Wake-based wind turbine optimisations under yawed conditions

Jiufa Cao; Xiang Gao; Xiang Shen; Haoyuan Sun; Yi Ju

doi:10.1109/EFEA56675.2022.10063800

Wake-based wind turbine optimisations under yawed conditions

Jiufa Cao, Xiang Gao, Xiang Shen, Haoyuan Sun, Yi Ju

Mechanical and Construction Engineering Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

34 Downloads (Pure)

Abstract

The yawed wind turbines in the upstream can be used to reduce wake losses for the downstream wind turbines. Accurate prediction for the wake aerodynamics performance under yawed operation condition is of significant importance for such a controlling strategy. In the present paper, an improved engineering wake model considering yawed conditions is implemented to simulate the wakes behind yawed wind turbines. Firstly, an improved engineering yaw model is utilized to simulate the wakes under yawed conditions. The improved wake model is based on the unsteady Blade Element Momentum (BEM) method with the induction factor and thrust coefficient as key parameters. Secondly, based on genetic algorithm optimization method, the yawed angles control optimization platform is built with wake model of wind turbine. Finally, the loads and aerodynamic performance are analyzed under optimal yawed angles of multi-wind turbine. The results showed that the improved engineering yawed model and yaw control strategy can be accurately and efficiently utilized in enhancing the wake velocity and aerodynamic performance of the yawed wind turbine.

Original language	English
Title of host publication	2022 7th International Conference on Environment Friendly Energies and Applications (EFEA)
Subtitle of host publication	Renewable and Sustainable Energy Systems, Hybrid Transportation Systems, Energy Transition, and Energy Security
Place of Publication	Piscataway, US
Publisher	IEEE
Pages	1-5
Number of pages	5
Edition	7th
ISBN (Electronic)	9798350333213
ISBN (Print)	9798350333220
DOIs	https://doi.org/10.1109/EFEA56675.2022.10063800
Publication status	Published - 22 Dec 2022
Event	2022 7th International Conference on Environment Friendly Energies and Applications, EFEA - Hotel Voila, Bagatelle, Mauritius Duration: 14 Dec 2022 → 16 Dec 2022 https://efeaconf.com/EFEA2022/index.html

Publication series

Name	Environment Friendly Energies and Applications (EFEA)
Publisher	IEEE Xplore
Number	7
ISSN (Print)	2641-5925
ISSN (Electronic)	2688-2558

Conference

Conference	2022 7th International Conference on Environment Friendly Energies and Applications, EFEA
Country/Territory	Mauritius
City	Bagatelle
Period	14/12/22 → 16/12/22
Internet address	https://efeaconf.com/EFEA2022/index.html

Keywords

Wind turbine
Wake model
Yawed operation condition
Optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/EFEA56675.2022.10063800

Cite this

Cao, J., Gao, X., Shen, X., Sun, H., & Ju, Y. (2022). Wake-based wind turbine optimisations under yawed conditions. In 2022 7th International Conference on Environment Friendly Energies and Applications (EFEA): Renewable and Sustainable Energy Systems, Hybrid Transportation Systems, Energy Transition, and Energy Security (7th ed., pp. 1-5). (Environment Friendly Energies and Applications (EFEA); No. 7). IEEE. https://doi.org/10.1109/EFEA56675.2022.10063800

Cao, Jiufa ; Gao, Xiang ; Shen, Xiang et al. / Wake-based wind turbine optimisations under yawed conditions. 2022 7th International Conference on Environment Friendly Energies and Applications (EFEA): Renewable and Sustainable Energy Systems, Hybrid Transportation Systems, Energy Transition, and Energy Security. 7th. ed. Piscataway, US : IEEE, 2022. pp. 1-5 (Environment Friendly Energies and Applications (EFEA); 7).

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title = "Wake-based wind turbine optimisations under yawed conditions",

abstract = "The yawed wind turbines in the upstream can be used to reduce wake losses for the downstream wind turbines. Accurate prediction for the wake aerodynamics performance under yawed operation condition is of significant importance for such a controlling strategy. In the present paper, an improved engineering wake model considering yawed conditions is implemented to simulate the wakes behind yawed wind turbines. Firstly, an improved engineering yaw model is utilized to simulate the wakes under yawed conditions. The improved wake model is based on the unsteady Blade Element Momentum (BEM) method with the induction factor and thrust coefficient as key parameters. Secondly, based on genetic algorithm optimization method, the yawed angles control optimization platform is built with wake model of wind turbine. Finally, the loads and aerodynamic performance are analyzed under optimal yawed angles of multi-wind turbine. The results showed that the improved engineering yawed model and yaw control strategy can be accurately and efficiently utilized in enhancing the wake velocity and aerodynamic performance of the yawed wind turbine.",

keywords = "Wind turbine, Wake model, Yawed operation condition, Optimization",

author = "Jiufa Cao and Xiang Gao and Xiang Shen and Haoyuan Sun and Yi Ju",

note = "Funding Information: The authors wish to express acknowledgement to the National, Natural Science Foundation of China under grant number 51906210, The research was supported by the Royal Society International Exchanges 2019 Cost Share Programme (Grant No. IEC\NSFC\191409) and the Northern Accelerator CCF Feasibility Project (Grant No. NACCF228), the Jiangsu Province Natural Science Foundation under grant number BK20160476.; 2022 7th International Conference on Environment Friendly Energies and Applications, EFEA ; Conference date: 14-12-2022 Through 16-12-2022",

