Rapid Fault Diagnosis of a Back-to-Back MMC-HVDC Transmission System under AC Line Fault

Abstract

Abstract:The integration of a modular multilevel converter-based high-voltage direct current (MMC-HVDC) transmission system in power networks has led to a high requirement for the rapidity of fault recognition. This study focused on the rapid fault diagnosis of an alternating current (AC) line fault in a back-to-back (BTB) MMC-HVDC system via fault detection and classification. Discrete wavelet transform and modulus maxima were applied to extract the fault features. Phase-mode transformation and normalization were adopted to widen the application range. Simulation and calculation results indicated that the proposed method can detect all fault types in an AC transmission line on the basis of single-side fault information within 1 ms under different values of transition resistance, fault inception angle, and fault distance. The BTB MMC-HVDC model was built using real-time laboratory (RT-LAB) based on the matrix laboratory (MATLAB) software platform, and the fault diagnosis algorithm was performed in MATLAB.

Fault Diagnosis with Wavelet Packet Transform and Principal Component Analysis for Multi-terminal Hybrid HVDC Network

“…To further highlight the advantages of the proposed method in this aspect of fault classification, Table IV provides comparative data of several methods. From them, the method proposed in [14] shows that the threshold criteria for single-, two-, and three-phase-to-ground faults are greater than 0.05, less than 0.05, and equal to 0, respectively. Compared with the method proposed in this paper, the threshold criterion of the method in [14] is too small, and it may not be able to accurately determine the fault type.…”

“…From them, the method proposed in [14] shows that the threshold criteria for single-, two-, and three-phase-to-ground faults are greater than 0.05, less than 0.05, and equal to 0, respectively. Compared with the method proposed in this paper, the threshold criterion of the method in [14] is too small, and it may not be able to accurately determine the fault type. Meanwhile, this method has smaller differences in the criteria for the same type of fault.…”

“…Fault diagnosis technology has always been one of the research hotspots of hybrid HVDC transmission, and some researchers have conducted in-depth research on it in HVDC transmission networks. Reference [14] uses discrete wavelet transform (WT) and phase-mode transformation to extract the modulus maxima and criterion factor of the signal that can be used as the criterion of fault time and fault types, which can realize fault detection and fault classification within 1 ms. However, the difference in criterion factors between different types of faults is relatively small.…”

A comprehensive review of fault diagnosis and fault-tolerant control techniques for modular multi-level converters

“…For AC side faults, in, 47 the authors proposed a method to detect and classify faults on the AC side of MMC. The feature extraction phenomenon uses discrete wavelets transform (DWT) and modulus maxima (MM).…”