Harnessing AI for Power Grid Optimization

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.

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01:19 - 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?”

14:28 - Dr. Kyri Baker: Using AI and Machine Learning for Power Grid Optimization

• Using AI and Machine Learning for Power Grid Optimization: How Neural Networks Can Speed Up Optimal Power Flow
• 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).

1:06:14 - 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. APA

1:23:26 - ESA (Energy System Analogies) World Cup Standings

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photo credit Carl Bower for The New York Times

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