AI's Hidden Cost to the Grid: Good Science, Bad Science
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AI's Hidden Cost to the Grid: Good Science, Bad Science
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In this Good Science, Bad Science episode of The Atomic Exchange Podcast, Dr. Goran Calic and Jennifer Ward examine "The Role of Nuclear Energy Base Load Demand in Capacity Expansion Planning for Low-Carbon Power Systems," a paper exploring how AI data centers' constant, always-on energy demand could reshape future nuclear buildout. They break down the paper's modeling of how nuclear penetration in Europe depends heavily on construction costs, comparing it against real-world reactor projects from France to China. The conversation dives into the hidden cost of renewable variability, including price cannibalization and the expensive complements needed to keep grids stable, and why these factors rarely show up in standard levelized cost of energy models.