Decentralized control in active distribution grids via supervised and reinforcement learning Article Swipe
Stavros Karagiannopoulos
,
Petros Aristidou
,
Gabriela Hug
,
Audun Botterud
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.egyai.2024.100342
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.egyai.2024.100342
While moving towards a low-carbon, sustainable electricity system, distribution networks are expected to host a large share of distributed generators, such as photovoltaic units and wind turbines. These inverter-based resources are intermittent, but also controllable, and are expected to amplify the role of distribution networks together with other distributed energy resources, such as storage systems and controllable loads. The available control methods for these resources are typically categorized based on the available communication network into centralized, distributed, and decentralized or local. Standard local schemes are typically inefficient, whereas centralized approaches show implementation and cost concerns. This paper focuses on optimized decentralized control of distributed generators via supervised and reinforcement learning. We present existing state-of-the-art decentralized control schemes based on supervised learning, propose a new reinforcement learning scheme based on deep deterministic policy gradient, and compare the behavior of both decentralized and centralized methods in terms of computational effort, scalability, privacy awareness, ability to consider constraints, and overall optimality. We evaluate the performance of the examined schemes on a benchmark European low voltage test system. The results show that both supervised learning and reinforcement learning schemes effectively mitigate the operational issues faced by the distribution network.
Related Topics
Concepts
Reinforcement learning
Computer science
Scalability
Benchmark (surveying)
Distributed computing
Decentralised system
Distributed generation
Microgrid
Photovoltaic system
Control (management)
Control engineering
Artificial intelligence
Renewable energy
Engineering
Electrical engineering
Database
Geodesy
Geography
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.egyai.2024.100342
- https://ars.els-cdn.com/content/image/1-s2.0-S2666546824000089-ga1_lrg.jpg
- OA Status
- gold
- Cited By
- 4
- References
- 53
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391131723
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391131723Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.egyai.2024.100342Digital Object Identifier
- Title
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Decentralized control in active distribution grids via supervised and reinforcement learningWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-23Full publication date if available
- Authors
-
Stavros Karagiannopoulos, Petros Aristidou, Gabriela Hug, Audun BotterudList of authors in order
- Landing page
-
https://doi.org/10.1016/j.egyai.2024.100342Publisher landing page
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https://ars.els-cdn.com/content/image/1-s2.0-S2666546824000089-ga1_lrg.jpgDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://ars.els-cdn.com/content/image/1-s2.0-S2666546824000089-ga1_lrg.jpgDirect OA link when available
- Concepts
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Reinforcement learning, Computer science, Scalability, Benchmark (surveying), Distributed computing, Decentralised system, Distributed generation, Microgrid, Photovoltaic system, Control (management), Control engineering, Artificial intelligence, Renewable energy, Engineering, Electrical engineering, Database, Geodesy, GeographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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53Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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