Utilidata and Nvidia’s projects with Portland General Electric, Duquesne Light, and other utility partners aren’t going to completely replace those utilities’ existing smart meters — at least, not right away. Instead, these initial projects are tied to strategic deployments at parts of the grid where the utilities are seeking more granular information, Brumberger said.
One major area of interest is in assessing the grid impacts of rooftop solar systems, backup batteries, EV chargers, and other so-called distributed energy resources, he said. A growing number of utilities are looking for ways to enlist these kinds of devices to reduce strains on their power grids — say, by instructing batteries to store solar power at midday to release it later when it’s more valuable to the grid, or by coordinating when EV charging happens to avoid overloading local grid infrastructure when everyone charges at once.
These virtual power plants (VPPs) or distributed energy resource management systems (DERMS) can sometimes be handled in a command-and-control fashion by utility grid operations centers communicating to in-field devices via hard-wired, cellular, or broadband internet. But more advanced tasks require complex computations of local grid conditions and real-time communications between multiple local devices — exactly what Karman was designed to handle, Brumberger said.
“How can you have a VPP that’s, from a capacity perspective, as big and as reliable as a gas-fired plant, without accelerating computing and AI? You’ve got so many disparate resources that have so much untapped value that we ultimately have to unlock,” he said.
Portland General Electric, which is planning to rely on distributed energy resources for a significant chunk of its future grid needs, sees technologies like Karman as a way to better understand the reliability of VPPs and DERMS, Ananth Sundaram, senior manager of integrated grid at Portland General Electric, told Canary Media in a 2023 interview.
“We can look at grid services, we can look at disaggregation of the power, and what customer behavior and customer signatures we can track,” he said. “That will not only provide us a solid platform for serving our clients, it also helps us harvest massive amounts of data we need to understand what exactly is happening on the grid edge.”
Utilidata is hoping that utilities and regulators will keep these future needs in mind when planning the next cycle of large-scale smart meter deployments. Brumberger noted that Quanta, a new investor in the latest funding round, is a key partner in many large-scale utility infrastructure and smart meter deployments.
Utilidata’s near-term deployments are also dependent on the Trump administration preserving the DOE grants supporting its first-of-a-kind utility projects. The administration has frozen and threatened to end federal climate and energy funding approved during the Biden administration, as well as to eliminate large swaths of the federal workforce, including DOE offices that manage these grant programs.
“We have not received any word that those projects are not happening,” Brumberger said about the grants. “If you sort of peel back the layers of our project, at its core, it’s next-generation AI infrastructure. That theme does seem central to this administration, when they talk about winning the AI race, about hardening our critical infrastructure.”
The latest round of funding will allow Utilidata to expand to new markets, both outside the U.S. and outside the utility grid, Brumberger said. In particular, it’s exploring the prospects for embedding its Nvidia-enabled distributed energy control devices within data centers themselves, enabling them to better understand and control power usage down to the server level, he said.
Utilidata and Nvidia’s computing platforms will also be collecting, analyzing, and “training” from the data they’re collecting, much like large language models (LLMs) “train” on massive amounts of human-generated text and images, Brumberger noted. The data might include things like differences between the grid voltage signals that accompany power disruptions caused by people turning things on and off in their homes and those caused by external impacts like tree branches hitting power lines.
“It’s no longer just a sensor, but a little hub of activity where you can train locally, so not every piece of information needs to leave the site,” he said. “The question is going to be, is this the kind of tech you need on 10% of your territory, on 50%, on 80%, or 100%?”
