Google on Aug. 4 unveiled two new utility agreements with Indiana Michigan Power and Tennessee Valley Authority that represent the first time that Google will deliver data center demand response by targeting machine learning (ML) workloads.
This builds on Google’s successful demonstration with Omaha Public Power District (OPPD) “where we reduced the power demand associated with ML workloads during three grid events last year — paving the way for us to pursue opportunities at other locations,” Google noted.
“Meeting energy demand with reliable, affordable power takes an all-of-the-above approach,” said Claire Jones, Manager, Demand Response & Event Management Power Supply & Fuels. “TVA’s demand response programs are an important way we work with Local Power Companies and customers on days of peak energy use to protect the system. Our partnerships are a great example of how demand response programs can ensure we deliver reliable power while supporting economic growth and innovative industries.”
“I&M is excited to partner with Google to enable demand response capabilities at their new data center in Fort Wayne, Indiana. As we add new large loads to our system, it is critical that we partner with our customers to effectively manage the generation and transmission resources necessary to serve them. Google’s ability to leverage load flexibility as part of the strategy to serve their load will be a highly valuable tool to meet their future energy needs,” said Steve Baker, president and chief operating officer of I&M.
Google noted that the first data center demand response capabilities it developed involve shifting non-urgent tasks — like processing a YouTube video — during specific periods when the grid is strained.
“Through our ongoing partnerships with Centrica Energy and transmission system operator Elia in Belgium, and Taiwan Power Company in Taiwan, we've leveraged this capability to help grid operators maintain reliability during those periods of the year when demand is the highest,” wrote Michael Terrell, Head of Advanced Energy for Google, in a blog post.
“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. By including load flexibility in our overall energy plan, we can manage AI-driven growth even where power generation and transmission are constrained. We believe this is a promising tool for managing large new energy loads and facilitating investment and growth,” wrote Terrell.
The Google executive said that data center demand flexibility is still in the early stages and will only be available at certain locations. “There are limits to how flexible a given data center can be, since high levels of reliability are critical for services like Search and Maps, as well as Cloud customers in essential industries like healthcare,” he said.
Incorporating ML workloads “is an important step to enable larger scale demand flexibility, delivering grid reliability and cost-saving benefits in the places where these capabilities are deployed. By engaging in long-term resource planning with utility partners like I&M and TVA, we can integrate flexibility into future grid development alongside Google’s data center infrastructure deployment.”
Terrell said that managing data center load growth will require a portfolio of solutions, including new generation and transmission investments, but demand response can play an important role.
“Looking forward, we remain committed to collaborating with system operators, utilities, and industry partners to capture AI’s immense opportunity while supporting a clean, reliable, and affordable energy system for everyone,” he wrote.
