Machine Learning-based OWC Diagnosis Using Real Measured Data from Wave Power Plants

The present manuscript introduces a classification for power take-off (PTO) diagnosis in Wave Energy Converter (WEC) farms. The suggested strategy has been tested on the Mutriku Multiple Oscillating Water Column-based wave power plant in order to reduce the Levelized Cost of Energy (LCoE) by implementing predictive maintenance strategies. This has been achieved by employing Linear Discriminant Analysis (LDA) to determine the furthermost relevant features from the measured data. Then the Support Vector Machine (SVM) has been implemented as a classification technique to classify the state of the OWC system.