IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i16p4848-d610976.html
   My bibliography  Save this article

Optimization Control Strategy for Large Doubly-Fed Induction Generator Wind Farm Based on Grouped Wind Turbine

Author

Listed:
  • Shijia Zhou

    (Department of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Fei Rong

    (Department of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Xiaojie Ning

    (Nanning Power Supply Bureau of Guangxi Power Grid Co., Ltd., Nanning 530023, China)

Abstract

This paper proposes a grouped, reactive power optimization control strategy to maximize the active power output of a doubly-fed induction generator (DFIG) based on a large wind farm (WF). Optimization problems are formulated based on established grouped loss models and the reactive power limits of the wind turbines (WTs). The WTs in the WF are grouped to relieve computational burden. The particle swarm optimization (PSO) algorithm is applied to optimize the distribution of reactive power among groups, and a proportional control strategy is used to distribute the reactive power requirements in each group. Furthermore, the proposed control strategy optimizes the reactive power distribution between the stator and the grid side converter (GSC) in each WT. The proposed control strategy greatly reduces the number of variables for optimization, and increases the calculation speed of the algorithm. Thus, the control strategy can not only increase the active power output of the WF but also enable the WF to track the reactive power dispatching instruction of the power grid. A simulation of the DFIG WF is given to verify the effectiveness of the proposed control strategy at different wind speeds and reactive power references.

Suggested Citation

  • Shijia Zhou & Fei Rong & Xiaojie Ning, 2021. "Optimization Control Strategy for Large Doubly-Fed Induction Generator Wind Farm Based on Grouped Wind Turbine," Energies, MDPI, vol. 14(16), pages 1-16, August.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4848-:d:610976
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/16/4848/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/16/4848/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Baohua Zhang & Weihao Hu & Peng Hou & Jin Tan & Mohsen Soltani & Zhe Chen, 2017. "Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm," Energies, MDPI, vol. 10(7), pages 1-17, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Feng-Chang Gu & Hung-Cheng Chen, 2021. "An Anti-Fluctuation Compensator Design and Its Control Strategy for Wind Farm System," Energies, MDPI, vol. 14(19), pages 1-16, October.
    2. Adolfo Dannier & Emanuele Fedele & Ivan Spina & Gianluca Brando, 2022. "Doubly-Fed Induction Generator (DFIG) in Connected or Weak Grids for Turbine-Based Wind Energy Conversion System," Energies, MDPI, vol. 15(17), pages 1-5, September.

    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. Wang, Ni & Li, Jian & Hu, Weihao & Zhang, Baohua & Huang, Qi & Chen, Zhe, 2019. "Optimal reactive power dispatch of a full-scale converter based wind farm considering loss minimization," Renewable Energy, Elsevier, vol. 139(C), pages 292-301.
    2. 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.
    3. Hesong Cui & Xueping Li & Gongping Wu & Yawei Song & Xiao Liu & Derong Luo, 2021. "MPC Based Coordinated Active and Reactive Power Control Strategy of DFIG Wind Farm with Distributed ESSs," Energies, MDPI, vol. 14(13), pages 1-19, June.
    4. Van-Hai Bui & Akhtar Hussain & Woon-Gyu Lee & Hak-Man Kim, 2019. "Multi-Objective Optimization for Determining Trade-Off between Output Power and Power Fluctuations in Wind Farm System," Energies, MDPI, vol. 12(22), pages 1-18, November.
    5. Luís F. N. Lourenço & Renato M. Monaro & Maurício B. C. Salles & José R. Cardoso & Loïc Quéval, 2018. "Evaluation of the Reactive Power Support Capability and Associated Technical Costs of Photovoltaic Farms’ Operation," Energies, MDPI, vol. 11(6), pages 1-19, June.

    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:gam:jeners:v:14:y:2021:i:16:p:4848-:d:610976. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.