The Clean Energy Gap: Quantifying the Feasibility of 100% U.S. Clean Energy Consumption by 2035 under Artificial Intelligence-Driven Demand Growth

This paper investigates whether the U.S. can achieve 100% carbon pollution-free electricity consumption by the year 2035 in the context of rapidly accelerating electricity demand driven by artificial intelligence and data center expansion. Employing a compound annual growth rate methodology, this paper uses 2024 figures to model the growth of both the supply and demand sides of U.S. electricity through 2035.

On the demand side, data center demand is projected using historically derived compound annual growth rates (“CAGR”) of 15.77%, while non-data center demands use the Energy Information Administration’s (“EIA”) baseline of 1.7% growth rate, yielding a total electricity consumption range of 5471 terawatt hours (“TWh”) to 5821 TWh by 2035. On the supply side, clean energy capacity is projected to reach a total of 1066.1 gigawatts (“GW”) by 2035 using a CAGR of 7.30%, yielding an estimated generation of 4104 TWh. This falls short of demand estimates with a gap between 1366 TWh and 1716 TWh, with only 70.5% to 75.0% demand covered by clean electricity supply. Closing the gap requires total annual capacity additions of 72 to 91 gigawatts, less than double the current rates. Under current trajectories, clean energy generation is not projected to fully meet total demand until approximately 2042. Under the assumptions and growth trajectories modeled in this paper, the United States is not projected to achieve 100% clean electricity consumption by 2035, and closing the supply gap implies trillion-dollar capital requirements that current markets and situations are unlikely to support.