiveness of the suggested protection technique under various fault scenarios, even with up to 200 Ω fault resistance. The proposed technique is not only able to detect the faulty line, but also it identifies overhead line faults and submarine cable faults for hybrid type lines. Moreover, the proposed technique is not affected by wind power injection changes, AC faults, or data noise. The simulated model was produced in the MATLAB/Simulink platform.

Funder

Alexandria University

Publisher

Springer Science and Business Media LLC

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Transmission Line Fault Detection and Classification Using Feature Extraction Based Self-Attention Convolutional Neural Network with Time Series Image;2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE);2024-04-26

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