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Power regulation of a wind farm through flexible operation of turbines using predictive control

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  • Routray, Abhinandan
  • Hur, Sung-ho

Abstract

Wind farms are becoming larger, presenting opportunities to improve their efficiency and effectiveness. Although wind farm control can be used to adjust a wind farm’s power output to meet grid requirements, its development is restricted by the limited flexibility of wind turbine operation. Wind turbines are typically designed to operate at the power output determined by the wind speed, making it difficult to adjust their power output quickly and easily in response to changes in grid demand. A new approach to wind farm control that provides full flexibility for both wind farms and turbines is proposed. This method adjusts the wind farm’s power production using predictive control of each turbine to meet the grid demands. The power generated by each turbine is adjusted to achieve this, keeping fluctuation in the wind farm power output low. A wind farm simulation is conducted under varying wind speeds using the discretized C MEX Matlab/SIMULINKR○ model of the 5 MW Supergen turbine and the wind turbine model from NREL. The results demonstrate that the wind farm power output tracks a reference value that can be set by the grid. The results are also analyzed on the torque/speed plane, and they indicate that the turbines operate within their specified safe operating zones under both normal and gusty wind operating conditions at the same time.

Suggested Citation

  • Routray, Abhinandan & Hur, Sung-ho, 2024. "Power regulation of a wind farm through flexible operation of turbines using predictive control," Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224036958
    DOI: 10.1016/j.energy.2024.133917
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    References listed on IDEAS

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    1. Hansen, Anca D. & Sørensen, Poul & Iov, Florin & Blaabjerg, Frede, 2006. "Centralised power control of wind farm with doubly fed induction generators," Renewable Energy, Elsevier, vol. 31(7), pages 935-951.
    2. Hur, Sung-ho, 2018. "Modelling and control of a wind turbine and farm," Energy, Elsevier, vol. 156(C), pages 360-370.
    3. Rodríguez-Amenedo, J.L. & Arnaltes, S. & Rodríguez, M.A., 2008. "Operation and coordinated control of fixed and variable speed wind farms," Renewable Energy, Elsevier, vol. 33(3), pages 406-414.
    4. Hur, S. & Recalde-Camacho, L. & Leithead, W.E., 2017. "Detection and compensation of anomalous conditions in a wind turbine," Energy, Elsevier, vol. 124(C), pages 74-86.
    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.
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    Citations

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    Cited by:

    1. Yu, Solui & Hur, Jin, 2025. "An enhanced critical operating constraint forecasting (COCF) for power grids with large scale wind generating resources," Energy, Elsevier, vol. 331(C).
    2. Liu, Jingwen & Wei, Shanbi & Wang, Yu & Yang, Wei, 2025. "Distributed collaborative model predictive control based on computationally feasible mesh wind farms," Energy, Elsevier, vol. 335(C).
    3. Dai, Juchuan & Zeng, Huifan & Wen, Li & Zhang, Fan & Tang, Kun, 2025. "A novel time-history optimization control method for power control of wind turbines based on aging evaluation," Energy, Elsevier, vol. 334(C).
    4. Li, Pei-hang & Jia, Rong & Cao, Ge & Ming, Bo & Guo, Yi & Wang, Song-kai & Li, Wei, 2025. "A novel perspective for equivalent aggregation of wind farm: Measuring the dynamic similarity between output time-series," Applied Energy, Elsevier, vol. 392(C).

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