IEEE Launches Course to Modernize Power Grids with AI
IEEE
The U.S. electrical grid is under strain from rising demand and renewable energy volatility. IEEE has launched an online course program to teach engineers and data scientists how to apply AI for grid modernization, covering topics like forecasting, grid control, and safe AI deployment.
The U.S. electrical grid, among the largest and most complex systems ever built, is operating at its limit due to rapid industrial growth, extreme weather, and a surge in electricity use, partly from data centers. The grid faces pressure from both a spike in demand and the shift to weather-dependent renewable energy, requiring second-by-second balancing to prevent blackouts. To address physical and digital vulnerabilities, including cyberattacks and severe weather disruptions, grid reliability organizations emphasize the need for a smarter, automated grid. AI is seen as a baseline operational necessity, capable of processing vast data instantly and enabling predictive maintenance, which McKinsey studies suggest could reduce equipment downtime by up to 50% and extend machinery lifespan by 40%. To bridge the gap between AI research and practical field deployment, IEEE Educational Activities, in partnership with the IEEE Power & Energy Society, has launched the online Artificial Intelligence for Power and Energy Systems course program, developed by Fangxing Li, a professor at the University of Tennessee. The program includes five modules: AI fundamentals, accelerating grid control with deep reinforcement learning, forecasting and data analytics, physics-informed and safe AI, and generative AI and next-generation tech. These modules aim to educate power system engineers, utility managers, and data scientists in modernizing the grid.
Source: IEEE Spectrum AI —
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