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Webinar Series 2020/21: Using machine learning to represent power system dynamics
10.12.2020
Our series of webinars focussing on the research of our seven flex funded projects which were awarded in 2019 has now concluded.
All webinar sessions are available to view on our YouTube channel.
If you have any questions or queries please contact Lindsey Allen, Research Project Coordinator.
10 December: Using machine learning to represent power system dynamics
10 December: Using machine learning to represent power system dynamics
(14:00 – 15:00)
Speaker: Panos Papadopoulos (University of Strathclyde)
The session is available to view.
Project Summary
The ever increasing integration of variable output renewable energy sources (mainly wind and solar) as well as various other power electronic interfaced devices (e.g. electric vehicles, HVDC interconnectors, potentially battery storage, heat pumps, etc.) to achieve decarbonisation targets, significantly increases the uncertainty and complexity in the dynamic behaviour of electrical power systems. Machine learning has shown great potential in dealing with complex nonlinear systems in various domains. This project envisions bringing together the artificial intelligence and power engineering research communities to work on the very computationally demanding and complex problem of representing the power system dynamic behaviour.
Further information on the project is available.
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