Rank-Based Predictive Control for Community Microgrids With Dynamic Topology and Multiple Points of Common Coupling Article Swipe
Brevann Nun
,
Muhammad F. Umar
,
Anas Karaki
,
Mohammad B. Shadmand
,
Sertaç Bayhan
,
Haitham Abu‐Rub
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/jestie.2021.3110746
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/jestie.2021.3110746
This article presents a rank-based model predictive control (MPC) scheme for voltage source converters (VSCs) operating in a low voltage, AC community microgrid with dynamically changing topology.The advent of mesh distribution networks with high renewable energy penetration in recent literature prompts the development of an adaptive VSC control technique for optimal performance in a changing environment.Several distributed control strategies have focused on communication less plug-and-play implementation, but the proposed ranking scheme focuses on resilient operation while minimizing physical communication requirements.The proposed framework provides intelligence to enable a fully synchronized microgrid with the ability to connect multiple VSCs to a utility grid simultaneously through multiple points of common coupling (MPCC) and disconnect from grid-forming distributed sources when islanded, attaining a higher margin of stability, robustness, and flexibility.The MPC framework features an adaptive ranking system that assigns operational modes to the VSCs, i.e., voltage control (grid-forming) or current control (grid-following), and defines leader-follower directionality for synchronization.Communication among VSCs is achieved using a topology-mirroring interaction layer.Several RTS case studies are provided to demonstrate the functionality and performance of the proposed intelligent rank-based MPC in a changing microgrid configuration with 10 VSCs.
Related Topics
Concepts
Microgrid
Model predictive control
Computer science
Grid
Robustness (evolution)
Distributed computing
Voltage source
Topology (electrical circuits)
Network topology
Control theory (sociology)
Control engineering
Voltage
Engineering
Control (management)
Computer network
Artificial intelligence
Electrical engineering
Gene
Mathematics
Chemistry
Biochemistry
Geometry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/jestie.2021.3110746
- https://ieeexplore.ieee.org/ielx7/8847244/9662449/09531537.pdf
- OA Status
- hybrid
- Cited By
- 14
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3197926402
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3197926402Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/jestie.2021.3110746Digital Object Identifier
- Title
-
Rank-Based Predictive Control for Community Microgrids With Dynamic Topology and Multiple Points of Common CouplingWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-09-08Full publication date if available
- Authors
-
Brevann Nun, Muhammad F. Umar, Anas Karaki, Mohammad B. Shadmand, Sertaç Bayhan, Haitham Abu‐RubList of authors in order
- Landing page
-
https://doi.org/10.1109/jestie.2021.3110746Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/8847244/9662449/09531537.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/8847244/9662449/09531537.pdfDirect OA link when available
- Concepts
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Microgrid, Model predictive control, Computer science, Grid, Robustness (evolution), Distributed computing, Voltage source, Topology (electrical circuits), Network topology, Control theory (sociology), Control engineering, Voltage, Engineering, Control (management), Computer network, Artificial intelligence, Electrical engineering, Gene, Mathematics, Chemistry, Biochemistry, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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14Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 5, 2022: 2, 2021: 5Per-year citation counts (last 5 years)
- References (count)
-
23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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