High-Speed Voltage Control in Active Distribution Systems with Smart Inverter Coordination and Deep Reinforcement Learning Article Swipe
Mohammad Golgol
,
Anamitra Pal
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2311.13080
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2311.13080
The increasing penetration of renewable energy resources in distribution systems necessitates high-speed monitoring and control of voltage for ensuring reliable system operation. However, existing voltage control algorithms often make simplifying assumptions in their formulation, such as real-time availability of smart meter measurements (for monitoring), or real-time knowledge of every power injection information(for control).This paper leverages the recent advances made in highspeed state estimation for real-time unobservable distribution systems to formulate a deep reinforcement learning-based control algorithm that utilizes the state estimates alone to control the voltage of the entire system. The results obtained for a modified (renewable-rich) IEEE34-nodedistributionfeeder indicate that the proposed approach excels in monitoring and controlling voltage of active distribution systems.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2311.13080
- https://arxiv.org/pdf/2311.13080
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388964594
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4388964594Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2311.13080Digital Object Identifier
- Title
-
High-Speed Voltage Control in Active Distribution Systems with Smart Inverter Coordination and Deep Reinforcement LearningWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-11-22Full publication date if available
- Authors
-
Mohammad Golgol, Anamitra PalList of authors in order
- Landing page
-
https://arxiv.org/abs/2311.13080Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2311.13080Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2311.13080Direct OA link when available
- Concepts
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Unobservable, Reinforcement learning, Voltage, Renewable energy, Computer science, Control engineering, Control (management), Smart meter, Engineering, Control theory (sociology), Smart grid, Electrical engineering, Artificial intelligence, Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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