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Performance Optimization of a Hybrid Offshore Wind-Wave Energy Platform

CORDIS · observation · Publication date unknown

he stabilization of the FOWT using the OWCs as an active structural control. The OWCs will be integrated into the floating barge platform which has not been investigated in previous research works. A Machine Learning-based control strategy will be developed to control all the Power Take-Off systems of the OWCs at once. The control of multiple OWCs on a single FOWT requires an adequate strategy that takes into account not only the plants state variables but external environmental conditions as well (wind speed, wave speed, wave heights, etc). The consideration of this external data motivates the use of a Machine Learning (ML) module for the estimation and prediction problems. An ML module will help in the prediction of future wind and wave speeds and estimate the proper reference input value of the designed controllers. Many research works using ML for FOWTs have been published and proved that ML is a promising solution. Automatic control, Control design, Floating Offshore Wind Turbine, Machine Learning, Oscillating Water Column, Platform stabilization, Fore-aft and Side-to-side displ

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recordType

award

status

SIGNED

region

EU

value

252724.32

unit

EUR