When a utility hears the word modernization, their mind often goes to investment cycles, regulator rate cases and large-scale technology upgrades. Glitre Nett is taking a more pragmatic approach. The Norwegian utility is building on its existing AMI deployment to extend visibility and control to the low-voltage edge.

As the first grid edge intelligence (GEI) deployment in the Nordics, the project offers a repeatable modernization blueprint: how utilities can extract greater value from infrastructure already in place by making targeted, incremental investments that transform growing volumes of network data into operational intelligence.

Building the Foundation for Grid Edge Intelligence 
Glitre Nett operates in a region where load growth, renewable energy adoption and distributed energy resources (DERs) are increasing the complexity of grid operations. As conditions become more dynamic, utilities need greater visibility into what’s happening across the network and more flexibility in how they respond to changing demand.

To address this, Glitre Nett is modernizing its AMI network with 10,000 Itron distributed intelligence (DI)-enabled grid edge devices as part of the first grid edge device deployment in Europe. As a result, the utility gains access to real-time data that can support faster, more localized decision-making and lay the groundwork for additional grid-edge applications.

With cellular-enabled meters now deployed and continued collaboration between Glitre Nett and Itron teams, the focus is shifting from installation to operational execution. Early efforts are centered on applying real-time data and distributed intelligence to improve grid reliability and better understand conditions throughout its service territory.

Modernization without the Rip-and-Replace
Glitre Nett's deployment demonstrates how distributed intelligence can be layered incrementally on an AMI foundation. Open architectures and a universal headend allow new capabilities to be integrated alongside existing systems, reducing complexity and avoiding disruption. More importantly, they create a foundation for turning network data into operational intelligence that can support additional use cases.

This approach offers an alternative to the broad assumption that modernization always requires an immediate full replacement. An integrated technology platform that connects devices, data and applications enables utilities to build on existing investments while improving capabilities over time. Further, with this approach, the goal isn’t just adding intelligence, it’s adding it where and when new investment is needed.

Turning Network Data into Actionable Insights
Enter GEI. At its core, GEI combines edge computing, communications networks, data management and applications to support more informed decision-making and localized control at the low-voltage edge.

DI-enabled grid edge devices act as distributed sensors that analyze high-resolution data, providing insight into conditions that may otherwise be difficult to detect. A low-latency communications network enables data exchange between field devices and utility systems, while a universal headend provides a single platform for managing devices, networks and data across the deployment.

The platform is further supported by Itron's Intelligent Edge Operating System (IEOS), which allows applications to operate across both edge and enterprise environments. It also supports coexistence of legacy and new AMI systems via simplified integration. Additionally, IEOS provides a foundation for Itron and third-party applications to work seamlessly together to support grid reliability, DER management, capacity management and other future use cases.

Together, these solutions allow utilities to collect, analyze and act on data in near real time, providing greater situational awareness from the grid edge to the control room. 

Closing the Low-Voltage Visibility Gap
One of the biggest challenges utilities face is identifying developing issues before they become larger reliability events. That starts with understanding what’s happening on low-voltage circuits, where visibility has historically been limited.

Insight at the grid edge can help utilities identify issues earlier, improve outage awareness and response and better understand changing network conditions. Because intelligence is distributed closer to where events occur, utilities like Glitre Nett can get the information they need to proactively respond without waiting on centralized systems to process data.

Managing DER Growth with Greater Confidence
As solar generation, electric vehicles and other DERs continue to grow, understanding how those resources affect localized grid conditions is more important than ever. In Europe alone, an estimated 3.3 million residential DERs created 9.0 GW of flexible capacity by the end of 2025. Traditional, centralized grid management methods can no longer keep pace.

GEI addresses this by providing greater insight into DER impacts and localized constraints. Utilities gain a clearer understanding of how DERs are affecting the network, supporting more informed planning and operational decisions without relying solely on extensive additional monitoring infrastructure.

Finding Capacity Before Building It
Distribution utilities are under pressure to support load growth, DER adoption and electrification while making the most of existing infrastructure. But it’s not always practical or feasible to simply build more capacity. A smarter approach is to strategically deploy intelligence to understand how existing assets are being used to give utilities greater awareness of how existing capacity can be optimized. This critical information helps utilities make more informed planning and investment decisions and potentially defer unnecessary infrastructure upgrades.

Moving from Data Collection to Operational Intelligence 
For years, AMI has helped utilities understand what happened. Deployments like Glitre Nett are exploring how that same infrastructure can help them understand what's happening in real time and take targeted action.

GEI makes that possible, moving beyond data collection to operational intelligence at the low-voltage edge.