Abstract

Existing non-unit protection schemes are inevitably influenced by the high fault-resistance in MMC-HVDC grid, which is a serious problem affecting the rapidity and reliability of fault recognition. This study proposes a dynamic fitting of data reconstruction-based protection method to improve the accuracy and rapidity of HVDC grid protection. Due to the propagation characteristics of the initial voltage traveling wave being unaffected by the transition resistance, the self-adapting exponential fitting algorithm is used to recognize the fault waveform. Then, sliding data window with the voltage traveling wave fit by the optimal basis exponential fitting algorithm could avoid the influence of initial value selection on fitting convergence. Meanwhile, the original fault traveling wave is reconstructed by “Bayesian compressed sensing algorithm (BCSA)” in a low sampling rate. This method could reduce the operation response time of the proposed method to satisfy the ultra-high-speed requirement of MMC-HVDC grid and also adapt the limitation of sampling rate in existing protection devices. Practical case studies in PSCAD/EMTDC and protection prototype testing have demonstrated that the proposed method is effective under different fault locations, fault types, and high fault impedance.

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