Data Center, AI and the impact on the electricity market

Data center operation is one of the fastest growing industries worldwide. The International Energy Agency recently projected that global data center electricity demand will more than double by 2026. In the United States, the national outlook could resemble the global outlook, but is highly uncertain.

One key uncertainty that could change the trajectory of data center load growth is the use of generative AI models. Both public and corporate imaginations were triggered by the release of OpenAI’s ChatGPT on November 30, 2022. Evidence about how widely these tools will be used and how much they will change computational needs is just starting to emerge. These early applications were estimated to require about ten times the electricity—from 0.3 watt-hours for a traditional Google search to 2.9 watt-hours for a ChatGPT query—to respond to user queries. Creation of original music, photos, and videos based upon user prompts and other emerging AI applications could require much more power. With 5.3 billion global internet users, widespread adoption of these tools could potentially lead to a step change in power requirements. On the other hand, history has shown that demand for increased processing has largely been offset by data center efficiency gains.

Drawing on public information about existing data centers, public estimates of industry growth, and recent electricity demand forecasts by industry experts, EPRI prepared four scenarios of potential electricity consumption in U.S. data centers during the period from 2023 to 2030.

According to Goldman Sachs between 2023-2030 the power demand will be 15% CAGR driving data centers to make up 8% of total US power demand by 2030 from about 3% currently.

Fifteen states accounted for an estimated 80% of the national data center load in 2023: Virginia, Texas, California, Illinois, Oregon, Arizona, Iowa, Georgia, Washington, Pennsylvania, New York, New Jersey, Nebraska, North Dakota, and Nevada. Concentration of demand is also evident globally, with the International Energy Agency recently projecting that data centers in Ireland could account for almost one-third of Ireland’s total electricity demand by 2026.

The most serious challenges to data center expansion are local and regional and result from the scale of the centers themselves and mismatches in infrastructure timing. A typical new data center of 100 to 1000 megawatts represents a load equal to that of a new neighborhood of 80,000 to 800,000 average homes. While neighborhoods require many years to plan and build, data centers can be developed and connected to the internet in one to two years. New transmission, in contrast, takes four or more years to plan, permit, and construct. And developing and connecting new generation can also take years. Therefore, expedition of the permitting/approval process for transmission projects will be key to alleviate it.

There are three essential strategies to support rapid data center expansion. These strategies emphasize increased collaboration between data center developers and electric companies:

1.      Improve data center operational efficiency and flexibility - . Although gains in data center operational efficiency have plateaued in recent years, there are clear opportunities for further improvement, including more efficient IT hardware; lower electricity use for cooling, lighting, and security; and more efficient AI development and deployment strategies. Efforts to increase both temporal and spatial (i.e., spreading compute geographically) flexibility are critical to helping accommodate these new loads.

2.      Increase collaboration between data center developers and electric companies - Developing a deeper understanding of data center power needs, timing, and potential flexibilities—while assessing how they match available electric supplies and delivery constraints—can create workable solutions for all. Enabled by technology and supporting policies, data center backup generators, powered by clean fuels, could support a more reliable grid while reducing the cost of data center operation. Shifting the data center-grid relationship from the current “passive load” model to a collaborative “shared energy economy”—with grid resources powering data centers and data center backup resources contributing to grid reliability and flexibility—could not only help electric companies contend with the explosive growth of AI but also contribute to affordability and reliability for all electricity users.

3.      Improve point load forecasting to better anticipate future point load growth and modeling of transient system behavior to maintain reliability - Forecasts need to make better projections describing new point load locations, magnitudes, and timing alongside better techniques for making decisions—to build or not build long lead-time infrastructure—while facing the economic, regulatory, and political uncertainty associated with siting these large point loads. Also, real-time modeling of data center operational characteristics in an increasingly inverter-based grid is needed to maintain reliability.