Security Constrained Unit Commitment with Extreme Wind Scenarios Article Swipe
Xin Zhu
,
Zongchao Yu
,
Xuan Liu
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.35833/mpce.2018.000797
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.35833/mpce.2018.000797
The rapid development of economy and society stimulates the increase of power demand. Wind power has received great attention as a typical renewable energy, and the share of wind power is continually increasing in recent years. However, the high integration of wind power brings challenges to the secure and reliable operation of power grid due to the intermittent characteristic of wind power. In order to solve the operation risk caused by wind power uncertainty, this paper proposes to solve the problem of stochastic security-constrained unit commitment (SCUC) by considering the extreme scenarios of wind power output. Firstly, assuming that the probability density distribution of wind power approximately follows a normal distribution, a great number of scenarios are generated by Monte Carlo (MC) simulation method to capture the stochastic nature of wind power output. Then, the clustering by fast search and find of density peaks (CSFDP) is utilized to separate the generated scenarios into three types: extreme, normal and typical scenarios. The extreme scenarios are identified to determine the on/off statuses of generators, while the typical scenarios are used to solve the day-ahead security-constrained economic dispatch (SCED) problem. The advantage of the proposed method is to ensure the robustness of SCUC solution while reducing the conservativeness of the solution as much as possible. The effectiveness of the proposed method is verified by IEEE test systems.
Related Topics
Concepts
Wind power
Power system simulation
Robustness (evolution)
Mathematical optimization
Computer science
Renewable energy
Cluster analysis
Power (physics)
Electric power system
Economic dispatch
Reliability engineering
Monte Carlo method
Engineering
Mathematics
Electrical engineering
Statistics
Biochemistry
Gene
Chemistry
Quantum mechanics
Machine learning
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.35833/mpce.2018.000797
- https://ieeexplore.ieee.org/ielx7/8685265/9097572/09048109.pdf
- OA Status
- diamond
- Cited By
- 51
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3027292208
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3027292208Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.35833/mpce.2018.000797Digital Object Identifier
- Title
-
Security Constrained Unit Commitment with Extreme Wind ScenariosWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Xin Zhu, Zongchao Yu, Xuan LiuList of authors in order
- Landing page
-
https://doi.org/10.35833/mpce.2018.000797Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/8685265/9097572/09048109.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/8685265/9097572/09048109.pdfDirect OA link when available
- Concepts
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Wind power, Power system simulation, Robustness (evolution), Mathematical optimization, Computer science, Renewable energy, Cluster analysis, Power (physics), Electric power system, Economic dispatch, Reliability engineering, Monte Carlo method, Engineering, Mathematics, Electrical engineering, Statistics, Biochemistry, Gene, Chemistry, Quantum mechanics, Machine learning, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
51Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 12, 2024: 6, 2023: 9, 2022: 13, 2021: 8Per-year citation counts (last 5 years)
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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