A model predictive control strategy for enhancing fault ride through in PMSG wind turbines using SMES and improved GSC control Article Swipe
Sobhy M. Abdelkader
,
Ernest F. Morgan
,
Tamer F. Megahed
,
Wesam Rohouma
,
Omar Abdel‐Rahim
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fenrg.2023.1277954
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fenrg.2023.1277954
Wind energy has emerged as a prominent player in the realm of renewable energy sources, both in terms of capacity and technological adaptability. Among the various renewable energy technologies, wind turbine generators stand out as the most widely employed. Recently, gearless permanent magnet synchronous generators have gained traction in the wind energy sector due to their appealing features, such as reduced maintenance costs and the elimination of gearboxes. Nevertheless, challenges remain, particularly concerning the grid-friendly integration of wind turbines, specifically with regard to high voltage ride-through (HVRT) and low voltage ride-through (LVRT) improvements. These challenges pose a threat to grid stability, impede Wind Turbine Generator performance, and may lead to significant damage to wind turbines. To address these concerns, this research proposes an integrated strategy that combines a model predictive control (MPC) superconducting magnetic energy storage (SMES) device with a modified WTG grid-side converter control. By coupling SMES devices to the dc-link of Permanent Magnet Synchronous Generator WTGs, the proposed approach aims to achieve an overvoltage suppression effect during grid disturbances and provide support for grid reactive power. Through various test scenarios, the feasibility and practicality of this suggested technique are demonstrated.
Related Topics
Concepts
Low voltage ride through
Wind power
Permanent magnet synchronous generator
Renewable energy
Turbine
Automotive engineering
Model predictive control
Grid
Fault (geology)
Overvoltage
Computer science
Engineering
AC power
Control engineering
Voltage
Electrical engineering
Control (management)
Mechanical engineering
Geology
Mathematics
Seismology
Geometry
Artificial intelligence
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fenrg.2023.1277954
- https://www.frontiersin.org/articles/10.3389/fenrg.2023.1277954/pdf?isPublishedV2=False
- OA Status
- gold
- Cited By
- 11
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388266916
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388266916Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fenrg.2023.1277954Digital Object Identifier
- Title
-
A model predictive control strategy for enhancing fault ride through in PMSG wind turbines using SMES and improved GSC controlWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-10-25Full publication date if available
- Authors
-
Sobhy M. Abdelkader, Ernest F. Morgan, Tamer F. Megahed, Wesam Rohouma, Omar Abdel‐RahimList of authors in order
- Landing page
-
https://doi.org/10.3389/fenrg.2023.1277954Publisher landing page
- PDF URL
-
https://www.frontiersin.org/articles/10.3389/fenrg.2023.1277954/pdf?isPublishedV2=FalseDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.frontiersin.org/articles/10.3389/fenrg.2023.1277954/pdf?isPublishedV2=FalseDirect OA link when available
- Concepts
-
Low voltage ride through, Wind power, Permanent magnet synchronous generator, Renewable energy, Turbine, Automotive engineering, Model predictive control, Grid, Fault (geology), Overvoltage, Computer science, Engineering, AC power, Control engineering, Voltage, Electrical engineering, Control (management), Mechanical engineering, Geology, Mathematics, Seismology, Geometry, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
11Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 6, 2024: 4, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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