Large Language Models (LLMs) as chatbots have drawn remarkable attention thanks to their versatile capability in natural language processing as well as in a wide range of tasks. While there has been great enthusiasm towards adopting such foundational model-based artificial intelligence tools in all sectors possible, the capabilities and limitations of such LLMs in improving the operation of the electric energy sector need to be explored, and this talk identifies fruitful directions in this regard. Key future research directions include data collection systems for fine-tuning LLMs, embedding power system-specific tools in the LLMs, and retrieval augmented generation (RAG)-based knowledge pool to improve the quality of LLM responses and LLMs in safety-critical use cases.
Reference:
Subir Majumder, Lin Dong, et. al., Exploring the Capabilities and Limitations of Large Language Models in the Electric Energy Sector,” Joule (accepted, to appear).
The webinar was held on Zoom at 3 p.m. CDT on June 18, 2024
The presentation slides are posted here. The video recording is posted here.
Presenter
Le Xie, Ph.D., is the Segers Family Dean’s Excellence Professor, Chancellor EDGES Fellow, and Presidential Impact Fellow in the Department of Electrical and Computer Engineering at Texas A&M University, and the Associate Director-Energy Digitization at Texas A&M Energy Institute. 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. His industry experience includes 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 and a Power and Energy Society (PES) Distinguished Lecturer. He received the National Science Foundation CAREER Award, and Oak Ridge Ralph E. Powe Junior Faculty Enhancement Award. He was awarded the 2021 IEEE Technical Committee on Cyber-Physical Systems Mid-Career Award, and 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, 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 PES AMPS Technical Committee Prize Paper 2023, 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.
More on Dr. Xie’s research can be viewed here.