IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v235y2024ics0960148124014253.html
   My bibliography  Save this article

Optimization of wind farm power output using wake redirection control

Author

Listed:
  • Balakrishnan, Raj Kiran
  • Son, Eunkuk
  • Hur, Sung-ho

Abstract

The wake effect, which is caused by the upstream turbines in a wind farm, adversely affects the efficiency of downstream turbines, leading to reduced energy generation and increased turbine fatigue loading. To mitigate this effect, a real-time wind farm control technique, i.e., wake redirection control (WRC), employing teaching learning-based optimization (TLBO) is introduced. This technique redirects the wakes away from the downstream turbines in real time, allowing them to generate more power by sacrificing some of the power generated by the upstream turbines. As a result, the total power generated by the wind farm is maximized. A low-fidelity 20-turbine real-life offshore wind farm is modeled and simulated in FLORISSE_M, the MATLAB version of the FLORIS (FLOw Redirection and Induction in Steady-state). The power produced by the wind farm model is maximized in real time by employing TLBO. The optimization results (i.e., the optimized yaw angles) are validated using the corresponding high-fidelity wind farm model developed in SOWFA (Simulator fOr Wind Farm Applications). Various results are presented to demonstrate that the TLBO-based WRC positively affects the power generated by the wind farm.

Suggested Citation

  • Balakrishnan, Raj Kiran & Son, Eunkuk & Hur, Sung-ho, 2024. "Optimization of wind farm power output using wake redirection control," Renewable Energy, Elsevier, vol. 235(C).
    • Handle: RePEc:eee:renene:v:235:y:2024:i:c:s0960148124014253
    DOI: 10.1016/j.renene.2024.121357
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124014253
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.121357?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Doekemeijer, Bart M. & van der Hoek, Daan & van Wingerden, Jan-Willem, 2020. "Closed-loop model-based wind farm control using FLORIS under time-varying inflow conditions," Renewable Energy, Elsevier, vol. 156(C), pages 719-730.
    2. Cai, Wei & Hu, Yang & Fang, Fang & Yao, Lujin & Liu, Jizhen, 2023. "Wind farm power production and fatigue load optimization based on dynamic partitioning and wake redirection of wind turbines," Applied Energy, Elsevier, vol. 339(C).
    3. Zhiwen Deng & Chang Xu & Zhihong Huo & Xingxing Han & Feifei Xue, 2023. "Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model," Energies, MDPI, vol. 16(9), pages 1-20, May.
    4. He, Ruiyang & Yang, Hongxing & Lu, Lin, 2023. "Optimal yaw strategy and fatigue analysis of wind turbines under the combined effects of wake and yaw control," Applied Energy, Elsevier, vol. 337(C).
    5. Stoyan Kanev, 2019. "On the Robustness of Active Wake Control to Wind Turbine Downtime," Energies, MDPI, vol. 12(16), pages 1-13, August.
    6. Gu, Bo & Meng, Hang & Ge, Mingwei & Zhang, Hongtao & Liu, Xinyu, 2021. "Cooperative multiagent optimization method for wind farm power delivery maximization," Energy, Elsevier, vol. 233(C).
    7. He, Ruiyang & Yang, Hongxing & Lu, Lin & Gao, Xiaoxia, 2024. "Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms," Renewable Energy, Elsevier, vol. 225(C).
    8. Gonzalez Silva, Jean & Ferrari, Riccardo & van Wingerden, Jan-Willem, 2023. "Wind farm control for wake-loss compensation, thrust balancing and load-limiting of turbines," Renewable Energy, Elsevier, vol. 203(C), pages 421-433.
    9. Fleming, Paul A. & Gebraad, Pieter M.O. & Lee, Sang & van Wingerden, Jan-Willem & Johnson, Kathryn & Churchfield, Matt & Michalakes, John & Spalart, Philippe & Moriarty, Patrick, 2014. "Evaluating techniques for redirecting turbine wakes using SOWFA," Renewable Energy, Elsevier, vol. 70(C), pages 211-218.
    10. Michael F. Howland & Jesús Bas Quesada & Juan José Pena Martínez & Felipe Palou Larrañaga & Neeraj Yadav & Jasvipul S. Chawla & Varun Sivaram & John O. Dabiri, 2022. "Collective wind farm operation based on a predictive model increases utility-scale energy production," Nature Energy, Nature, vol. 7(9), pages 818-827, September.
    11. Qian, Guo-Wei & Ishihara, Takeshi, 2021. "Wind farm power maximization through wake steering with a new multiple wake model for prediction of turbulence intensity," Energy, Elsevier, vol. 220(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tu, Yu & Chen, Yaoran & Zhang, Kai & He, Ruiyang & Han, Zhaolong & Zhou, Dai, 2025. "A multi-fidelity framework for power prediction of wind farm under yaw misalignment," Applied Energy, Elsevier, vol. 377(PC).
