IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v156y2018icp360-370.html
   My bibliography  Save this article

Modelling and control of a wind turbine and farm

Author

Listed:
  • Hur, Sung-ho

Abstract

The Matlab/Simulink model of the Supergen (Sustainable Power Generation and Supply) Wind 5 MW exemplar wind turbine, which has been employed by a number of researchers at various institutions and Universities over the last decade, is reported. It is subsequently improved, especially in speed, to facilitate wind farm modelling, which usually involves duplicating wind turbine models. The improvement is achieved through various stages, including prewarping, discretisation using Heun's method in addition to Euler method, and conversion to C. Results are presented to demonstrate that improvement in speed is significant and that the resulting wind turbine model can be used for wind farm modelling more efficiently. It is important to highlight that improvement in speed is achieved without compromising the complexity of the turbine model; that is, each turbine included in a wind farm is neither simplified nor compromised. The use of the wind farm model for testing a wind farm controller that has recently been introduced is also demonstrated.

Suggested Citation

  • Hur, Sung-ho, 2018. "Modelling and control of a wind turbine and farm," Energy, Elsevier, vol. 156(C), pages 360-370.
    • Handle: RePEc:eee:energy:v:156:y:2018:i:c:p:360-370
    DOI: 10.1016/j.energy.2018.05.071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218308910
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.05.071?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.

    Citations

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


    Cited by:

    1. Song, Dongran & Yang, Yinggang & Zheng, Songyue & Tang, Weiyi & Yang, Jian & Su, Mei & Yang, Xuebing & Joo, Young Hoon, 2019. "Capacity factor estimation of variable-speed wind turbines considering the coupled influence of the QN-curve and the air density," Energy, Elsevier, vol. 183(C), pages 1049-1060.
    2. Liu, Jizhen & Yao, Qi & Hu, Yang, 2019. "Model predictive control for load frequency of hybrid power system with wind power and thermal power," Energy, Elsevier, vol. 172(C), pages 555-565.
    3. Mahdy, Ahmed & Hasanien, Hany M. & Helmy, Waleed & Turky, Rania A. & Abdel Aleem, Shady H.E., 2022. "Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy," Energy, Elsevier, vol. 245(C).
    4. Sotoudeh, Freshteh & Kamali, Reza & Mousavi, Seyed Mahmood, 2019. "Field tests and numerical modeling of INVELOX wind turbine application in low wind speed region," Energy, Elsevier, vol. 181(C), pages 745-759.
    5. 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.
    6. Siahpour, Shahin & Khakiani, Fardad N. & Fazlollahi, Vahid & Golozar, Ali & Shirazi, Farzad A., 2021. "Morphing Omni-directional Panel Mechanism: A novel active roof design for improving the performance of the wind delivery system," Energy, Elsevier, vol. 217(C).
    7. Abhinandan Routray & Yiza Srikanth Reddy & Sung-ho Hur, 2023. "Predictive Control of a Wind Turbine Based on Neural Network-Based Wind Speed Estimation," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    8. Naemi, Mostafa & Brear, Michael J., 2020. "A hierarchical, physical and data-driven approach to wind farm modelling," Renewable Energy, Elsevier, vol. 162(C), pages 1195-1207.
    9. Xiaobing Kong & Lele Ma & Xiangjie Liu & Mohamed Abdelkarim Abdelbaky & Qian Wu, 2020. "Wind Turbine Control Using Nonlinear Economic Model Predictive Control over All Operating Regions," Energies, MDPI, vol. 13(1), pages 1-21, January.

    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:energy:v:156:y:2018:i:c:p:360-370. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/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.