Numerical Simulation of Control Strategies at Mutriku Wave Power Plant

François-Xavier Faÿ, James Kelly, João Henriques, Ainhoa Pujana, Mohammad Abusara, Markus Mueller, Imanol Touzon, Pablo Ruiz-Minguela

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

7 Citas (Scopus)

Resumen

In order to de-risk wave energy technologies and bring confidence to the sector, it is necessary to gain experience and collect data from sea trials. As part of the OPERA H2020 project, the Mutriku Wave Power Plant (MWPP) is being used as a real condition laboratory for the experiment of innovative technologies. The plant is situated in the North shore of Spain and has been operating since 2011. It uses the Oscillating Water Column (OWC) principle, which consists in compressing and expanding the air trapped in a chamber due to the inner free-surface oscillation resulting from the incident waves. The pressure difference between the air chamber and the atmosphere is used to drive an air turbine. In that case, a self-rectifying air turbine is the best candidate for the energy conversion, as it produces a unidirectional torque in presence of a bi-directional flow. The power take-off system installed is composed of a biradial turbine connected to a 30kW off-the-shelf squirrel cage generator. One of the novelties of the turbine is a high-speed stop-valve installed close to the rotor. The valve may be used to control the flow rate through the turbine or for latching control. This paper focuses on the development, the implementation and the numerical simulation of five control strategies including turbine speed and generator torque controllers. The algorithms were designed thanks to a numerical model describing one of the OWC chambers of the Mutriku power plant. Numerical results are presented for a variety of sea states and a comparison between the proposed control laws in terms of energy production and power quality is performed.
Idioma originalInglés
Título de la publicación alojadaunknown
EditorialAmerican Society of Mechanical Engineers (ASME)
PáginasV010T09A029
Número de páginas1
Volumen10
ISBN (versión digital)9780791851319
ISBN (versión impresa)978-079185131-9
DOI
EstadoPublicada - 2018
EventoASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2018 - Madrid, Espana
Duración: 17 jun 201822 jun 2018

Serie de la publicación

Nombre10

Conferencia

ConferenciaASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2018
País/TerritorioEspana
CiudadMadrid
Período17/06/1822/06/18

Palabras clave

  • Control algorithms
  • Model Predictive Control
  • Oscillating Water Column
  • Reinforcement Learning
  • Torque control
  • Wave energy
  • Wave-to-Wire model

Project and Funding Information

  • Project ID
  • info:eu-repo/grantAgreement/EC/H2020/654444/EU/Open Sea Operating Experience to Reduce Wave Energy Cost/OPERA
  • Funding Info
  • This work has been performed as part of the H2020 OPERA project GA 654444. The third author was supported by Portuguese Science Foundation, FCT researcher grant No. IF/01457/2014.

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