TY - GEN
T1 - Numerical Simulation of Control Strategies at Mutriku Wave Power Plant
AU - Faÿ, François-Xavier
AU - Kelly, James
AU - Henriques, João
AU - Pujana, Ainhoa
AU - Abusara, Mohammad
AU - Mueller, Markus
AU - Touzon, Imanol
AU - Ruiz-Minguela, Pablo
N1 - Publisher Copyright:
© Copyright 2018 ASME.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Control algorithms
KW - Model Predictive Control
KW - Oscillating Water Column
KW - Reinforcement Learning
KW - Torque control
KW - Wave energy
KW - Wave-to-Wire model
KW - Control algorithms
KW - Model Predictive Control
KW - Oscillating Water Column
KW - Reinforcement Learning
KW - Torque control
KW - Wave energy
KW - Wave-to-Wire model
UR - http://www.scopus.com/inward/record.url?scp=85055439662&partnerID=8YFLogxK
U2 - 10.1115/OMAE2018-78011
DO - 10.1115/OMAE2018-78011
M3 - Conference contribution
SN - 978-079185131-9
VL - 10
T3 - 10
SP - V010T09A029
BT - unknown
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2018
Y2 - 17 June 2018 through 22 June 2018
ER -
