Model predictive control based on air pressure forecasting of OWC wave power plants.

Ocean waves hold a promising potential as a sustainable source of clean energy. However, in order to make wave energy converters financially viable, particularly in the case of the oscillating water column (OWC), it is crucial to optimize the power take-off system to maximize performance. Most control strategies focus solely on turbine performance, often at the expense of overlooking the overall wave-to-wire system performance. Therefore, a model predictive control (MPC) strategy using short-term air pressure prediction was proposed to enhance electrical energy delivered to the grid. The Mutriku wave power plant (Spain) was case-studied for evaluating the control approaches, which focused on maximizing average power (turbine or generator) from an OWC equipped with the innovative biradial turbine. In comparison to the reference baseline strategy, the implementation of MPC (with a 16-second forecast) resulted in a minor 2%-increase in the average turbine power. However, when it comes to the generator power accumulated over a year, the MPC strategy produced an improvement of more than 8%. Since generator power is the ultimate product, this improvement is significant. Nonetheless, the MPC strategy exhibited a non-smooth control response compared to other strategies. Improving control action quality should be a primary focus of future research. • A model predictive control was proposed for an oscillating-water-column power plant. • Short-term air pressure forecasting was performed using an autoregressive model. • The proposed algorithm was applied to the Mutriku wave power plant. • Improvements in the annual average generator power output of over 8% were observed. [ABSTRACT FROM AUTHOR]