Abstract:

The transition toward carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitters: electricity and transportation. The transition to a carbon-neutral electric grid poses significant challenges to conventional paradigms of modern grid planning and operation. Much of the challenge arises from the scale of the decision-making and the uncertainty associated with the energy supply and demand. Artificial intelligence (AI) could potentially have a transformative impact on accelerating the speed and scale of carbon-neutral transition, as many decision-making processes in the power grid can be cast as classic, though challenging, machine learning tasks. We point out that to amplify AI’s impact on carbon-neutral transition of the electric energy systems, the AI algorithms originally developed for other applications should be tailored in three layers of technology, markets, and policy.

Bio:

Dr. Le Xie is the Gordon McKay Professor of Electrical Engineering at Harvard John A. Paulson School Of Engineering And Applied Sciences. He received B.E. in Electrical Engineering from Tsinghua University in 2004, S.M. in Engineering Sciences from Harvard in 2005, and Ph.D. in Electrical and Computer Engineering from Carnegie Mellon in 2009. He was on the faculty of Texas A&M from 2010 to 2024. His industry experience includes work at ISO-New England and Edison Mission Energy Marketing and Trading. His research interest includes modeling and control in data-rich large-scale systems, grid integration of clean energy resources, and electricity markets.

Dr. Xie is a Fellow of IEEE, IEEE PES Distinguished Lecturer, and recipient of several prestigious awards, including the NSF CAREER Award, the 2021 IEEE Technical Committee on Cyber-Physical Systems Mid-Career Award, and the 2017 IEEE PES Outstanding Young Engineer Award. He was the recipient of Texas A&M Dean of Engineering Excellence Award, ECE Outstanding Professor Award, and TEES Select Young Fellow. He serves or have served on the Editorial Board of IEEE Transactions on Power Systems (Senior Editor), IEEE Transactions on Smart Grid, and IET Transaction on Smart Grid. He is the founding chair of IEEE PES Subcommittee on Big Data & Analytics for Grid Operations. His team received the IEEE PES Technical Committee Prize Paper award, and multiple Best Paper awards at North American Power Symposium 2012, IEEE SmartGridComm 2013, HICSS 2019 and 2021, IEEE Sustainable Power & Energy Conference 2019, and IEEE PES General Meeting 2020/2023.