As NVIDIA, IBM and others apply AI to boost utilities, regulatory and data privacy obstacles abound

Digital-technology providers have long been frustrated with what they see as utilities’ innovation-impeding focus on reliability. But rapid load growth and potential artificial-intelligence solutions are inspiring collaboration, particularly on ways to use and share power-system data.

Utilities have seen the data on significant projected load growth from transportation, manufacturing, building electrification and data centers. And tech companies like NVIDIA, Microsoft, IBM and Schneider Electric are beginning to understand the regulatory barriers holding utilities back from transitioning to advanced AI computing strategies, executives said.

Digital technologies’ skyrocketing computational power and hyperscale cloud resources are transforming previous assumptions about AI’s potential to learn, execute and optimize system operations, starting utilities on what some are calling the “technology transition.”

“The utility industry is conservative, but it faces clean-energy and emissions-reduction mandates,” said Marc Spieler, senior managing director, energy, for microprocessor market leader NVIDIA. Advanced computing’s “real time predictions can optimize” decision making on things like bulk system dispatch and maintenance and NVIDIA’s “dedicated modules will apply learning from other industries to the energy transition,” he added.

Utilities have used advanced computing in wildfire mitigation, vegetation management and predictive maintenance, and are beginning to consider its potential to optimize system dispatch, analysts said.

“The technology business model is ‘move fast and break things’ and they haven’t always understood why regulated utilities don’t move as fast,” said Edison Electric Institute General Counsel, Corporate Secretary and Executive Vice President, Clean Energy, Emily Sanford Fisher. “But there seems to be a new spirit of cooperation on solving utility challenges.”

One obstacle may slow this technology transition. Tech companies have seen how innovations in advanced computing from other sectors can maximize AI capabilities. But utilities still must verify that potential and convince regulators that investments in implementing advanced computing capabilities are justified.

The challenge and the potential

The rapidly rising load growth is clear.

“Over the past year, grid planners nearly doubled the 5-year load growth forecast” from “2.6% to 4.7% growth,” a December 2023 Grid Strategies study reported. The 2024 forecast “is likely to show an even higher nationwide growth rate,” driven by investment in new manufacturing, industrial, and data centers, it added.

Broad use of advanced computing is now providing “some decision support to bulk system operators” for managing the new load, said Jeremy Renshaw, senior technical executive, AI, quantum, and innovation, with the Electric Power Research Institute.

But fully optimizing distribution system operations and dispatch “could be one breakthrough or years away,” Renshaw added.

Many tech companies are putting advanced computing to work in hopes of finding that breakthrough.

To read the rest of the article, visit Utility Dive.