The chip was built with Nvidia's Jetson edge AI platform and the Nvidia AI Enterprise software suite, and it's embedded in smart meters. Nvidial's technology will help Utilidata regularly and quickly deploy new algorithms to existing algorithms on the smart meters, at scale, while minimizing downtime.
This kind of power grid management will become increasingly important as more renewable energy sources and distributed energy resources (DERs) come online. DERs refers to a range of technologies -- close to end users -- that can store or generate energy, like solar panels and electric vehicles.
"To maximize the value of DERs and integrate these resources into grid operations, utilities are going to need decentralized solutions," Utilidata CTO Marissa Hummon said in a statement. "Existing meters don't have the computational power or communications bandwidth to support this kind of real-time operation. But combining our real-time grid software solutions with Nvidia's advanced edge computing capabilities unlocks new value from the meter and offers a path to scale."
Within the US Energy Department, the National Renewable Energy Laboratory (NREL) has developed a decentralized solution called Real-Time Optimal Power Flow (RT-OPF). Originally developed with funding from DOE's Advanced Research Projects Energy program, RT-OPF enables highly localized load control to integrate an increasing number of DERs while ensuring stable and efficient grid operations.
"To date, the scalability and commercial potential of technologies like RT-OPF have been limited by single-use hardware solutions," Santosh Veda, Group Manager for Grid Automation and Controls at NREL, said in a statement. "By developing a smart grid chip that can be embedded in one of the most ubiquitous utility assets -- the smart meter -- this approach will potentially enable wider adoption and commercialization of the technology and redefine the role of edge computing for DER integration and resiliency."
