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Adaptive Extremum Seeking Control of Urban Area Wind Turbines

Author

Listed:
  • Felix Dietrich

    (Automation and Intelligent Systems Group/Control Engineering Group, Faculty 1: School of Engineering—Energy and Information, University of Applied Sciences (HTW) Berlin, 12459 Berlin, Germany
    Current address: Wilhelminenhofstraße 75A, 12459 Berlin, Germany.)

  • Steffen Borchers-Tigasson

    (Automation and Intelligent Systems Group/Control Engineering Group, Faculty 1: School of Engineering—Energy and Information, University of Applied Sciences (HTW) Berlin, 12459 Berlin, Germany
    Current address: Wilhelminenhofstraße 75A, 12459 Berlin, Germany.)

  • Till Naumann

    (MOWEA—Modulare Windenergieanlagen GmbH, Storkower Str. 115A, 10407 Berlin, Germany)

  • Horst Schulte

    (Automation and Intelligent Systems Group/Control Engineering Group, Faculty 1: School of Engineering—Energy and Information, University of Applied Sciences (HTW) Berlin, 12459 Berlin, Germany
    Current address: Wilhelminenhofstraße 75A, 12459 Berlin, Germany.)

Abstract

Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics.

Suggested Citation

  • Felix Dietrich & Steffen Borchers-Tigasson & Till Naumann & Horst Schulte, 2021. "Adaptive Extremum Seeking Control of Urban Area Wind Turbines," Energies, MDPI, vol. 14(5), pages 1-12, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1356-:d:508982
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    References listed on IDEAS

    as
    1. Ciri, Umberto & Rotea, Mario A. & Leonardi, Stefano, 2017. "Model-free control of wind farms: A comparative study between individual and coordinated extremum seeking," Renewable Energy, Elsevier, vol. 113(C), pages 1033-1045.
    2. Hu, Lu & Xue, Fei & Qin, Zijian & Shi, Jiying & Qiao, Wen & Yang, Wenjing & Yang, Ting, 2019. "Sliding mode extremum seeking control based on improved invasive weed optimization for MPPT in wind energy conversion system," Applied Energy, Elsevier, vol. 248(C), pages 567-575.
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    Cited by:

    1. Altaf Hussain Rajpar & Imran Ali & Ahmad E. Eladwi & Mohamed Bashir Ali Bashir, 2021. "Recent Development in the Design of Wind Deflectors for Vertical Axis Wind Turbine: A Review," Energies, MDPI, vol. 14(16), pages 1-23, August.

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