Fault detection and mitigation in MVDC grids using a Non-Unit Voltage Ratio Derivative Algorithm

Future MVDC grids will be used to reinforce the grid infrastructure enhancing transmission capabilities, minimizing losses, and providing capability to compensate reactive power as well as to control load flows. This paper addresses the protection of MVDC grids, which is one of the main challenges to be overcome, before taking advantage of all the inherent benefits that this technology will bring. The main objective of this paper is to validate a non-unit voltage derivative fault detection algorithm in a MVDC grid with green hydrogen production. The performance is analyzed with different fault cases and fault locations. As a main conclusion, the distance is the most relevant factor, which affects detection and tripping times.

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Publication Details

Journal
Renewable Energy and Power Quality Journal
Published
2024-08-10
DOI
https://doi.org/10.52152/4029
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00

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article

Fault detection and mitigation in MVDC grids using a Non-Unit Voltage Ratio Derivative Algorithm

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Renewable Energy and Power Quality Journal
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article

Fault detection and mitigation in MVDC grids using a Non-Unit Voltage Ratio Derivative Algorithm

P. Eguía, A. Iturregi, Antonio Blázquez, M.J. Pérez-Molina, D.M. Larruskain, E. Torres
article en

Abstract

Future MVDC grids will be used to reinforce the grid infrastructure enhancing transmission capabilities, minimizing losses, and providing capability to compensate reactive power as well as to control load flows. This paper addresses the protection of MVDC grids, which is one of the main challenges to be overcome, before taking advantage of all the inherent benefits that this technology will bring. The main objective of this paper is to validate a non-unit voltage derivative fault detection algorithm in a MVDC grid with green hydrogen production. The performance is analyzed with different fault cases and fault locations. As a main conclusion, the distance is the most relevant factor, which affects detection and tripping times.

Renewable Energy and Power Quality Journal
Oceanic Platform of the Canary Islands (ES), University of the Basque Country (ES), Ente Vasco de la Energía (ES)
European Commission, Eusko Jaurlaritza
Openalex Percentile: Top 80%
Smart Grid Security and Resilience
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