# Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements
## 1 Introduction
The Oscillating Water Columns (OWC) are widely deployed wave energy converters thanks to their simplicity and feasibility. Nevertheless, OWC devices using Wells turbine-based PTO systems withstand a hindrance in power generation caused by the stalling phenomenon that affects the Wells turbine's aerodynamic efficiency resulting into a reduced energy extraction [10; 11]. Many scientists and research groups have studied and investigated the effects of the stalling phenomenon in Wells turbine and how to reduce its impact on the produced power. [PERSON] et al. worked on the stall effect of Wells turbine and performed many analyses from numerical and experimental data. In [12] they used detailed CFD to investigate the flow-field through the turbine blades to offer a description of the complex flow mechanism that originates separation and, consequently, low efficiency at high flowrates by solving the Reynolds-averaged Navier-Stokes equations together with three turbulence models. In addition, in [13] they investigated a 3D-printed Wells turbine in the open wind tunnel of the Polytechnic University of Bari. The scaled prototype was designed to operate in a 1:10 scaled model of a REWEC3 breakwater for ocean application and was tested under steady-state and pulsating flow conditions. Obtained results indicated that when the turbine experiences large sinusoidal variations of the flow coefficient at high mass flow rates, a delayed onset of stall can be observed and that the variation of the turbine performance under dynamic flow conditions is crucial for a correct design of the Wells turbine. [PERSON] et al. investigated in [14] the dynamic interaction between the OWC and the Wells turbine. In this work, a lumped parameter model has been introduced and compared to experimental and CFD data. The proposed lumped parameter model allows rapid isolation of parameters with the largest influence on system performance and could be integrated with existing wave-to-wire models to improve the understanding of the hydrodynamic/aerodynamic interaction in the overall system. [PERSON] et al. investigated in [15] the possibility of enhancing the Wells turbine performance by using water as the working fluid rather than air by submerging the Wells turbine in the sea water. For this CFD simulations were performed using the steady 3D incompressible Reynolds-Averaged Navier-Stokes (RANS) calculations on this type of axial turbine rotor with realizable \(k\)-\(\varepsilon\) turbulence model. Also, from a control point of view, [PERSON] et al. proposed in [16] a real-time sliding mode control for a wave energy converter based on a Wells turbine using Lyapunov stability theory to analyze its stability. The proposed control is tested first by meansof simulations using MATLAB/Simulink and then using a real-time experimental platform based on a dSPACE DS1103 control board. The present manuscript introduces the OWC's model and proposes a rotational speed control. The propose of the rotational speed control is to help the turbo-generator evade the stalling behavior which will increase the power generation. For this purpose, an ANN-based rotational speed control has been developed and implemented with the intention to control the back-to-back (BTB) converter connected to a Doubly Fed Induction Generator (DFIG). This will allow the regulation of the rotational speed by considering the wave input and predicting the optimal rotational speed via an Artificial Neural Network (ANN)-based Maximum Power Point Tracking (MPPT). The designed network has been trained using measured wave data from the harbor of Mutriku by means of an Acoustic Doppler Current Profiler (ADCP) and its capabilities have been adopted to recognize the incoming strong waves causing the stall effect and generate the suitable reference value of the desired rotational speed for the proposed rotational speed control scheme.