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Experimental Validation of Damping Adjustment Method with Generator Parameter Study for Wave Energy Conversion

Author

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  • Fabian G. Pierart

    (Department of Mechanical Engineering, College of Engineering, Universidad del Bío-Bío, 4051381 Collao Avenue, Concepción 1202, Chile)

  • Matias Rubilar

    (Department of Mechanical Engineering, College of Engineering, Universidad del Bío-Bío, 4051381 Collao Avenue, Concepción 1202, Chile)

  • Jaime Rohten

    (Department of Electric and Electronic Engineering, College of Engineering, Universidad del Bío-Bío, 4051381 Collao Avenue, Concepción 1202, Chile)

Abstract

Effective control strategies are essential for optimizing wave energy production. While theoretical studies have explored various control approaches, experimental validation of these methods remains limited. This study proposes a damping adjustment method as a means to enable the experimental application of resistive control in wave energy systems. The system’s damping is adjusted through a variable electrical resistance coupled to the generator. A mathematical model is developed to capture the interaction between the wave energy converter, generator, and variable resistance. Experimental validation demonstrates a good fit between the experimental results and the mathematical model. Four different DC machines acting as generators are tested to evaluate the influence of the model’s parameters on control capability. Results indicate that DC machines with less internal resistance allow a wider range of damping and power adjustment by using external resistance. The proposed method shows promising results, emphasizing the significance of the DC machine parameters in achieving effective control over system variables. These findings contribute to the development of efficient and reliable control strategies for enhancing wave energy production at small scales.

Suggested Citation

  • Fabian G. Pierart & Matias Rubilar & Jaime Rohten, 2023. "Experimental Validation of Damping Adjustment Method with Generator Parameter Study for Wave Energy Conversion," Energies, MDPI, vol. 16(14), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5298-:d:1191447
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    References listed on IDEAS

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    5. Aleix Maria-Arenas & Aitor J. Garrido & Eugen Rusu & Izaskun Garrido, 2019. "Control Strategies Applied to Wave Energy Converters: State of the Art," Energies, MDPI, vol. 12(16), pages 1-19, August.
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    Cited by:

    1. Fabian G. Pierart & Pedro G. Campos & Cristian E. Basoalto & Jaime Rohten & Thomas Davey, 2024. "Experimental Implementation of Reinforcement Learning Applied to Maximise Energy from a Wave Energy Converter," Energies, MDPI, vol. 17(20), pages 1-13, October.

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