Dr. Kyri Baker on AI & OPF
Professor Baker describes a hybrid approach to solving power grid optimization that may provide better dispatch solutions faster, plus how micro-dosing on AI could lead to running the grid on a laptop
Dr. Kyri Baker, an assistant professor of engineering at the University of Colorado, makes a return visit to discuss the use of artificial intelligence for power grid optimization. Plus, Conleigh Byers, Farhad Billimoria, Ahlmahz Negash, and Paul Dockery wrap the interview with an explanation of AI and all its acronyms.
photo credit Carl Bower for The New York Times
You can find the podcast on Apple Podcast, Spotify, or wherever you get your podcasts. Share with friends that are energy enthusiasts, like us!
01:31 - 30 second theory
Farhad Billimoria on “What is OPF?”
Conleigh Byers on “What’s the difference between artificial intelligence (AI), machine learning (ML), Deep Learning, Physics Informed Neural Networks (PINN), Large Language Models (LLM), generative AI, and general intelligence?”
14:20 - Dr. Kyri Baker: Using AI and Machine Learning for Power Grid Optimization
Baker, Kyri. "Emulating ac opf solvers with neural networks." IEEE Transactions on Power Systems 37.6 (2022): 4950-4953.
Baker, Kyri, and Harsha Gangammanavar. "Locational Marginal Prices Obey DC Circuit Laws." arXiv preprint arXiv:2403.19032 (2024).
1:05:53 - Updating our Priors
Chatzivasileiadis, Spyros, et al. "Machine learning in power systems: Is it time to trust it?." IEEE Power and Energy Magazine 20.3 (2022): 32-41.
1:25:56 - ESA (Energy System Analogies) World Cup Standings
Public Power Underground, for electric utility enthusiasts! Public Power Underground, it’s work to watch!