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Sea trial results of a predictive algorithm at the Mutriku Wave power plant and controllers assessment based on a detailed plant model

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  • Faÿ, François-Xavier
  • Robles, Eider
  • Marcos, Marga
  • Aldaiturriaga, Endika
  • Camacho, Eduardo F.

Abstract

Improving the power production in wave energy plants is essential to lower the cost of energy production from this type of installations. Oscillating Water Column is among the most studied technologies to convert the wave energy into a useful electrical one. In this paper, three control algorithms are developed to control the biradial turbine installed in the Mutriku Wave Power Plant. The work presents a comparison of their main advantages and drawbacks first from numerical simulation results and then with practical implementation in the real plant, analysing both performance and power integration into the grid. The wave-to-wire model used to develop and assess the controllers is based on linear wave theory and adjusted with operational data measured at the plant. Three different controllers which use the generator torque as manipulated variable are considered. Two of them are adaptive controllers and the other one is a nonlinear Model Predictive Control (MPC) algorithm which uses information about the future waves to compute the control actions. The best adaptive controller and the predictive one are then tested experimentally in the real power plant of Mutriku, and the performance analysis is completed with operational results. A real time sensor installed in front of the plant gives information on the incoming waves used by the predictive algorithm. Operational data are collected during a two-week testing period, enabling a thorough comparison. An overall increase over 30% in the electrical power production is obtained with the predictive control law in comparison with the reference adaptive controller.

Suggested Citation

  • Faÿ, François-Xavier & Robles, Eider & Marcos, Marga & Aldaiturriaga, Endika & Camacho, Eduardo F., 2020. "Sea trial results of a predictive algorithm at the Mutriku Wave power plant and controllers assessment based on a detailed plant model," Renewable Energy, Elsevier, vol. 146(C), pages 1725-1745.
    • Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:1725-1745
    DOI: 10.1016/j.renene.2019.07.129
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    References listed on IDEAS

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    Cited by:

    1. Ciappi, Lorenzo & Simonetti, Irene & Bianchini, Alessandro & Cappietti, Lorenzo & Manfrida, Giampaolo, 2022. "Application of integrated wave-to-wire modelling for the preliminary design of oscillating water column systems for installations in moderate wave climates," Renewable Energy, Elsevier, vol. 194(C), pages 232-248.
    2. Carrelhas, A.A.D. & Gato, L.M.C. & Henriques, J.C.C., 2023. "Peak shaving control in OWC wave energy converters: From concept to implementation in the Mutriku wave power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
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    4. Nicola Delmonte & Eider Robles & Paolo Cova & Francesco Giuliani & François Xavier Faÿ & Joseba Lopez & Piero Ruol & Luca Martinelli, 2020. "An Iterative Refining Approach to Design the Control of Wave Energy Converters with Numerical Modeling and Scaled HIL Testing," Energies, MDPI, vol. 13(10), pages 1-19, May.
    5. Tomás Cabral & Daniel Clemente & Paulo Rosa-Santos & Francisco Taveira-Pinto & Tiago Morais & Filipe Belga & Henrique Cestaro, 2020. "Performance Assessment of a Hybrid Wave Energy Converter Integrated into a Harbor Breakwater," Energies, MDPI, vol. 13(1), pages 1-22, January.
    6. Carrelhas, A.A.D. & Gato, L.M.C. & Falcão, A.F.O. & Henriques, J.C.C., 2021. "Control law design for the air-turbine-generator set of a fully submerged 1.5 MW mWave prototype. Part 2: Experimental validation," Renewable Energy, Elsevier, vol. 171(C), pages 1002-1013.
    7. Calheiros-Cabral, Tomás & Clemente, Daniel & Rosa-Santos, Paulo & Taveira-Pinto, Francisco & Ramos, Victor & Morais, Tiago & Cestaro, Henrique, 2020. "Evaluation of the annual electricity production of a hybrid breakwater-integrated wave energy converter," Energy, Elsevier, vol. 213(C).

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