scholarly journals Semi-Active Control for Two-Body Ocean Wave Energy Converter by Using Hybrid Model Predictive Control

2018 ◽  
Author(s):  
Qiuchi Xiong ◽  
Xiaofan Li ◽  
Dillon Martin ◽  
Sijing Guo ◽  
Lei Zuo
Keyword(s):  
Quadratic Programming ◽  
Active Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Control Strategy ◽  
Optimal Solution ◽  
Energy Converter ◽  
Negative Power ◽  
Ocean Wave Energy ◽  
Power Maximization

Model predictive control (MPC) has been considered as one important feed-forward optimal control strategy for ocean wave energy converter (WEC) targeted on power maximization. The capability of MPC to handle system constraints (ex. stroke, velocity, actuator limitations), and the availability to provide optimal solution for linear system provide potential for the implementation of such algorithm in the WEC control. However, currently, only active MPC control has been introduced for single and two-body WECs. Such control strategy may introduce negative power during the optimization process, since the power take-off (PTO) damping has no constraint. In this paper, we proposed a hybrid MPC strategy in limiting both the PTO damping force and PTO damping to avoid negative power generation during cost function minimization (negative power minimization) for the two-body WEC. The problem is formulated into a quadratic programming (QP) problem targeted at power maximization. However, the standard QP problem formulation cannot be directly applied to the semi-active control problem due to the PTO damping constraints. Therefore, the problem is reformulated as a Mixed-integer Quadratic Programming (MIQP) problem, which contains logical switch to select constraint matrices based on the sign of the relative velocity between the buoy and submerged body. The optimal solution is compared with those of the active MPC control strategy and the passive model with the same irregular wave input.

scholarly journals Passive Model Predictive Control on a Two-Body Self-Referenced Point Absorber Wave Energy Converter

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1731
Author(s):  
Dan Montoya ◽  
Elisabetta Tedeschi ◽  
Luca Castellini ◽  
Tiago Martins
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Power Flow ◽  
Linear Constraints ◽  
Wave Energy Converter ◽  
Control Technique ◽  
Computational Time ◽  
Energy Converter ◽  
Point Absorber

Wave energy is nowadays one of the most promising renewable energy sources; however, wave energy technology has not reached the fully-commercial stage, yet. One key aspect to achieve this goal is to identify an effective control strategy for each selected Wave Energy Converter (WEC), in order to extract the maximum energy from the waves, while respecting the physical constraints of the device. Model Predictive Control (MPC) can inherently satisfy these requirements. Generally, MPC is formulated as a quadratic programming problem with linear constraints (e.g., on position, speed and Power Take-Off (PTO) force). Since, in the most general case, this control technique requires bidirectional power flow between the PTO system and the grid, it has similar characteristics as reactive control. This means that, under some operating conditions, the energy losses may be equivalent, or even larger, than the energy yielded. As many WECs are designed to only allow unidirectional power flow, it is necessary to set nonlinear constraints. This makes the optimization problem significantly more expensive in terms of computational time. This work proposes two MPC control strategies applied to a two-body point absorber that address this issue from two different perspectives: (a) adapting the MPC formulation to passive loading strategy; and (b) adapting linear constraints in the MPC in order to only allow an unidirectional power flow. The results show that the two alternative proposals have similar performance in terms of computational time compared to the regular MPC and obtain considerably more power than the linear passive control, thus proving to be a good option for unidirectional PTO systems.

Co-design of a wave energy converter using constrained predictive control

2017 ◽  
Vol 102 ◽  
pp. 142-156 ◽  
Author(s):  
Adrian C.M. O'Sullivan ◽  
Gordon Lightbody
Keyword(s):  
Predictive Control ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Energy Converter

Performance of a Wave-Energy-Converter Array Operating Under Model-Predictive Control Based on a Convex Formulation

2018 ◽  
Author(s):  
Qian Zhong ◽  
Ronald W. Yeung
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Reactive Power ◽  
Optimal Solution ◽  
Energy Output ◽  
Control Input ◽  
Energy Extraction ◽  
Power Performance ◽  
Point Absorbers

Economics decision drives the operation of ocean-wave energy converters (WEC) to be in a “farm mode”. Control strategy developed for a WEC array will be of high importance for improving the aggregate energy extraction efficiency of the whole system. Model-predictive control (MPC) has shown its strong potential in maximizing the energy output in devices with hard constraints on operation states and machinery inputs (See Ref. [1–3]). Computational demands for using MPC to control an array in real time can be prohibitive. In this paper, we formulate the MPC to control an array of heaving point absorbers, by recasting the optimization problem for energy extraction into a convex Quadratic Programming (QP) problem, the solution of which can be carried out very efficiently. Large slew rates are to be penalized, which can also guarantee the convexity of the QP and improve the computational efficiency for achieving the optimal solution. Constraints on both the states and the control input can be accommodated in this MPC method. Full hydro-dynamic interference effects among the WEC array components are taken into account using the theory developed in [4]. Demonstrative results of the application are presented for arrays of two, three, and four point absorbers operating at different incident-wave angles. Effects of the interacting waves on power performance of the array under the new MPC control are investigated, with simulations conducted in both regular and irregular seas. Heaving motions of individual devices at their optimal conditions are shown. Also presented is the reactive power required by the power takeoff (PTO) system of the array to achieve optimality. We are pleased to contribute this article in celebration of our collegiality with Professor Bernard Molin on the occasion of his honoring symposium.

scholarly journals Validation of a CFD-based numerical wave tank model for the power production assessment of the wavestar ocean wave energy converter

2020 ◽  
Vol 146 ◽  
pp. 2499-2516 ◽  
Author(s):  
Christian Windt ◽  
Josh Davidson ◽  
Edward J. Ransley ◽  
Deborah Greaves ◽  
Morten Jakobsen ◽  
...  
Keyword(s):  
Wave Energy ◽  
Power Production ◽  
Wave Energy Converter ◽  
Ocean Wave ◽  
Numerical Wave Tank ◽  
Energy Converter ◽  
Tank Model ◽  
Wave Tank ◽  
Ocean Wave Energy ◽  
Numerical Wave

scholarly journals Model Predictive Control Tuning by Inverse Matching for a Wave Energy Converter

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4158 ◽  
Author(s):  
Hancheol Cho ◽  
Giorgio Bacelli ◽  
Ryan G. Coe
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Energy Converter ◽  
Feedback Form ◽  
Linear Controller ◽  
Prediction Horizon ◽  
The Cost ◽  
Input And State Constraints

This paper investigates the application of a method to find the cost function or the weight matrices to be used in model predictive control (MPC) such that the MPC has the same performance as a predesigned linear controller in state-feedback form when constraints are not active. This is potentially useful when a successful linear controller already exists and it is necessary to incorporate the constraint-handling capabilities of MPC. This is the case for a wave energy converter (WEC), where the maximum power transfer law is well-understood. In addition to solutions based on numerical optimization, a simple analytical solution is also derived for cases with a short prediction horizon. These methods are applied for the control of an empirically-based WEC model. The results show that the MPC can be successfully tuned to follow an existing linear control law and to comply with both input and state constraints, such as actuator force and actuator stroke.

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