Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)

A Protection Algorithm Based on Transient Current Spectrum Characteristic for MMC-HVDC Line

Authors
Xingguo Wang
Corresponding Author
Xingguo Wang
Available Online April 2017.
DOI
10.2991/eame-17.2017.6How to use a DOI?
Keywords
MMC-HVDC transmission line; natural frequency; protection; transient current; spectrum characteristic
Abstract

When a fault occurs on a transmission line, fault generated high frequency transient components are a series of natural frequencies in frequency domain. This paper proposes a protection algorithm for MMC-HVDC transmission line based on spectrum characteristic of natural frequency. Spectrum correlation coefficient is used to determine whether a fault is internal or external fault. The scheme performance was proven using PSCAD/EMTDC simulations in ±500kV MMC-HVDC power system. The simulation results show that it can identify fault quickly and accurately.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/eame-17.2017.6
ISSN
2352-5401
DOI
10.2991/eame-17.2017.6How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xingguo Wang
PY  - 2017/04
DA  - 2017/04
TI  - A Protection Algorithm Based on Transient Current Spectrum Characteristic for MMC-HVDC Line
BT  - Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)
PB  - Atlantis Press
SP  - 21
EP  - 25
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-17.2017.6
DO  - 10.2991/eame-17.2017.6
ID  - Wang2017/04
ER  -