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02/05/2025 - Value in energy data | AIOLUS - an intelligent wind farm management system

AIOLUS, named after Artificial Intelligence (AI) and Aeolus, the Greek god of wind, is a groundbreaking wind farm management system designed to make wind energy smarter and more efficient. As the world accelerates towards clean energy and Net Zero goals, AIOLUS provides a novel solution by optimising the performance of wind farms.

By developing and leveraging cutting-edge AI techniques in wind farm control and management, AIOLUS aims to boost wind farm annual energy production by at least 5%.

In this webinar, you will learn more about AIOLUS which offers a scalable and cost-effective way to enhance production and minimise the need for new land and offshore developments. By unlocking the full potential of wind energy, AIOLUS is paving the way for a cleaner and more sustainable future.

AIOLUS - an intelligent wind farm management system

Calendar

Wednesday 2 April 2025

Clock

12pm

Map Pin

Online

Duration: 1 hr

Register now

Speakers

Professor Xiaowei Zhao, Professor of Control Engineering, University of Warwick.
Xiaowei is the director of the EPSRC Supergen Network PLUS in Artificial Intelligence for Renewable Energy and a co-director of the EPSRC Supergen Offshore Renewable Energy Hub.
Xiaowei obtained his PhD in Control Theory from Imperial College London in 2010 and then worked as a postdoctoral researcher at the University of Oxford until 2013. After that he joined the University of Warwick where he was awarded a chair in 2018. At Warwick he established the Intelligent Control & Smart Energy (ICSE) research group and four state-of-the-art laboratories.
Dr Hongyang Dong, Assistant Professor, University of Warwick
His research focuses on control theory and machine learning methods, with applications in complex systems such as offshore renewable energy and autonomous systems. He has published over 40 papers in these fields, including 18 in IEEE Transactions journals. One of his recent core research efforts centres on AI-powered wind farm control, where he develops reinforcement learning algorithms to significantly enhance overall wind farm efficiency.

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