A DC Fault Protection Scheme in MMC-Based HVDC Systems Based on the DC Fault Current Characteristics

Abstract

DC fault is one of the critical issues in modular multilevel converter (MMC)-based high voltage DC (HVDC) systems. Existing DC fault detection schemes suffer from several limitations, including poor sensitivity to high-resistance faults, low noise immunity, high sampling-frequency requirements, and significant computational burden. To address these limitations, this article proposes a novel wavelet function derived from the transient characteristics of fault currents in MMC-based HVDC systems to optimize the performance of the wavelet transform for DC fault detection. This work rigorously presents the mathematical equations describing the parameters of the proposed transient fault current-based wavelet function, and a systematic, step-by-step design procedure is comprehensively explained. Furthermore, a performance index, termed the similarity factor, is introduced to evaluate the performance of the proposed wavelet compared to conventional alternatives. Based on the proposed wavelet function, a novel DC fault detection scheme is developed, providing enhanced noise immunity compared with the conventional methods. In addition, unlike conventional approaches, the proposed scheme exhibits high capability to detect high-resistance DC faults up to 2.5 p.u. while substantially lowering both computational time and sampling-frequency requirements. The effectiveness of the proposed scheme is validated through real-time simulations and experiments on a scaled-down prototype.