Microgrid Operations Planning Based on Improving the Flying Sparrow Search Algorithm Article Swipe
Trong-The Nguyen
,
Truong-Giang Ngo
,
Thi-Kien Dao
,
Thi-Thanh-Tan Nguyen
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/sym14010168
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/sym14010168
Microgrid operations planning is crucial for emerging energy microgrids to enhance the share of clean energy power generation and ensure a safe symmetry power grid among distributed natural power sources and stable functioning of the entire power system. This paper suggests a new improved version (namely, ESSA) of the sparrow search algorithm (SSA) based on an elite reverse learning strategy and firefly algorithm (FA) mutation strategy for the power microgrid optimal operations planning. Scheduling cycles of the microgrid with a distributed power source’s optimal output and total operation cost is modeled based on variables, e.g., environmental costs, electricity interaction, investment depreciation, and maintenance system, to establish grid multi-objective economic optimization. Compared with other literature methods, such as Genetic algorithm (GA), Particle swarm optimization (PSO), Firefly algorithm (FA), Bat algorithm (BA), Grey wolf optimization (GWO), and SSA show that the proposed plan offers higher performance and feasibility in solving microgrid operations planning issues.
Related Topics
Concepts
Microgrid
Firefly algorithm
Particle swarm optimization
Mathematical optimization
Computer science
Genetic algorithm
Grid
Scheduling (production processes)
Distributed generation
Crossover
Renewable energy
Algorithm
Engineering
Mathematics
Control (management)
Artificial intelligence
Geometry
Electrical engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/sym14010168
- https://www.mdpi.com/2073-8994/14/1/168/pdf?version=1642467095
- OA Status
- gold
- Cited By
- 53
- References
- 29
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4205970187
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4205970187Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/sym14010168Digital Object Identifier
- Title
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Microgrid Operations Planning Based on Improving the Flying Sparrow Search AlgorithmWork title
- Type
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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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2022-01-15Full publication date if available
- Authors
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Trong-The Nguyen, Truong-Giang Ngo, Thi-Kien Dao, Thi-Thanh-Tan NguyenList of authors in order
- Landing page
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https://doi.org/10.3390/sym14010168Publisher landing page
- PDF URL
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https://www.mdpi.com/2073-8994/14/1/168/pdf?version=1642467095Direct link to full text PDF
- Open access
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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://www.mdpi.com/2073-8994/14/1/168/pdf?version=1642467095Direct OA link when available
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Microgrid, Firefly algorithm, Particle swarm optimization, Mathematical optimization, Computer science, Genetic algorithm, Grid, Scheduling (production processes), Distributed generation, Crossover, Renewable energy, Algorithm, Engineering, Mathematics, Control (management), Artificial intelligence, Geometry, Electrical engineeringTop concepts (fields/topics) attached by OpenAlex
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53Total citation count in OpenAlex
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2025: 7, 2024: 13, 2023: 16, 2022: 17Per-year citation counts (last 5 years)
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29Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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