IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v377y2025ipds0306261924019950.html
   My bibliography  Save this article

An accelerated asynchronous distributed control for DFIG wind turbines and collection system loss minimization in waked wind farm

Author

Listed:
  • Wang, Pengda
  • Xiao, Jinxin
  • Huang, Sheng
  • Wu, Qiuwei
  • Zhang, Menglin
  • Wu, Xuan
  • Shen, Feifan
  • Ma, Kuichao

Abstract

A loss minimization method achieved by voltage control strategy for doubly-fed induction generator wind turbine generators and collection system in waked wind farm with an accelerated asynchronous distributed calculation scheme is proposed in this paper. With the model predictive control-based voltage control strategy used, the active power of generators and reactive power of rotor-side and grid-side converters can be coordinated, and thus the loss of wind turbines and collection system is minimized, which can improve the power generation of wind farm and service lifetime of wind turbines. In addition, a modified time-varying dynamic wake model is established to improve the accuracy of wake wind speed calculation. Further, the wake propagation process described by time delay is taken into consideration. Meanwhile, a correction method related to turbulence intensity is used to modify downstream wind speed. An asynchronous distributed calculation scheme is introduced to improve efficiency of solving the large-scale optimization problem, meanwhile strengthen the robustness to communication delay and failures. To further speed up the computation, the Nesterov acceleration strategy is introduced. Simulations show that compared to the traditional method, the proposed strategy reduces the loss and decreases the voltage by an average of 2.78 % and 11.84 % under the three wind directions, meanwhile owns stronger robustness under communication delay and failures with fewer iterations compared to traditional distributed calculation scheme.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:377:y:2025:i:pd:s0306261924019950
    DOI: 10.1016/j.apenergy.2024.124612
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924019950
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.124612?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. 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).
    2. Kandasamy, Jeevitha & Ramachandran, Rajeswari & Veerasamy, Veerapandiyan & Irudayaraj, Andrew Xavier Raj, 2024. "Distributed leader-follower based adaptive consensus control for networked microgrids," Applied Energy, Elsevier, vol. 353(PA).
    3. Lin, Wei & Jin, Xiaolong & Jia, Hongjie & Mu, Yunfei & Xu, Tao & Xu, Xiandong & Yu, Xiaodan, 2021. "Decentralized optimal scheduling for integrated community energy system via consensus-based alternating direction method of multipliers," Applied Energy, Elsevier, vol. 302(C).
    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. Li, Zepeng & Wu, Qiuwei & Li, Hui & Nie, Chengkai & Tan, Jin, 2024. "Distributed low-carbon economic dispatch of integrated power and transportation system," Applied Energy, Elsevier, vol. 353(PA).
    6. Meng, Lingzhuochao & Yang, Xiyun & Zhu, Jiang & Wang, Xinzhe & Meng, Xin, 2024. "Network partition and distributed voltage coordination control strategy of active distribution network system considering photovoltaic uncertainty," Applied Energy, Elsevier, vol. 362(C).
    7. Tan, Jin & Wu, Qiuwei & Wei, Wei & Liu, Feng & Li, Canbing & Zhou, Bin, 2020. "Decentralized robust energy and reserve Co-optimization for multiple integrated electricity and heating systems," Energy, Elsevier, vol. 205(C).
    8. Wang, Ni & Li, Jian & Yu, Xiang & Zhou, Dao & Hu, Weihao & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2020. "Optimal active and reactive power cooperative dispatch strategy of wind farm considering levelised production cost minimisation," Renewable Energy, Elsevier, vol. 148(C), pages 113-123.
    9. Chen, Zhenyu & Lin, Zhongwei & Zhai, Xiaoya & Liu, Jizhen, 2022. "Dynamic wind turbine wake reconstruction: A Koopman-linear flow estimator," Energy, Elsevier, vol. 238(PB).
    10. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Pan, Bo & Qi, Shiqiang, 2020. "Two-stage stochastic optimal operation of integrated electricity and heat system considering reserve of flexible devices and spatial-temporal correlation of wind power," Applied Energy, Elsevier, vol. 275(C).
    11. Zhou, Yu & Li, Zhengshuo & Wang, Guangrui, 2021. "Study on leveraging wind farms' robust reactive power range for uncertain power system reactive power optimization," Applied Energy, Elsevier, vol. 298(C).
