Wave energy has great potential as a renewable energy source, and can therefore contribute significantly to the proportion of renewable energy in the global energy mix. This is especially important since energy mixes with high renewable penetration have become a worldwide priority. One solution to facilitate such goals is to harvest the latent untapped energy of the ocean waves and convert it into electrical energy. A device performing such a task is known as a wave energy converter (WEC). In the present work, we focus on a specific type of WEC, which has the advantages of both significant energy storage capabilities, and adaptability to extract energy from the whole spectrum of ocean waves. This WEC consists of an array of point absorber devices, comprising adaptable piston-type hydraulic pumps powered by interconnected floaters, whose target is to extract optimally the energy from waves of varying heights and periods. Two different cases are considered in this paper; namely, the analysis of the energy extraction in a simplified floater blanket, and a model predictive control strategy to maximize the extracted energy of the WEC.
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In this work, a frequency-domain method for the numerical solution of the nonlinear dynamics of a wave energy converter with a pumping system is presented. To this end, a finite Fourier series is used to describe the nonlinear force components, i.e., the pumping force. The dynamics of the buoy and the piston are obtained by solving a set of linear motion equations. The numerical model is validated by comparing it with experimental results. The dynamic characteristics of the pumping system are investigated by performing a series of numerical simulations for several approximation orders under various wave conditions. The advantages and limitations of this method are also discussed in the paper. This work provides great insight into the mechanism of a WEC with a pumping unit under various sea states, which can guide the design of a multi-piston pump (MPP) system. This model will be applied to investigate the optimal configuration for the MPP system in the future.
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