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Article: Wind farm cooperative control under unsteady inflow conditions considering dynamic wake interactions

TitleWind farm cooperative control under unsteady inflow conditions considering dynamic wake interactions
Authors
KeywordsDYCORS algorithm
Dynamic wind farm control framework
Hurst exponent
Revised FLORIDyn model
Speed and direction variability
Yaw update interval
Issue Date1-May-2025
PublisherElsevier
Citation
Renewable Energy, 2025, v. 244 How to Cite?
Abstract

Overlooking wake dynamics undermines the real-time control performance of wind farms. This paper proposes a novel dynamic wind farm control framework that integrates a mid-fidelity dynamic wake model, the FLORIDyn model, with surrogate model optimization, the DYCORS algorithm, to achieve optimal coordinated control settings within the yaw update interval accurately and efficiently. The framework is tested in a 6-turbine wind farm exposed to time-varying inflow conditions over 2400 s, with the conventional steady framework as the comparison. Additionally, parametric studies on yaw update interval and wind variability are conducted to explore the applicability of the dynamic framework under different inflow and operation conditions. Results indicate that achieving the anticipated power output of the steady wind farm control framework is challenging in a realistic wind farm setting. The proposed dynamic wind farm control framework enhances the power benefits of wake redirection compared to the steady framework, achieving a 2.22 % increase in power gains. The dynamic optimal control is more sensitive to yaw update interval variations than the greedy control. A smaller Hurst exponent, indicating increased stationarity of the inflow condition, reduces the power disparities between steady and dynamic control optimizations. Directional variability imposes a more distinct impact on control benefits than speed variability.


Persistent Identifierhttp://hdl.handle.net/10722/359654
ISSN
2023 Impact Factor: 9.0
2023 SCImago Journal Rankings: 1.923

 

DC FieldValueLanguage
dc.contributor.authorYang, Shanghui-
dc.contributor.authorDeng, Xiaowei-
dc.contributor.authorDai, Feng-
dc.contributor.authorYang, Kun-
dc.contributor.authorWang, Qiulei-
dc.contributor.authorDong, Zhikun-
dc.date.accessioned2025-09-10T00:30:34Z-
dc.date.available2025-09-10T00:30:34Z-
dc.date.issued2025-05-01-
dc.identifier.citationRenewable Energy, 2025, v. 244-
dc.identifier.issn0960-1481-
dc.identifier.urihttp://hdl.handle.net/10722/359654-
dc.description.abstract<p>Overlooking wake dynamics undermines the real-time control performance of wind farms. This paper proposes a novel dynamic wind farm control framework that integrates a mid-fidelity dynamic wake model, the FLORIDyn model, with surrogate model optimization, the DYCORS algorithm, to achieve optimal coordinated control settings within the yaw update interval accurately and efficiently. The framework is tested in a 6-turbine wind farm exposed to time-varying inflow conditions over 2400 s, with the conventional steady framework as the comparison. Additionally, parametric studies on yaw update interval and wind variability are conducted to explore the applicability of the dynamic framework under different inflow and operation conditions. Results indicate that achieving the anticipated power output of the steady wind farm control framework is challenging in a realistic wind farm setting. The proposed dynamic wind farm control framework enhances the power benefits of wake redirection compared to the steady framework, achieving a 2.22 % increase in power gains. The dynamic optimal control is more sensitive to yaw update interval variations than the greedy control. A smaller Hurst exponent, indicating increased stationarity of the inflow condition, reduces the power disparities between steady and dynamic control optimizations. Directional variability imposes a more distinct impact on control benefits than speed variability.</p>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofRenewable Energy-
dc.subjectDYCORS algorithm-
dc.subjectDynamic wind farm control framework-
dc.subjectHurst exponent-
dc.subjectRevised FLORIDyn model-
dc.subjectSpeed and direction variability-
dc.subjectYaw update interval-
dc.titleWind farm cooperative control under unsteady inflow conditions considering dynamic wake interactions -
dc.typeArticle-
dc.identifier.doi10.1016/j.renene.2025.122654-
dc.identifier.scopuseid_2-s2.0-85217768064-
dc.identifier.volume244-
dc.identifier.eissn1879-0682-
dc.identifier.issnl0960-1481-

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