Efficiency-aware nonlinear model-predictive control with real-time iteration scheme for wave energy converters

Guerrero-Fernández, Juan; Villarreal, Oscar Julian Gonzalez; Rossiter, J.A.

doi:10.1080/00207179.2022.2078424

Cited by 4 publications

(2 citation statements)

References 33 publications

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“…For the purpose of energy maximization, a considerable number of control strategies can be found in the literature, such as reactive control [13], model predictive control (MPC) [14], moment-matching based control [15], Spectral/Pseudospectral-based (MPClike type) control [16], LTI (LiTe-Con) controller [17], etc. The most well known of these is reactive control [18], based on linear resonance theory, and it has been discussed and tested in many references.…”

Section: Introductionmentioning

confidence: 99%

“…At first glance, this seems to be because the use of a "complex conjugate" method may violate the WEC linear model assumption of the hydrodynamics, involving many power fluctuations (both positive and negative), and can be limited to application for regular wave conditions, due to its frequency-dependent characteristic. The other choice is MPC [14,16,19], which selects the average absorbed mechanical power as an objective function and maximizes the power by solving an optimization problem. The MPC can reach the optimal solution for energy extraction and deal with system constraints elegantly.…”

Section: Introductionmentioning

confidence: 99%

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Model Predictive Energy-Maximising Tracking Control for a Wavestar-Prototype Wave Energy Converter

Patton

2023

JMSE

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To date, one of the main challenges in the wave energy field is to achieve energy-maximizing control in order to reduce the levelized cost of energy (LCOE). This paper presents a model predictive velocity tracking control method based on a hierarchical structure for a Wavestar-like deivce in the WEC-SIM benchmark. The first part of the system structure aims to estimate the wave excitation moment (WEM) by using a Kalman filter. Then, an extended Kalman filter (EKF) is chosen to obtain the amplitude and angular frequency of the WEM in order to compute the reference velocity. Following this, a low-level model predictive control (MPC) method is designed to ensure the wave energy converter (WEC) tracks the optimal reference velocity for maximum energy extraction from irregular waves. Two Gaussian Process (GP) models are considered to predict the future wave excitation moment and future reference velocity, which are needed in MPC design. The proposed strategy can give a new vision for energy-maximizing tracking control based on MPC.

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