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Cao, J, Gao, X, Shen, X, Sun, H & Ju, Y 2022, Wake-based wind turbine optimisations under yawed conditions. in 2022 7th International Conference on Environment Friendly Energies and Applications (EFEA): Renewable and Sustainable Energy Systems, Hybrid Transportation Systems, Energy Transition, and Energy Security. 7th edn, Environment Friendly Energies and Applications (EFEA), no. 7, IEEE, Piscataway, US, pp. 1-5, 2022 7th International Conference on Environment Friendly Energies and Applications, EFEA, Bagatelle, Mauritius, 14/12/22. https://doi.org/10.1109/EFEA56675.2022.10063800

Wake-based wind turbine optimisations under yawed conditions. / Cao, Jiufa; Gao, Xiang; Shen, Xiang et al.
2022 7th International Conference on Environment Friendly Energies and Applications (EFEA): Renewable and Sustainable Energy Systems, Hybrid Transportation Systems, Energy Transition, and Energy Security. 7th. ed. Piscataway, US: IEEE, 2022. p. 1-5 (Environment Friendly Energies and Applications (EFEA); No. 7).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Wake-based wind turbine optimisations under yawed conditions

AU - Cao, Jiufa

AU - Gao, Xiang

AU - Shen, Xiang

AU - Sun, Haoyuan

AU - Ju, Yi

N1 - Funding Information: The authors wish to express acknowledgement to the National, Natural Science Foundation of China under grant number 51906210, The research was supported by the Royal Society International Exchanges 2019 Cost Share Programme (Grant No. IEC\NSFC\191409) and the Northern Accelerator CCF Feasibility Project (Grant No. NACCF228), the Jiangsu Province Natural Science Foundation under grant number BK20160476.

PY - 2022/12/22

Y1 - 2022/12/22

N2 - The yawed wind turbines in the upstream can be used to reduce wake losses for the downstream wind turbines. Accurate prediction for the wake aerodynamics performance under yawed operation condition is of significant importance for such a controlling strategy. In the present paper, an improved engineering wake model considering yawed conditions is implemented to simulate the wakes behind yawed wind turbines. Firstly, an improved engineering yaw model is utilized to simulate the wakes under yawed conditions. The improved wake model is based on the unsteady Blade Element Momentum (BEM) method with the induction factor and thrust coefficient as key parameters. Secondly, based on genetic algorithm optimization method, the yawed angles control optimization platform is built with wake model of wind turbine. Finally, the loads and aerodynamic performance are analyzed under optimal yawed angles of multi-wind turbine. The results showed that the improved engineering yawed model and yaw control strategy can be accurately and efficiently utilized in enhancing the wake velocity and aerodynamic performance of the yawed wind turbine.

AB - The yawed wind turbines in the upstream can be used to reduce wake losses for the downstream wind turbines. Accurate prediction for the wake aerodynamics performance under yawed operation condition is of significant importance for such a controlling strategy. In the present paper, an improved engineering wake model considering yawed conditions is implemented to simulate the wakes behind yawed wind turbines. Firstly, an improved engineering yaw model is utilized to simulate the wakes under yawed conditions. The improved wake model is based on the unsteady Blade Element Momentum (BEM) method with the induction factor and thrust coefficient as key parameters. Secondly, based on genetic algorithm optimization method, the yawed angles control optimization platform is built with wake model of wind turbine. Finally, the loads and aerodynamic performance are analyzed under optimal yawed angles of multi-wind turbine. The results showed that the improved engineering yawed model and yaw control strategy can be accurately and efficiently utilized in enhancing the wake velocity and aerodynamic performance of the yawed wind turbine.

KW - Wind turbine

KW - Wake model

KW - Yawed operation condition

KW - Optimization

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U2 - 10.1109/EFEA56675.2022.10063800

DO - 10.1109/EFEA56675.2022.10063800

M3 - Conference contribution

AN - SCOPUS:85151255555

SN - 9798350333220

T3 - Environment Friendly Energies and Applications (EFEA)

SP - 1

EP - 5

BT - 2022 7th International Conference on Environment Friendly Energies and Applications (EFEA)

PB - IEEE

CY - Piscataway, US

T2 - 2022 7th International Conference on Environment Friendly Energies and Applications, EFEA

Y2 - 14 December 2022 through 16 December 2022

ER -

Cao J, Gao X, Shen X, Sun H, Ju Y. Wake-based wind turbine optimisations under yawed conditions. In 2022 7th International Conference on Environment Friendly Energies and Applications (EFEA): Renewable and Sustainable Energy Systems, Hybrid Transportation Systems, Energy Transition, and Energy Security. 7th ed. Piscataway, US: IEEE. 2022. p. 1-5. (Environment Friendly Energies and Applications (EFEA); 7). doi: 10.1109/EFEA56675.2022.10063800

Wake-based wind turbine optimisations under yawed conditions

Abstract

Publication series

Conference

Keywords

UN SDGs

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