Accelerated hierarchical optimization method for emergency energy management of microgrids with energy storage systems Article Swipe
Weihao Zhou
,
Qiang Li
,
Kunming Wu
,
Leiqi Zhang
,
Muhammad Arshad Shehzad Hassan
,
Minyou Chen
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1002/ese3.1077
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1002/ese3.1077
When failures occur in microgrids (MGs), the energy management for emergencies is required. To respond to emergencies in MGs rapidly, an accelerated hierarchical optimization method has been proposed, where the outputs of energy storage systems (ESSs) are controlled to provide urgent supports, before the MG reconfiguration starts. However, it is time‐consuming to find the optimal schemes for MG reconfiguration. To reduce the time of reconfiguration, an optimization method based on deep neural networks (DNNs) for MG reconfiguration is presented, which consists of three levels. First, the combinational optimization for load shedding amounts is solved to determine the loads that have to be cut off. Second, a DNN is used to find the parameters of reconfiguration instead of the time‐consuming calculation of power flow, which is a good way to reduce time of reconfiguration. Third, according to these parameters, the optimal scheme for reconfiguration is selected by a comprehensive evaluation method, where the Delphi method (DM) is employed to adjust the weights of preferences in a comprehensive evaluation function, so it offers the diversity of decisions for the MG reconfiguration. Finally, to test our method, a modified IEEE 33‐bus system is built in MATLAB for simulations. Compared to traditional methods, our method can obtain the same reconfiguration scheme under different on/off states of load switches, but the time of reconfiguration is only one‐sixty‐seventh of that of other methods. Furthermore, in terms of our comprehensive evaluation method, reconfiguration schemes can be selected under different preferences.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/ese3.1077
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ese3.1077
- OA Status
- gold
- Cited By
- 8
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4210725444
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4210725444Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/ese3.1077Digital Object Identifier
- Title
-
Accelerated hierarchical optimization method for emergency energy management of microgrids with energy storage systemsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-01-28Full publication date if available
- Authors
-
Weihao Zhou, Qiang Li, Kunming Wu, Leiqi Zhang, Muhammad Arshad Shehzad Hassan, Minyou ChenList of authors in order
- Landing page
-
https://doi.org/10.1002/ese3.1077Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ese3.1077Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ese3.1077Direct OA link when available
- Concepts
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Control reconfiguration, Computer science, Power (physics), Scheme (mathematics), Reliability engineering, Energy storage, Energy (signal processing), MATLAB, Mathematical optimization, Embedded system, Engineering, Mathematics, Operating system, Statistics, Physics, Mathematical analysis, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 3, 2023: 4Per-year citation counts (last 5 years)
- References (count)
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32Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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