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TALOS Wave Energy Converter Power Output Prediction Analysis Based on a Machine Learning Approach

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Published
Article numberISOPE-24-34-3-306
<mark>Journal publication date</mark>9/09/2024
<mark>Journal</mark>International Journal of Offshore and Polar Engineering
Issue number3
Volume34
Number of pages8
Pages (from-to)306–313
Publication StatusPublished
<mark>Original language</mark>English

Abstract

Wave energy shows potential to provide electricity in a renewable manner. The TALOS WEC (Wave Energy Converter) is a unique design with six PTO (Power Take-Off) elements to provide six degrees of freedom (DOFs). It is potentially able to harvest energy more efficiently than traditional single-DOF devices. As a step towards its optimisation and control, a power prediction model is developed, using the wave elevation and motions of the WEC to predict the power output of each PTO. The results show that using LSTM (Long-Short Term Memory) has a higher prediction accuracy than the other approaches considered.