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Hardware-in-the-Loop Validation of Model Predictive Control of a Discrete Fluid Power Power Take-Off System for Wave Energy Converters

Author

Listed:
  • Anders H. Hansen

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, 9220 Aalborg East, Denmark)

  • Magnus F. Asmussen

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, 9220 Aalborg East, Denmark)

  • Michael M. Bech

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 111, 9220 Aalborg East, Denmark)

Abstract

Model predictive control based wave power extraction algorithms have been developed and found promising for wave energy converters. Although mostly proven by simulation studies, model predictive control based algorithms have shown to outperform classical wave power extraction algorithms such as linear damping and reactive control. Prediction models and objective functions have, however, often been simplified a lot by for example, excluding power take-off system losses. Furthermore, discrete fluid power forces systems has never been validated experimentally in published research. In this paper a model predictive control based wave power extraction algorithm is designed for a discrete fluid power power take-off system. The loss models included in the objective function are based on physical models of the losses associated with discrete force shifts and throttling. The developed wave power extraction algorithm directly includes the quantized force output and the losses models of the discrete fluid power system. The experimental validation of the wave power extraction algorithm developed in the paper shown an increase of 14.6% in yearly harvested energy when compared to a reactive control algorithm.

Suggested Citation

  • Anders H. Hansen & Magnus F. Asmussen & Michael M. Bech, 2019. "Hardware-in-the-Loop Validation of Model Predictive Control of a Discrete Fluid Power Power Take-Off System for Wave Energy Converters," Energies, MDPI, vol. 12(19), pages 1-22, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3668-:d:270630
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    References listed on IDEAS

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    1. Guo, Bingyong & Patton, Ron J. & Jin, Siya & Lan, Jianglin, 2018. "Numerical and experimental studies of excitation force approximation for wave energy conversion," Renewable Energy, Elsevier, vol. 125(C), pages 877-889.
    2. Rico H. Hansen & Morten M. Kramer & Enrique Vidal, 2013. "Discrete Displacement Hydraulic Power Take-Off System for the Wavestar Wave Energy Converter," Energies, MDPI, vol. 6(8), pages 1-44, August.
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    Cited by:

    1. Ryan G. Coe & Giorgio Bacelli, 2023. "Useful Power Maximization for Wave Energy Converters," Energies, MDPI, vol. 16(1), pages 1-2, January.
    2. Gaspar, José F. & Pinheiro, Rafael F. & Mendes, Mário J.G. C. & Kamarlouei, Mojtaba & Guedes Soares, C., 2024. "Review on hardware-in-the-loop simulation of wave energy converters and power take-offs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    3. Niklas Enoch Andersen & Jakob Blåbjerg Mathiasen & Maja Grankær Carøe & Chen Chen & Christian-Emil Helver & Allan Lynggaard Ludvigsen & Nis Frededal Ebsen & Anders Hedegaard Hansen, 2022. "Optimisation of Control Algorithm for Hydraulic Power Take-Off System in Wave Energy Converter," Energies, MDPI, vol. 15(19), pages 1-18, September.
    4. Lasse Schmidt & Kenneth Vorbøl Hansen, 2022. "Electro-Hydraulic Variable-Speed Drive Networks—Idea, Perspectives, and Energy Saving Potentials," Energies, MDPI, vol. 15(3), pages 1-33, February.

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