TY - JOUR
T1 - Maximum Energy Capturing Approach for Heaving Wave Energy Converters Using an Estimator-Based Finite Control Set Model Predictive Control
AU - Jama, Mohammed
AU - Mon, Bisni Fahad
AU - Wahyudie, Addy
AU - Mekhilef, Saad
N1 - Funding Information:
This work was supported in part by the Joint Research Program between UAE University and Asian Universities Alliance (AUA) under Grant 31R169, and in part by the Ph.D. Fund under Grant 31N275.
Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - The control problem in wave energy continues to remain an open question. This is mainly attributed to the difficulties associated with developing effective, yet economically viable, wave energy-harnessing control strategies, such as resource irregularity, the multidisciplinary nature of the system, and dynamic model uncertainties and ambiguities. Herein, a maximum energy-capturing approach for heaving wave energy converters (WECs) using an estimator-based finite control set model predictive control (FCS-MPC) is proposed. The proposed control strategy utilizes an elaborate nonlinear wave-to-wire model of a heaving WEC. The FCS-MPC is formulated such that a control command trajectory is not required; instead, it searches for the optimum control law - in the form of switching functions - that maximizes the WEC converted electrical energy while imposing soft constraints on the states of the power take-off (PTO) mechanism. Current transducers are deployed to measure the PTO three-phase currents and both mechanical and electrical variables required by the FCS-MPC strategy are estimated using an electrical-based extended Kalman filter (E-EKF). Simulations were performed to assess the effectiveness of the proposed control strategy. Results presented herein clearly show that the proposed referenceless FCS-MPC managed to produce 10%-23% more energy compared with benchmark resistive loading-based techniques with both fixed and variable wave frequency capabilities while utilizing 18%-45% less PTO resources.
AB - The control problem in wave energy continues to remain an open question. This is mainly attributed to the difficulties associated with developing effective, yet economically viable, wave energy-harnessing control strategies, such as resource irregularity, the multidisciplinary nature of the system, and dynamic model uncertainties and ambiguities. Herein, a maximum energy-capturing approach for heaving wave energy converters (WECs) using an estimator-based finite control set model predictive control (FCS-MPC) is proposed. The proposed control strategy utilizes an elaborate nonlinear wave-to-wire model of a heaving WEC. The FCS-MPC is formulated such that a control command trajectory is not required; instead, it searches for the optimum control law - in the form of switching functions - that maximizes the WEC converted electrical energy while imposing soft constraints on the states of the power take-off (PTO) mechanism. Current transducers are deployed to measure the PTO three-phase currents and both mechanical and electrical variables required by the FCS-MPC strategy are estimated using an electrical-based extended Kalman filter (E-EKF). Simulations were performed to assess the effectiveness of the proposed control strategy. Results presented herein clearly show that the proposed referenceless FCS-MPC managed to produce 10%-23% more energy compared with benchmark resistive loading-based techniques with both fixed and variable wave frequency capabilities while utilizing 18%-45% less PTO resources.
KW - Wave energy converter
KW - damping control
KW - extended Kalman filter
KW - finite control set
KW - model predictive control
KW - permanent magnet linear generator
KW - point absorber
KW - wave-to-wire model
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U2 - 10.1109/ACCESS.2021.3077444
DO - 10.1109/ACCESS.2021.3077444
M3 - Article
AN - SCOPUS:85105845792
SN - 2169-3536
VL - 9
SP - 67648
EP - 67659
JO - IEEE Access
JF - IEEE Access
M1 - 9422707
ER -