Development of a Low-Friction Testbed for Model Scale Wave Energy Converter Control System Studies

Van Wieren, Mady; Gonzalez, Tania Demonte; Yassin, Houssein; Jeanetta-Wark, Niccolo; Kumpula, Theo; Naglak, John; Parker, Gordon

doi:10.23919/oceans52994.2023.10337092

OCEANS 2023 - MTS/IEEE U.S. Gulf Coast 2023

DOI: 10.23919/oceans52994.2023.10337092

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Development of a Low-Friction Testbed for Model Scale Wave Energy Converter Control System Studies

Mady Van Wieren,

Tania Demonte Gonzalez,

Houssein Yassin

et al.

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2024

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Cited by 2 publications

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Nonlinear Model Predictive Control of Heaving Wave Energy Converter with Nonlinear Froude–Krylov Forces

Demonte Gonzalez,

Anderlini,

Yassin

et al. 2024

Energies

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Wave energy holds significant promise as a renewable energy source due to the consistent and predictable nature of ocean waves. However, optimizing wave energy devices is essential for achieving competitive viability in the energy market. This paper presents the application of a nonlinear model predictive controller (MPC) to enhance the energy extraction of a heaving point absorber. The wave energy converter (WEC) model accounts for the nonlinear dynamics and static Froude–Krylov forces, which are essential in accurately representing the system’s behavior. The nonlinear MPC is tested under irregular wave conditions within the power production region, where constraints on displacement and the power take-off (PTO) force are enforced to ensure the WEC’s safety while maximizing energy absorption. A comparison is made with a linear MPC, which uses a linear approximation of the Froude–Krylov forces. The study comprehensively compares power performance and computational costs between the linear and nonlinear MPC approaches. Both MPC variants determine the optimal PTO force to maximize energy absorption, utilizing (1) a linear WEC model (LMPC) for state predictions and (2) a nonlinear model (NLMPC) incorporating exact Froude–Krylov forces. Additionally, the study analyzes four controller configurations, varying the MPC prediction horizon and re-optimization time. The results indicate that, in general, the NLMPC achieves higher energy absorption than the LMPC. The nonlinear model also better adheres to system constraints, with the linear model showing some displacement violations. This paper further discusses the computational load and power generation implications of adjusting the prediction horizon and re-optimization time parameters in the NLMPC.

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Nonlinear Model Predictive Control of Heaving Wave Energy Converter with Nonlinear Froude–Krylov Forces

Demonte Gonzalez,

Anderlini,

Yassin

et al. 2024

Energies

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Optimal Control of Nonlinear, Nonautonomous, Energy Harvesting Systems Applied to Point Absorber Wave Energy Converters

Yassin,

Demonte Gonzalez,

Nelson

et al. 2024

JMSE

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Pursuing sustainable energy solutions has prompted researchers to focus on optimizing energy extraction from renewable sources. Control laws that optimize energy extraction require accurate modeling, often resulting in time-varying, nonlinear differential equations. An energy-maximizing optimal control law is derived for time-varying, nonlinear, second-order, energy harvesting systems. We demonstrate that sustaining periodic motion under this control law when subjected to periodic disturbances necessitates identifying appropriate initial conditions, inducing the system to follow a limit cycle. The general optimal solution is applied to two point absorber wave energy converter models: a linear model where the analytical derivation of initial conditions suffices and a nonlinear model demanding a numerical approach. A stable limit cycle is obtained for the latter when the initial conditions lie within an ellipse centered at the origin of the phase plane. This work advances energy-maximizing optimal control solutions for nonautonomous nonlinear systems with application to point absorbers. The results also shed light on the significance of initial conditions in achieving physically realizable periodic motion for periodic energy harvesting systems.

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Development of a Low-Friction Testbed for Model Scale Wave Energy Converter Control System Studies

Cited by 2 publications

References 5 publications

Nonlinear Model Predictive Control of Heaving Wave Energy Converter with Nonlinear Froude–Krylov Forces

Nonlinear Model Predictive Control of Heaving Wave Energy Converter with Nonlinear Froude–Krylov Forces

Optimal Control of Nonlinear, Nonautonomous, Energy Harvesting Systems Applied to Point Absorber Wave Energy Converters

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