Enhancing power system resilience to extreme events
Jin Zhao (赵瑾)
Jin Zhao is an Assistant Professor at Trinity College Dublin. She is the Alexander von Humboldt Research Fellow of Germany hosted by IE3 TU Dortmund University. She was a Research Scientist at The University of Tennessee (UTK), USA. She received the B.E. and Ph.D. degrees from Shandong University, Jinan, China, all in Electrical Engineering, in 2015 and 2020, respectively. She was an outstanding reviewer of several IEEE Trans. journals. She is an associate editor of IET Generation, Transmission & Distribution. She is the chair of IEEE Task Force AISR. Her research interests include power system resilience, transmission and distribution system restoration, optimal operation of highly renewable energy integrated systems, resilient micro-grids and machine learning.
Research interests
Power System Resilience, Renewable Energy based Electricity, Transmission/Distribution System Restoration, Distributed/Decentralized Optimization, Microgrids, Deep Learning, and Reinforcement Learning.
Publications
Click here for my publications : )
Recent academic activities
Chair, IEEE Task Force: Advanced Artificial Intelligence for Resilient Power System Restoration (AISR).
Please check AISR for details. Welcome to join!
Chair (incoming), 07.2024, Seattle, USA, IEEE PES General Meeting, Panel Session on 'Realizable Machine Learning in Resilient Power Grids: from lab developments to industrial applications'.
Steering Committee(PES rep), 03.2024-, IEEE DataPort.
Keynote, 11.2023, IEEE PES YP, 'Microgrid Solutions for Resilience and Sustainability'.
Panelist, 07.2023, Orlando, USA, IEEE PES General Meeting, Panel Session on 'Exploring Feasibility of Machine Learning for Grid Resilience Assessment'.
Presenter, 04.2023, Postdam, Germany, Potsdam Institute for Climate Impact Research, Panel Session on 'Machine Learning Supported High RES Penetrated Power Systems -- Actions to Defend Extreme Weather'.
Co-chair, 07.2022, Denver, USA, IEEE PES General Meeting, Panel Session on 'Machine Learning for Power System Decision-making'.
Members, IEEE Power and Energy Society, IEEE working group on Machine Learning and Power Systems, IEEE working group on Power System Restoration.
Contact information
Email: zhaoj6@tcd.ie/jzhao44@utk.edu