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Modelling and control of a wind turbine and farm

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  • 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
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    Citations

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    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. 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).
    3. 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.
    4. 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).
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    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.

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