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Enhanced fault ride-through control for grid-forming inverters: comparative analysis and adaptive strategies

  • Liang Yuan
  • , Zheng Liang
  • , Hua Han*
  • , Mingxin Hu
  • , Xubin Liu
  • , Zhao Yang Dong
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

13 Downloads (CityUHK Scholars)

Abstract

As renewable energy technologies increasingly dominate as primary power sources, grid-forming (GFM) inverters have emerged as crucial components for future low inertia power systems, offering flexible inertia support and autonomous grid-forming capabilities. However, their integration poses significant challenges, especially in maintaining fault ride-through (FRT) capabilities, which are constrained by the inverters’ limited overcurrent capacity. This paper evaluates three distinct FRT strategies for GFM inverters: additional power control, direct current injection, and switching-following-type control. By establishing energy functions for each strategy, the transient stability is thoroughly analyzed, and the influence of key parameters is systematically investigated. Theoretical analysis and simulations are conducted to examine the impacts of control parameters and fault voltage sag depths, providing insights into system behavior under diverse fault conditions. To further enhance the FRT performance, an adaptive reactive power coefficient and enhanced multi-mode FRT control are proposed to maximize the inverter's active support capability and achieving improved fault response under various voltage sags and swells. The effectiveness of the proposed control scheme is validated through extensive simulations using PSCAD/EMTDC. © 2025 The Author(s)
Original languageEnglish
Article number111066
Number of pages15
JournalInternational Journal of Electrical Power and Energy Systems
Volume172
Online published1 Oct 2025
DOIs
Publication statusPublished - Nov 2025

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 52307156 , U23B20129 and 52207145 , in part by the Natural Science Foundation of Hunan Province under Grant 2025JJ60374 , and in part by the Natural Science Foundation of Changsha City under Grant kq2208279 .

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Research Keywords

  • Active support
  • Adaptive coefficient
  • Fault ride-through
  • Grid-forming

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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