Google advanced one of its initiatives Monday to address the burgeoning demand for energy by its data centers, driven by power-hungry artificial intelligence applications.
The company announced agreements with Indiana Michigan Power and the Tennessee Valley Authority to throttle energy demand from machine learning workloads at its data centers in those regions.
“This builds on our successful demonstration with Omaha Public Power District (OPPD), where we reduced the power demand associated with ML workloads during three grid events last year,” Michael Terrell, Google’s head of advanced energy, explained in a company blog.
Google began managing grid demand at its data centers by shifting non-urgent computing tasks — like processing a YouTube video — during specific periods when the grid is strained. Through its partnerships, it leveraged those demand management capabilities to help grid operators maintain reliability during peak demand periods.
“As AI adoption accelerates, we see a significant opportunity to expand our demand response toolkit, develop capabilities specifically for ML workloads, and leverage them to manage large new energy loads,” Terrell wrote. “By including load flexibility in our overall energy plan, we can manage AI-driven growth even where power generation and transmission are constrained.”
Pete DiSanto, senior vice president of data centers at Enchanted Rock, an electrical resiliency-as-a-service company in Houston, added, “Demand-side solutions are absolutely critical for aligning growth with grid reliability.”
“Without demand-side solutions, the grid simply won’t be able to keep up with the scale and speed of AI data center growth, especially in regions already facing capacity and interconnection challenges,” he told TechNewsWorld. “These tools are the key to enabling rapid expansion without breaking the grid.”
AI Strains U.S. Power Capacity
Demand-side power management solutions are expected to play a crucial role in meeting the growing electricity demands of data centers driven by AI in the coming years. According to Morningstar Research Services, U.S. data center power capacity is expected to approximately triple to 80 gigawatts by 2030, driven by the growth of data centers utilizing generative artificial intelligence.
However, Morningstar acknowledges that its projections are less bullish than those of other prognosticators, which see capacity reaching 100 gigawatts during the same period. “We believe such forecasts overlook the practical limitations associated with building large-scale infrastructure and also underestimate the long-term rising energy efficiency of AI chips,” it noted in a report titled “Powering Tomorrow’s AI Data Center” released in July.
“We don’t have sufficient generating capacity for both the existing energy loads and AI data centers,” said Rob Enderle, president and principal analyst with the Enderle Group, an advisory services firm in Bend, Ore.