Analyses of different approaches for detecting, classifying and locating faults in a three-terminal VSC-HVDC system

Julio Arita Torres*, Ricardo Caneloi dos Santos, Qingqing Yang, Jianwei Li

*Corresponding author for this work

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Abstract

This paper presents three intelligent approaches for fault detection, classification and location in a three-terminal VSC-HVDC system. The proposed approaches are all based on ANNs, although each one has a specific pre-processing step to process the DC current samples. The approaches were implemented in Matlab, while the adopted three-terminal VSC-HVDC system was modelled in PSCAD. A large number of fault cases differing with respect to fault location, fault type and fault resistance were specifically generated to develop, test and compare the solutions presented here. The observed results encourage the application of the proposed approaches in practical situations, as a good performance was verified regardless the fault case characteristics. In terms of fault detection and classification functions the response time is always within 2 ms, while for fault location function the average accuracy is 1.7%.

Original languageEnglish
Article number107514
JournalInternational Journal of Electrical Power and Energy Systems
Volume135
DOIs
Publication statusPublished - Feb 2022
Externally publishedYes

Keywords

  • Artificial neural networks
  • Discrete wavelet transform
  • Fault detection
  • Fault location
  • HVDC protection
  • Pattern recognition

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Arita Torres, J., dos Santos, R. C., Yang, Q., & Li, J. (2022). Analyses of different approaches for detecting, classifying and locating faults in a three-terminal VSC-HVDC system. International Journal of Electrical Power and Energy Systems, 135, Article 107514. https://doi.org/10.1016/j.ijepes.2021.107514