IEEE opens a five-module course on running grids with AI

Developed by the University of Tennessee's Fangxing Li, it covers reinforcement-learning grid control, forecasting and physics-informed AI. No price is published.

IEEE Educational Activities, with the IEEE Power & Energy Society, has published a course called Artificial Intelligence for Power and Energy Systems. It was developed by Professor Fangxing "Fran" Li of the University of Tennessee in Knoxville, who chairs the IEEE Working Group on Machine Learning for Power Systems. Five modules cover AI fundamentals for grids, deep reinforcement learning for grid control, forecasting and data analytics, physics-informed and safe AI, and generative AI.

The framing statistic IEEE uses is the one this feed has been tracking all week: 220 gigawatts of new connection requests at Texas's largest transmission utility, driven largely by AI and cloud facilities, per CNBC. The course is aimed at power system engineers, utility managers and data scientists.

This is a training product, not a research result or a deployment, and it is scored accordingly. No course length and no price appear on the page; individuals are pointed at the IEEE Learning Network and organisations are told to ask about volume pricing. That matters for a site that measures whether things get cheaper: an unpriced course cannot be put on a curve. What it does mark is a real second-order effect worth watching, which is that grid operation is becoming a skill that has to be retaught, and the professional bodies have started doing it.

Source: IEEE Spectrum