Sponsor: Foothill Section, Foothill Section Chapter, PE31
Speaker: Dr. Panagiotis Papadopoulos of The University of Manchester (UK)

Date: 16 Jun 2025
Time: 11:00 AM PDT to 12:00 PM PDT
Cost:
Location:
Reservations: IEEE
Summary:
Electrical power systems are undergoing unprecedented changes, mainly driven by decarbonisation targets and climate change, as well as other technical, economic, and social reasons. This leads to the integration of new technologies such as renewable generation, electric vehicles, HVDC links, etc. These devices are mostly connected via power electronics with very different dynamic behaviour, leading to increasing complexity of power system dynamics. In addition, uncertainty is also increasing due to the intermittent nature of renewable generation, but also because of how society will use energy on the way to decarbonization (e.g., electrification of transport or possibly heating). At the same time, advanced measurement and communication infrastructure are being integrated into modern power systems. Such technologies, especially coupled with machine learning, offer opportunities for advanced situational awareness, decision support tools, and automated control methods.

This presentation will highlight the challenges faced in future power systems with high penetration of converter-connected units, in terms of their dynamic behaviour, and discuss methods and tools to tackle them. The talk will mainly address the question of how we characterize the complex and uncertain dynamic behaviour in power systems with high converter penetration, and how this can be affected by different control structures. Probabilistic stability assessment methods to quantify the impact and characterize new types of oscillatory interactions of power systems with converter-connected units will be discussed, including the behaviour of oscillations in the sub-synchronous range. In addition, a view on how to define system strength associated with small-signal dynamics will also be discussed.

Bio: Dr. Panagiotis Papadopoulos is a Reader (Associate Prof.) in the Department of Electrical and Electronic Engineering at the University of Manchester and a UK Research and Innovation Future Leaders Fellow working on “Addressing the complexity of future power system dynamic behaviour”. He received the Dipl. Eng. and Ph.D. degrees from the Department of Electrical and Computer Engineering at Aristotle University of Thessaloniki, in 2007 and 2014, respectively. From 2014-2017, he was a post-doctoral Research Associate at the University of Manchester and in 2017, he joined the University of Strathclyde as a Lecturer.

His research interests are in the area of power system stability and dynamics under increased uncertainty, introduced due to the integration of new technologies. He is also interested in power system applications of machine learning to tackle complex problems related to power system stability.

He has authored more than 80 papers in international journals and conferences. He is the Technical Committee Program Chair of the Power System Dynamic Performance Committee of IEEE Power and Energy Society and has also been a member of the IEEE PES Long Range Planning Committee, the chair of the IEEE UK and Ireland, PES chapter and a member of the IET Engineering Policy Group Scotland. He also received the Outstanding Engineer Award in 2021 from IEEE Power and Energy Society, UK and Ireland Chapter. He is currently a member of the IEEE Big Data Analytics Working Group and has been a member of the CIGRE C2.42 Working Group related to applications of machine learning in power systems.

He has also worked in collaboration with industrial partners, including National Grid Electricity System Operator UK, SP Energy Networks, SSE, Scottish Power Renewables, Hitachi Energy, EPRI USA, IBM, GE Grid Solutions and the Alan Turing Institute in the UK.