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Field service advice needs more than a slide deck
Why our team trained on IFS Advanced Forms with OmniByte before recommending it.
Industry
Grid intelligence
40% of Dutch transformer stations are at or near capacity (Netbeheer NL). The reflex is to build more infrastructure. Grid operators moving ahead are building intelligence at the edge first, then deciding which cables still need to be laid.
With solar, batteries and EV chargers reshaping load, operators move automated decisions to the edge.
From central control to edge-based decisions
The traditional grid model assumed control happens in the center. That breaks when a distribution network carries thousands of solar installations, battery systems, and EV chargers, each capable of feeding power back or drawing peaks the transformers were never sized for. A substation detects voltage rise and adjusts tap settings before the control room sees the alert. IFS Cloud treats each grid asset as an intelligent node: thresholds trigger automated responses, and the control room sees outcomes rather than micro-decisions.
DER integration is a data architecture problem
Benelux grid operators have solid visibility into high-voltage assets, almost none at the distribution edge. They see a transformer is overloaded. They do not see which DER caused the spike or could have absorbed it. IFS Cloud builds the data model that makes coordination possible. Every DER carries an asset record with live operational data and capacity limits. DERMS integration links individual resources into virtual power plants. When a feeder needs feed-in reduction, the system picks which DERs to curtail.
Industry
EDF Renewables UK and Ireland: 380 users, 90 mobile technicians, one IFS Cloud platform
Grid operators who have moved past the pilot phase face a different challenge: keeping edge logic aligned as DER penetration climbs and load patterns shift.
Risk-based maintenance across the T&D edge
Not every asset failure carries the same consequence. A primary substation outage affects tens of thousands of customers. A distribution cabinet fault affects a street. Maintenance budgets should reflect that difference. IFS Cloud supports risk-based prioritization: transformers with early degradation signals get attention before identical units running normally. The risk calculation combines condition data, network criticality, and consequence of failure, weighted for the actual grid topology. Crews move from calendar routines to assets that will actually fail.
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Frequently asked questions
Grid intelligence at the edge is the operating model where decisions about voltage, frequency, and feed-in happen at the substation or DER itself, not in a central control room. Grid operators ahead are already pushing logic to the edge rather than waiting for a central AI rollout.
Grid intelligence at the edge is the operating model where decisions about voltage, frequency, and feed-in happen at the substation or DER itself, not in a central control room. Grid operators ahead are already pushing logic to the edge rather than waiting for a central AI rollout.
The failure is almost never hardware. It is data architecture. Operators can see high-voltage assets but cannot identify which of the hundreds of DERs on a feeder caused an overload or could solve it. IFS Cloud closes that gap by treating every DER as an asset record with live operational data.
Risk-based maintenance means maintenance budgets follow consequence of failure and condition, not calendar intervals. A primary substation with early degradation signals gets attention before a distribution cabinet running normally. IFS Cloud supports this across the full asset hierarchy, weighted for the network’s actual topology.
Capital investment decisions become data-driven when operational asset data flows into the investment model. IFS Cloud, combined with Copperleaf, connects total cost of ownership, failure probability curves, and remaining useful life to the same system that issues work orders.
The first question is whether an anomaly flag triggers an automated response or a phone call at 02:00. Grid operators get named senior consultants who keep the configuration current as DER penetration climbs, not a ticket queue.
Discuss Grid Intelligence with Eqeep
If your grid intelligence processes are under pressure from complexity, growth, service expectations or data quality, we can help identify the most practical IFS improvement path.
Tell us where grid capacity, maintenance or investment choices are under pressure. We will help you connect the operational and capital view in IFS.