For decades, intelligence in electricity networks has been concentrated in the SCADA center, control room and dispatcher’s screen.Field equipment collected data, sent it upstream for analysis, and waited for instructions to come back.That model still plays a critical role. But the grid is evolving.
With the rapid growth of renewables, distributed energy resources, battery storage, electric vehicles and smart meters, utilities are managing an increasingly decentralized network.The question is no longer only how to make the control room smarter.
What if the network itself could become intelligent?
AI Is Moving to the Edge
Smart reclosers, RTUs, IEDs and other intelligent devices are evolving from simple data collection points into local decision-makers.Instead of sending every event to a central system, some decisions can increasingly happen where the event occurs.
The traditional model:
Sense ? Send ? Analyse ? Decide ? Act
is moving towards:
Sense ? Analyse ? Decide ? Act
This can make a significant difference when milliseconds matter.
Faster, More Resilient, More Scalable
Faster
Local intelligence can support fault detection, isolation and restoration without waiting for every decision to travel through the control center.
More Resilient
If communication links are disrupted, intelligent field devices can continue making appropriate local decisions, reducing dependence on constant connectivity.
More Scalable
Millions of DERs, EVs, batteries and smart devices cannot be micromanaged from one central system. Intelligence needs to exist closer to the assets themselves.
What This Means for DERMS and FDIR
This evolution is closely connected to DERMS, FDIR 2.0 and distributed AI inference.The control center will remain essential for system-wide visibility, coordination and optimization.
But increasingly:
Central systems optimize the network.
Edge systems respond to the network.
The future is not about replacing centralized intelligence. It is about combining central intelligence with distributed intelligence.
A Changing Digital Footprint
Moving intelligence to the edge also changes how data moves through the network.
Not every measurement needs to travel continuously to the Cloud or a central data center. Some data can be processed locally, some events can be filtered, and some decisions can happen directly at the point of action.
As Aurélien Pallavisini, CEO of Strat & IoT, explains:
“AI at the edge doesn’t eliminate the digital footprint. AI redistributes and shrinks the network-and-cloud portion of it, trading centralized data-center load for lean, purpose-built compute at the point of decision.”
The objective is not simply to process more data.
It is to process the right data, at the right place, at the right time.
The Strategic Question for Utilities
The question should not simply be:
“Where can we deploy AI?”
It should be:
“Where should intelligence sit?”
Some decisions belong in the control room. Others belong at the substation, feeder or directly on the equipment.The utilities shaping the next generation of the grid will be those that understand where intelligence creates the greatest operational value and how centralized and distributed systems can work together.The grid will not stop needing control rooms.
It will simply become capable of thinking beyond them.
How STRAT & IOT Can Help
At STRAT & IOT, we help utilities connect AI, IoT, OT and digital technologies with real operational challenges.
Our areas of focus include smart metering, ADMS, DERMS, grid automation, asset intelligence, IoT architecture, AI strategy and digital transformation.
Our objective is simple:
