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Displacement of the maximum power point caused by losses in wind turbine systems

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  • De Kooning, Jeroen D.M.
  • Vandoorn, Tine L.
  • Van de Vyver, Jan
  • Meersman, Bart
  • Vandevelde, Lieven

Abstract

The energy yield of wind turbines is to a large extent determined by the performance of the Maximum Power Point Tracking (MPPT) algorithm. Conventionally, they are programmed to maximize the turbines power coefficient. However, due to losses in the generator and converter, the true optimal operating point of the system shifts. This effect is often overlooked, which results in a decreased energy yield. Therefore, in this paper, the wind turbine system is modeled including the dominant loss components to investigate this effect in detail. By simulations and experiments on a wind turbine emulator, it is shown that the location of the maximum power point is significantly affected for low wind speeds. For high wind speeds, the effect is less pronounced. The parameter of interest is the increase in yearly energy output with respect to the classical MPPT method, which is calculated in this paper by including a Rayleigh wind speed distribution. For typical average wind speeds, the energy yield can increase with 1–2%. There is no cost associated with operating the turbine in the overall MPP, making it worthwhile to include this effect. The findings are implemented in an MPPT algorithm to validate the increased performance in a dynamic situation.

Suggested Citation

  • De Kooning, Jeroen D.M. & Vandoorn, Tine L. & Van de Vyver, Jan & Meersman, Bart & Vandevelde, Lieven, 2016. "Displacement of the maximum power point caused by losses in wind turbine systems," Renewable Energy, Elsevier, vol. 85(C), pages 273-280.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:273-280
    DOI: 10.1016/j.renene.2015.06.052
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    References listed on IDEAS

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    1. Narayana, M. & Putrus, G.A. & Jovanovic, M. & Leung, P.S. & McDonald, S., 2012. "Generic maximum power point tracking controller for small-scale wind turbines," Renewable Energy, Elsevier, vol. 44(C), pages 72-79.
    2. Cárdenas, Roberto & Peña, Rubén & Wheeler, Patrick & Clare, Jon & Juri, Carlos, 2012. "Control of a matrix converter for the operation of autonomous systems," Renewable Energy, Elsevier, vol. 43(C), pages 343-353.
    3. Fleck, Brian & Huot, Marc, 2009. "Comparative life-cycle assessment of a small wind turbine for residential off-grid use," Renewable Energy, Elsevier, vol. 34(12), pages 2688-2696.
    4. Kortabarria, Iñigo & Andreu, Jon & Martínez de Alegría, Iñigo & Jiménez, Jaime & Gárate, José Ignacio & Robles, Eider, 2014. "A novel adaptative maximum power point tracking algorithm for small wind turbines," Renewable Energy, Elsevier, vol. 63(C), pages 785-796.
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    Cited by:

    1. Hoffstaedt, J.P. & Truijen, D.P.K. & Fahlbeck, J. & Gans, L.H.A. & Qudaih, M. & Laguna, A.J. & De Kooning, J.D.M. & Stockman, K. & Nilsson, H. & Storli, P.-T. & Engel, B. & Marence, M. & Bricker, J.D., 2022. "Low-head pumped hydro storage: A review of applicable technologies for design, grid integration, control and modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    2. Arash E. Samani & Jeroen D. M. De Kooning & Nezmin Kayedpour & Narender Singh & Lieven Vandevelde, 2020. "The Impact of Pitch-To-Stall and Pitch-To-Feather Control on the Structural Loads and the Pitch Mechanism of a Wind Turbine," Energies, MDPI, vol. 13(17), pages 1-21, September.
    3. Karabacak, Murat, 2019. "A new perturb and observe based higher order sliding mode MPPT control of wind turbines eliminating the rotor inertial effect," Renewable Energy, Elsevier, vol. 133(C), pages 807-827.
    4. Andrea Bonfiglio & Federico Delfino & Marco Invernizzi & Renato Procopio, 2017. "Modeling and Maximum Power Point Tracking Control of Wind Generating Units Equipped with Permanent Magnet Synchronous Generators in Presence of Losses," Energies, MDPI, vol. 10(1), pages 1-24, January.

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