Fuzzy Gain Scheduled PI-Based Airflow Control of an Oscillating Water Column in Wave Power Generation Plants

Numerous control schemes have been proposed to reach a more efficient power generation using Wells-turbine-based oscillating-water-column power plants. Most of these control strategies aim to avoid the stalling behavior, a feature of the Wells turbine, that limits the generated power. Besides, the plant must be able to maintain its performance despite the input variations due to the intrinsic oscillating nature of the waves and constant climate changes. This paper deals with the modeling and control of the NEREIDA wave power plant installed in the breakwater of Mutriku in the Basque Coast of Spain. In this context, the design of a novel fuzzy gain scheduled proportional integral (FGS-PI) controller is presented to improve the input airflow control. The fuzzy supervisor adequately changes the controller gains to offer the control scheme an adaptive mechanism against input parameter changes. Two study cases were performed to compare the FGS-PI to a conventional PI. The first test is for the output power optimization and the second is to test the robustness against parameter changes. Results show the superior performance of the proposed control providing power generation improvement and higher robustness even with varying input conditions.