Last year, we celebrated Norwegian utility Glitre Nett’s Grid Edge Intelligence (GEI) program, the first of its kind in the Nordics. The ongoing deployment is exploring how Glitre Nett can extend its existing advanced metering infrastructure (AMI) beyond traditional meter data collection and into grid operations.

In part one of this series, we looked at how Glitre Nett is building on its AMI foundation to bring greater intelligence to the low-voltage grid. In part two, the focus shifts from visibility to action: how intelligence at the grid edge helps utilities make faster, more localized decisions, and successfully manage a more complex and dynamic grid.

What Changes When the Meter Becomes a Grid Sensor
For decades, a meter’s primary job was relatively straightforward: measuring energy consumption and sending that information back to the utility for centralized processing. As computing moves to the grid edge, the role of the meter is expanding.

Today, Itron Riva DI-enabled grid edge devices go beyond highly accurate energy measurement. With computing capability built into the endpoint, they provide the foundation for distributed intelligence, acting as intelligent grid sensors that can analyze real-time conditions and enable action directly at the grid edge. Instead of relying exclusively on raw data sent upstream for centralized analysis, intelligence is distributed across edge and enterprise environments, extending observability beyond traditional monitoring points. 

Centralized analytics remain essential to grid operations, but edge intelligence adds a powerful complementary layer. By identifying significant grid conditions closer to where they occur, edge intelligence creates the potential for faster, more targeted responses. High-resolution waveform data further enriches this situational awareness, providing deeper insight into grid behavior and helping utilities better understand what is happening across the distribution network.

This isn’t simply a change in where data is processed. It points to a broader shift in how information moves through grid operations and where decisions are made.

Why Local Intelligence Matters on the Low-Voltage Grid
Many of today's grid changes are playing out across the distribution system. Solar generation, electric vehicle charging and other distributed energy resources (DERs) create dynamic conditions that vary significantly across the network. Understanding their impact requires visibility into how different parts of the distribution system are behaving. At the same time, growing attention to grid resilience across the Nordic region is increasing the importance of understanding conditions deeper within the distribution network.

Take a developing fault or localized constraint. Utilities have traditionally relied on additional monitoring infrastructure or centralized analysis of large volumes of data to understand these conditions. GEI introduces another approach: applying distributed intelligence (DI) through the AMI infrastructure to identify developing faults and localized constraints at the endpoint.

Earlier detection is only part of the benefit. More granular visibility provides a clearer understanding of where assets are under strain, where available capacity exists and how DERs are affecting individual parts of the network. For utilities, that type of information can inform decisions around outage response, DER integration and grid resilience. A clearer picture of asset loading and available capacity also helps determine where reinforcement is needed and where existing infrastructure has more room to serve growing demand. 

An Application Platform That Evolves with the Grid
One of the biggest departures from traditional AMI comes from what happens after the infrastructure is deployed.

Itron’s Intelligent Edge Operating System (IEOS) provides the application platform for extending edge intelligence over time through applications installed over the air. Unlike an AMI 1.0 model, where much of a meter's functionality is determined when the infrastructure is deployed, an application-based approach lets utilities introduce new capabilities incrementally as operational priorities change. 

Utilities don’t have to tie every new use case to the next infrastructure refresh. The same endpoint infrastructure supports applications for advanced grid reliability, DER visibility, capacity management and new customer engagement services. An interoperable architecture allows those applications to work alongside existing systems, third-party devices and solutions from different vendors.

For Glitre Nett, this application model opens the door to use cases beyond initial grid operations. As the deployment progresses, the utility is evaluating existing DI applications against Norwegian grid conditions and exploring where those capabilities could address its evolving operational needs. Glitre Nett is also looking into the potential for bidirectional intelligence over Wi-Fi through the home area network, an area where regulatory requirements will help shape how the capability develops.

Building Toward a More Intelligent Grid
Glitre Nett’s ongoing deployment illustrates how the role of AMI can expand. Infrastructure built primarily to collect meter data can also provide a foundation for distributed sensing, localized intelligence and new operational applications.

Intelligence at the endpoint supports more localized decision-making, while an application-based architecture creates room for new operational use cases long after initial deployment. As utilities face evolving demands around DER integration, capacity and grid resilience, that flexibility becomes increasingly important. For Glitre Nett and other utilities pursuing what’s next, modernization no longer requires starting over. It means building on what’s already in place and expanding what that infrastructure can support over time. 

To learn more, visit us at Enlit from Nov. 10-12 in Vienna, Austria, Stand B20.