Wednesday, April 29, 2026

2024 U.S. Data Center Energy Usage Report from LBL

Shehabi, A., Smith, S.J., Hubbard, A., Newkirk, A., Lei, N., Siddik, M.A.B., Holecek, B., Koomey, J., Masanet, E., Sartor, D. 2024. 2024 United States Data Center Energy Usage Report. Lawrence Berkeley National Laboratory, Berkeley, California. LBNL-2001637

2024 United States Data Center Energy Usage Report

Our local supervisors here in Prince William County, and our neighboring counties have been approving data centers without any plan. Loudoun County and Prince William, VA, have used "lenient" approvals to build a massive tax base that funds schools, social services, local government, and parks without that could not have been afforded without massive property tax increases. The need for high-capacity transmission lines and additional transmission has forced a reactive and haphazard response to the demands for power and other infrastructure.  We need to look at and plan for what is happening- the creation of a regional data center hub of global proportions.

About a year and a half ago the Lawrence Berkeley National Laboratory (LBL) issued a very important report, for planning infrastructure and the future of our nation. The article below is excerpted from that report cited above.

The Energy Act of 2020 called for an update to Lawrence Berkeley National Laboratory’s prior study entitled United States Data Center Energy Usage Report (2016). This report estimates historical data center electricity consumption back to 2014, relying on previous studies and historical data. This report also provides a forecasted range of future demand out to 2028 based on trends and the most recent available data. The figure below provides an estimate of total U.S. data center electricity use including servers, storage, network equipment, and infrastructure from 2014 through 2028.

U.S. data center annual energy use remained stable between 2014–2016 at about 60 TWh, continuing a minimal growth trend observed since about 2010. In 2017, the overall server installed base started growing and Graphic Processing Unit (GPU)-accelerated servers for artificial intelligence (AI) became a significant enough portion of the data center server stock that total data center electricity use began to increase. By 2018 data centers consumed about 76 TWh, representing 1.9% of total U.S. electricity consumption.

from LBL
 Since 2017 U.S. data center energy use has continued to grow at an accelerating rate, reaching 176 TWh by 2023, representing 4.4% of total U.S. electricity consumption. Lawrence Berkeley National Laboratory went on to forecast total data center energy use after 2023. It is presented as a range of the various scenarios of future equipment shipments and operational practices, as well as variations in cooling technology. There is a tradeoff between water use and energy use for cooling.

Cooling systems, such as shifting to liquid base cooling or moving away from evaporative
cooling determine a significant portion of energy use. Together, the scenario variations provide a range of total data center energy estimates, with the low and high end of roughly 325 and 580 TWh in 2028, as shown above.

Assuming an average capacity utilization rate of 50%, this annual energy use range would
translate to a total power demand for data centers between 74 and 132 GW. This annual
energy use also represents 6.7% to 12.0% of total U.S. electricity consumption forecasted for 2028.

Historically, data center electricity use increased substantially from 2000–2005, roughly
doubling during that period. During the early and mid-2010s, a shift from on-premises data
centers to colocation or cloud facilities helped enable efficiency improvements that allowed data center electricity use to remain nearly constant at a time when the data center industry grew significantly. During this period, improved cooling and power management, increased server utilization rates, increased computational efficiencies, and reduced server idle power allowed growth without increased energy use.

While many of these efficiency strategies continue to provide significant energy efficiency improvements, the expansion of data center services and new types of hardware has ended the era of generally flat data center energy use. The rapid growth in accelerated servers has caused current total data center energy demand to more than double between 2017 and 2023, and continued growth in the use of accelerated servers for AI services could cause further substantial increases by the end of this decade.

The current and possible near-future surge in energy demand highlights the need for future research to understand the early-stage, rapidly changing AI segment of the data center industry and identify new efficiency strategies to minimize the resource impacts of this growing and increasingly significant sector in our economy. The estimates in their report are based on a “bottom-up” energy use that calculates total electricity use from an installed base of data center equipment.

The lack of direct energy data available in a sector with rapidly evolving technologies limits the analysis. The results of the study with all its limitations indicate that the electricity consumption of U.S. data centers is currently growing at an accelerating rate. The compound annual growth rate was approximately 7% from 2014 to 2018, increasing to 18% between 2018 and 2023. Lawrence Berkeley National Laboratory estimates that the growth rate will range from 13% to 27% between 2023 and 2028. Many of those projects are already under construction and the GPUs ordered.

This surge in data center electricity demand needs to be understood in the context of the much larger national electricity demand that is expected to occur over the next few decades as our nation experiences a combination of electric vehicle adoption, onshoring of manufacturing, hydrogen utilization, and the electrification of industry and buildings. We as a nation need to meet data centers’ future energy needs, but also an economy-wide expansion of electricity infrastructure to meet all future needs.

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