    12. Xu, Da & Bai, Ziyi & Jin, Xiaolong & Yang, Xiaodong & Chen, Shuangyin & Zhou, Ming, 2022. "A mean-variance portfolio optimization approach for high-renewable energy hub," Applied Energy, Elsevier, vol. 325(C).
    13. Jin, Rongsen & Hou, Peng & Yang, Guangya & Qi, Yuanhang & Chen, Cong & Chen, Zhe, 2019. "Cable routing optimization for offshore wind power plants via wind scenarios considering power loss cost model," Applied Energy, Elsevier, vol. 254(C).
    14. Gao, Xiaoxia & Li, Bingbing & Wang, Tengyuan & Sun, Haiying & Yang, Hongxing & Li, Yonghua & Wang, Yu & Zhao, Fei, 2020. "Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements," Applied Energy, Elsevier, vol. 260(C).
    15. Martinez-Rojas, Marcela & Sumper, Andreas & Gomis-Bellmunt, Oriol & Sudrià-Andreu, Antoni, 2011. "Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search," Applied Energy, Elsevier, vol. 88(12), pages 4678-4686.
    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. 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).
    2. 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).
    3. 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).
    4. Deng, Lirong & Fu, Yang & Guo, Qinglai & Li, Zhenkun & Xue, Yixun & Zhang, Zhiquan, 2024. "Energy and reserve procurement in integrated electricity and heating system: A high-dimensional covariance matrix approach based on stochastic differential equations," Energy, Elsevier, vol. 304(C).
    5. Tan, Jin & Wu, Qiuwei & Zhang, Menglin & Wei, Wei & Liu, Feng & Pan, Bo, 2021. "Chance-constrained energy and multi-type reserves scheduling exploiting flexibility from combined power and heat units and heat pumps," Energy, Elsevier, vol. 233(C).
    6. 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.
    7. Zhang, Zhaoyi & Han, Zixi & Hu, Hao & Fan, Youping & Fan, Jianbin & Shu, Yinbiao, 2024. "Self-adaptive system state optimization based on nonlinear affine transformation for renewable energy volatility," Renewable Energy, Elsevier, vol. 230(C).
    8. Sharma, Akanksha & Jain, Sanjay K., 2021. "Day-ahead optimal reactive power ancillary service procurement under dynamic multi-objective framework in wind integrated deregulated power system," Energy, Elsevier, vol. 223(C).
    9. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Lin, Zhongwei & Fang, Fang & Chen, Qun, 2021. "Optimal operation of integrated electricity and heat system: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    10. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
    11. 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).
    12. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    13. Zhang, Shaohai & Duan, Huanfeng & Lu, Lin & He, Ruiyang & Gao, Xiaoxia & Zhu, Songye, 2024. "Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy," Energy, Elsevier, vol. 294(C).
    14. Bogdan Tomoiagă & Mircea Chindriş & Andreas Sumper & Antoni Sudria-Andreu & Roberto Villafafila-Robles, 2013. "Pareto Optimal Reconfiguration of Power Distribution Systems Using a Genetic Algorithm Based on NSGA-II," Energies, MDPI, vol. 6(3), pages 1-17, March.
    15. Fei Zhao & Yihan Gao & Tengyuan Wang & Jinsha Yuan & Xiaoxia Gao, 2020. "Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    16. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    17. Dong, Zhen & Li, Zhongguo & Liang, Zhongchao & Xu, Yiqiao & Ding, Zhengtao, 2021. "Distributed neural network enhanced power generation strategy of large-scale wind power plant for power expansion," Applied Energy, Elsevier, vol. 303(C).
    18. Cazzaro, Davide & Fischetti, Martina & Fischetti, Matteo, 2020. "Heuristic algorithms for the Wind Farm Cable Routing problem," Applied Energy, Elsevier, vol. 278(C).
    19. Gao, Xiaoxia & Chen, Yao & Xu, Shinai & Gao, Wei & Zhu, Xiaoxun & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Lu, Hao, 2022. "Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements," Applied Energy, Elsevier, vol. 307(C).
    20. Xu, Zongyuan & Gao, Xiaoxia & Zhang, Huanqiang & Lv, Tao & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu, 2023. "Analysis of the anisotropy aerodynamic characteristics of downstream wind turbine considering the 3D wake expansion based on coupling method," Energy, Elsevier, vol. 263(PD).

    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:appene:v:377:y:2025:i:pd:s0306261924019950. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.