Fault Ride-Through Techniques for Permanent Magnet Synchronous Generator Wind Turbines (PMSG-WTGs): A Systematic Literature Review

Ernest F. Morgan, Omar Abdel-Rahim, Tamer F. Megahed, Junya Suehiro, Sobhy M. Abdelkader

Research output: Contribution to journalReview articlepeer-review

Abstract

Global warming and rising energy demands have increased renewable energy (RE) usage globally. Wind energy has become the most technologically advanced renewable energy source. Wind turbines (WTs) must ride through faults to ensure power system stability. On the flip side, permanent magnet synchronous generators (PMSG)-based wind turbine power plants (WTPPs) are susceptible to grid voltage fluctuations and require extra regulations to maintain regular operations. Due to recent changes in grid code standards, it has become vital to explore alternate fault ride-through (FRT) methods to ensure their capabilities. This research will ensure that FRT solutions available via the Web of Science (WoS) database are vetted and compared in hardware retrofitting, internal software control changes, and hybrid techniques. In addition, a bibliometric analysis is provided, which reveals an ever-increasing volume of works dedicated to the topic. After that, a literature study of FRT techniques for PMSG WTs is carried out, demonstrating the evolution of these techniques over time. This paper concludes that additional research is required to enhance FRT capabilities in PMSG wind turbines and that further attention to topics, such as machine learning tools and the combination of FRT and wind power smoothing approaches, should arise in the following years.

Original languageEnglish
Article number9116
JournalEnergies
Volume15
Issue number23
DOIs
Publication statusPublished - Dec 2022

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Building and Construction
  • Fuel Technology
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

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