    2. Zhiwen Deng & Chang Xu & Zhihong Huo & Xingxing Han & Feifei Xue, 2023. "Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model," Energies, MDPI, vol. 16(9), pages 1-20, May.
    3. Tong Shu & Young Hoon Joo, 2023. "Non-Centralised Balance Dispatch Strategy in Waked Wind Farms through a Graph Sparsification Partitioning Approach," Energies, MDPI, vol. 16(20), pages 1-21, October.
    4. He, Ruiyang & Yang, Hongxing & Lu, Lin & Gao, Xiaoxia, 2024. "Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms," Renewable Energy, Elsevier, vol. 225(C).
    5. Wang, Wenwen & Kong, Xiaobing & Li, Gangqiang & Liu, Xiangjie & Ma, Lele & Liu, Wenting & Lee, Kwang Y., 2024. "Wind farm control using distributed economic MPC scheme under the influence of wake effect," Energy, Elsevier, vol. 309(C).
    6. Adam Zagubień & Katarzyna Wolniewicz & Jakub Szwochertowski, 2024. "Analysis of Wind Farm Productivity Taking Wake Loss into Account: Case Study," Energies, MDPI, vol. 17(23), pages 1-14, November.
    7. Rivera-Arreba, Irene & Li, Zhaobin & Yang, Xiaolei & Bachynski-Polić, Erin E., 2024. "Comparison of the dynamic wake meandering model against large eddy simulation for horizontal and vertical steering of wind turbine wakes," Renewable Energy, Elsevier, vol. 221(C).
    8. Huanqiang, Zhang & Xiaoxia, Gao & Hongkun, Lu & Qiansheng, Zhao & Xiaoxun, Zhu & Yu, Wang & Fei, Zhao, 2024. "Investigation of a new 3D wake model of offshore floating wind turbines subjected to the coupling effects of wind and wave," Applied Energy, Elsevier, vol. 365(C).
    9. Huang, Zishuo & Wu, Wenchuan, 2024. "An efficient solution for large offshore wind farm power optimization with the Porté-Agel wake model: Optimality and efficiency," Energy, Elsevier, vol. 306(C).
    10. Fathy, Ahmed & Rezk, Hegazy & Yousri, Dalia & Kandil, Tarek & Abo-Khalil, Ahmed G., 2022. "Real-time bald eagle search approach for tracking the maximum generated power of wind energy conversion system," Energy, Elsevier, vol. 249(C).
    11. Wang, Pengda & Xiao, Jinxin & Huang, Sheng & Wu, Qiuwei & Zhang, Menglin & Wu, Xuan & Shen, Feifan & Ma, Kuichao, 2025. "An accelerated asynchronous distributed control for DFIG wind turbines and collection system loss minimization in waked wind farm," Applied Energy, Elsevier, vol. 377(PD).
    12. Sun, Jili & Chen, Zheng & Yu, Hao & Gao, Shan & Wang, Bin & Ying, You & Sun, Yong & Qian, Peng & Zhang, Dahai & Si, Yulin, 2022. "Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines," Renewable Energy, Elsevier, vol. 199(C), pages 71-86.
    13. Maarten T. van Beek & Axelle Viré & Søren J. Andersen, 2021. "Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm," Energies, MDPI, vol. 14(5), pages 1-21, February.
    14. Kuichao Ma & Huanqiang Zhang & Xiaoxia Gao & Xiaodong Wang & Heng Nian & Wei Fan, 2024. "Research on Evaluation Method of Wind Farm Wake Energy Efficiency Loss Based on SCADA Data Analysis," Sustainability, MDPI, vol. 16(5), pages 1-16, February.
    15. Tian, Runze & Kou, Peng & Zhang, Yuanhang & Mei, Mingyang & Zhang, Zhihao & Liang, Deliang, 2024. "Residual-connected physics-informed neural network for anti-noise wind field reconstruction," Applied Energy, Elsevier, vol. 357(C).
    16. Tanvir Ahmad & Abdul Basit & Muneeb Ahsan & Olivier Coupiac & Nicolas Girard & Behzad Kazemtabrizi & Peter C. Matthews, 2019. "Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms," Energies, MDPI, vol. 12(7), pages 1-15, April.
    17. Ma, Hongliang & Ge, Mingwei & Wu, Guangxing & Du, Bowen & Liu, Yongqian, 2021. "Formulas of the optimized yaw angles for cooperative control of wind farms with aligned turbines to maximize the power production," Applied Energy, Elsevier, vol. 303(C).
    18. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
    19. Rubel C. Das & Yu-Lin Shen, 2023. "Analysis of Wind Farms under Different Yaw Angles and Wind Speeds," Energies, MDPI, vol. 16(13), pages 1-19, June.
    20. Liu, Yige & Zhao, Zhenzhou & Liu, Yan & Liu, Huiwen & Wei, Shangshang & Ma, Yuanzhuo & Ling, Ziyan & Luo, Qiao, 2024. "Combined wake control of aligned wind turbines for power optimization based on a 3D wake model considering secondary wake steering," Energy, Elsevier, vol. 308(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:235:y:2024:i:c:s0960148124014253. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.