Advanced fault location in MTDC networks utilising optically-multiplexed current measurements and machine learning approach

Abstract

This paper presents a method for accurate fault localisation of DC-side faults in Voltage Source Converter (VSC) based Multi-Terminal Direct Current (MTDC) networks utilising optically-multiplexed DC current measurements sampled at 5 kHz, off-line continuous wavelet transform and machine learning approach. The technical feasibility of optically-based DC current measurements is evaluated through laboratory experiments using commercially available equipment. Simulation-based analysis through Matlab/Simulink® has been adopted to test the proposed fault location algorithm under different fault types and locations along a DC grid. Results revealed that the proposed fault location scheme can accurately calculate the location of a fault and successfully identify its type. The scheme has been also found to be effective for highly resistive fault with resistances of up to 500 Ω. Further sensitivity analysis revealed that the proposed scheme is relatively robust to additive noise and synchronisation errors

A novel approach to estimate fault location in current source converter–based HVDC transmission line by Gaussian process regression

“…The comparative study between the proposed and conventional methods for the different critical application such as traditional CSC-based HVSC and VSC-based HVDC system is summarized in Table 9. [13][14][15][16][17][18] This study reveals that the proposed method has less complexity in comparison with Tzelepis et al 13 as the scheme proposed by the author requires installation of numerous current sensors comprising of highly synchronized two-end current data along the total length of the transmission line. [13][14][15][16][17][18] This study reveals that the proposed method has less complexity in comparison with Tzelepis et al 13 as the scheme proposed by the author requires installation of numerous current sensors comprising of highly synchronized two-end current data along the total length of the transmission line.…”

“…Despite provision of fast response and higher accuracy; the method is not convincing as its reliability is adversely affected due to the necessity for accurate detection of surge arrival time and requirement of synchronized data of two terminals. However, the proposed method in Tzelepis et al 13 demands the requirement of synchronized current data, which is to be harvested from the optical sensor allocated along the networks transmission line. The determination of fault location in a multi-terminal HVDC system using pattern matching-based method is studied in Tzelepis et al 13 by employing the continuous wavelet transform and Pearson correlation coefficient.…”

“…Comparison with existing schemesTzelepis et al13 Pattern matching-based scheme using current signal from sensors distributed along lines, which adopted CWT and Pearson correlation coefficient technique.Yang et al16 MLPNN-based scheme using frequency spectrum of two-end current data.Abbreviations: CSC, current source converter; HVDC, high-voltage direct current.…”

Centralised busbar differential and wavelet‐based line protection system for multi‐terminal direct current grids, with practical IEC‐61869‐compliant measurements

“…There are five modular multi-level converters (MMCs) in the network operating at ±400 kV (in symmetric monopole configuration), current-limiting inductors and hybrid circuit breakers (HbCBs). The MMC models utilised in this paper are identical to those used in [1,12,25,26] and the AC-DC network parameters are presented in Table 1. The lines have been modelled using a distributed parameter model.…”

Locating short-circuit faults in HVDC systems using automatically selected frequency-domain features

“…In this method, the discrete wavelet transform has been applied to the one‐end voltage and current measurements, and finally, the normalized wavelet energies have been used as inputs to the fault section classifier. Tzelepis et al have employed the continuous wavelet transform and the Pearson correlation coefficient to design a pattern matching–based fault‐location approach for multiterminal HVDC networks. This method has used the synchronized current data gathered from the optical sensors distributed along the network's transmission lines.…”