Will Energy-Hungry AI Create a Baseload Power Demand Boom?
Jonas Kristiansen Nøland, Martin Hjelmeland, Magnus Korpås
Abstract
The rapid expansion of generative artificial intelligence (AI) technologies is projected to significantly affect electricity use in the global data center sector. Earlier research has proposed using data centers for load-balancing the future power grid to allow higher integration of variable renewables. In this paper, we review the expected future electricity consumption of AI and evaluate the behavior of AI data centers in clean energy systems. Our work found that the levelized cost of computing (LCOC) favors higher load factors and shows a relatively low sensitivity to electricity price levels. Under our baseline cost assumptions, a baseload electricity price of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\$} {\mathrm {125~}} \mathrm {/MWh}$ </tex-math></inline-formula> benefits load factors higher than 64 %, depending on the market price conditions and variations. Nevertheless, high-tier data centers with higher operational costs and capital expenditures favor even higher load factors to optimize their LCOC. These findings show that a boom in AI energy use could drive significant baseload power demand in future power systems.