Abstract
Wave energy has the potential to become a significant contributor to the future seawater desalination thanks to its high-power density. However, the intermittent characteristics of wave energy are the main issues to be overcome in the seawater desalination process. In this paper, a spiral wave energy converter (WEC) powered desalination system is proposed by utilizing a bottom flanged pitching spiral pump based WEC to directly convert the pressurized seawater into freshwater. The dynamic model of the spiral WEC powered desalination system is established. In order to mitigate the uncertainties and fluctuations in the fresh water supply, a deep reinforcement learning (DRL) control of the WEC is also designed for smoothing freshwater production, and a prioritized experience replay mechanism is employed for improving training efficiency. The test results indicate that the freshwater flowrate can be maintained at the desired value of 1200 m3/day by using the trained DRL control and the DRL training process converges to the stable value of around −18.
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