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Controller design for a tidal turbine array, considering both power and loads aspects

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  • Zhang, Yidan
  • Shek, Jonathan K.H.
  • Mueller, Markus A.

Abstract

The complex turbine-wake interactions within a tidal array leads to sub-optimal power generation from most tidal turbines, and results in higher fatigue loading on downstream turbines due to upstream turbines increase the turbulence intensity in the wake reaching other turbines. This paper presents an array controller which determines the power and loads set-points between the turbines based on incoming flow velocity for each turbine. This control methodology enables to dynamic response in time-variable flow velocity and trade-off between output power and fatigue loads through adjusting reference pitch angle and maximum power point tracking reference speed simultaneously for each turbine. The benefits of this novel control strategy is tested in a 4.5 MW three-turbine array model which is simulated in MATLAB/Simulink. Results show that in low flow velocity, the objective of stabilizing the fluctuation of loads is mainly achieved by adjusting generator speed. Conversely, the pitch controller dominates the results of the array in high flow velocity. Under the premise of mitigating fatigue loads, the proposed control strategy is still able to guarantee a high-level output power extraction.

Suggested Citation

  • Zhang, Yidan & Shek, Jonathan K.H. & Mueller, Markus A., 2023. "Controller design for a tidal turbine array, considering both power and loads aspects," Renewable Energy, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:renene:v:216:y:2023:i:c:s0960148123009771
    DOI: 10.1016/j.renene.2023.119063
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    Cited by:

    1. Druault, Philippe & Krawczynski, Jean-François & Çan, Erdi & Germain, Grégory, 2024. "On the necessity of considering the hub when examining the induction of a horizontal axis tidal turbine," Renewable Energy, Elsevier, vol. 224(C).
    2. Li, Changming & Liu, Bin & Wang, Shujie & Yuan, Peng & Lang, Xianpeng & Tan, Junzhe & Si, Xiancai, 2024. "Tidal turbine hydrofoil design and optimization based on deep learning," Renewable Energy, Elsevier, vol. 226(C).

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