Special Session 15: Machine Learning in offshore wind

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Organizers:

Dr. Cian Desmond, Gavin & Doherty Geosolutions (GDG)

Dr. Louis Marin Lapastoure, Gavin & Doherty Geosolutions (GDG)

Prof. David Igoe, Trinity College Dublin

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Description:

Machine learning has become hugely popular in offshore wind over the last half a decade. This trend has been driven by the large amount of data available, access computational power, advances in machine learning techniques and increasing pressure to optimise the design and operations of offshore assets. Wind turbines – their foundations, and blades for instance are constantly monitored through SCADA systems whilst the structure of the atmosphere is constantly monitored by remote and in-situ sensors. This large availability of data has allowed for the development of data-driven artificial intelligence (AI). AI based methods provide the opportunity to reduce the design and operational costs and deploy economic solutions. In the design phase of offshore wind farms, AI allows for the computationally efficient analysis for design optimization. In the operational phase, AI makes use of digital twins for predictive maintenance, increasing operational efficiency and safety.

 

In this session, a series of presentations will provide an overview of the state of the are in the use of ML in the design and operation of offshore wind farms. Topics will include geotechnical measurement and modelling, metocean, O+M optimisation and end of life decision making. 

 

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