National Grid turns to digital twins to speed up energy network planning
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As Britain accelerates toward net zero, the pressure on electricity networks is intensifying. Rising demand from electric vehicles, data centres and low carbon heating is forcing utilities to make investment decisions faster and with greater confidence. For National Grid, the challenge is no longer a lack of data but how to translate vast and fragmented information into infrastructure that can be delivered on time.
The company is now deploying digital twins to reshape how it plans and develops the electricity network. Through a partnership with Atos, National Grid has launched a platform known as Triton, designed to model future demand and network constraints in far greater detail than traditional planning tools. The aim is to remove bottlenecks before they slow the energy transition.
By creating a digital replica of the physical grid, Triton allows engineers to simulate how the network will respond to new connections and changing demand patterns. National Grid says the system can reduce the time required to analyse and decide on network reinforcements by 70 percent, a significant gain at a moment when delays are increasingly costly.
Digital twins accelerate network planning decisions
Electricity networks have historically been planned using static models updated infrequently. That approach struggles to cope with the pace of change now facing the system. New generation, storage and high load users are connecting faster than reinforcement projects can be delivered, raising the risk that grid capacity becomes a brake on economic growth.
Triton replaces static forecasts with dynamic simulations. By mapping future demand at individual grid supply points and transmission substations, the platform provides long term visibility on where capacity will be needed. Engineers can test multiple scenarios quickly, assessing the impact of new connections or policy driven demand growth without waiting months for revised models.
According to National Grid, this capability shortens decision cycles and allows capital to be directed more precisely. Instead of reinforcing assets based on broad assumptions, investment can be targeted where constraints are most likely to emerge. In a capital intensive sector, this improves both efficiency and confidence.
Owen Wilkes, network design director at National Grid, has described the platform as a way to virtually model how, when and where the network must expand to meet rising demand. The emphasis is on anticipating pressure points rather than reacting once capacity is exhausted.
Integrating fragmented data into a single system
One of the persistent obstacles to digital transformation in utilities has been data fragmentation. Information is often spread across legacy systems, external partners and regional operators, making it difficult to form a coherent picture of the network. Triton has been designed to address this issue directly.
The platform consolidates thousands of datasets provided by distribution network operators and transmission owners, automating the processing of information that previously required manual intervention. This data is then fed into National Grid’s wider monitoring and engineering tools, enabling faster configuration of models and more frequent updates.
For Atos, which developed the platform, the focus has been on reducing risk as well as improving speed. Graham Scanlon, head of critical national infrastructure at Atos UK and Ireland, has said the system allows National Grid to make data based decisions more quickly while supporting both current operations and future needs.
The approach reflects a broader shift toward treating data as infrastructure in its own right. As energy systems become more complex, the ability to integrate and interpret information at scale is becoming as important as physical assets.
Implications for customers and future connections
The impact of Triton extends beyond internal efficiency at National Grid. Improved modelling has direct consequences for businesses seeking new or expanded grid connections. Data centres, renewable energy projects and large industrial users all depend on accurate assessments of network capacity and connection timelines.
By stress testing scenarios in advance, the platform helps identify where reinforcement will be required to support high load customers. This provides greater clarity for commercial decision makers planning major investments that rely on secure electricity supply. In theory, it should also reduce the risk of late stage surprises that delay projects.
The system also supports the assessment of embedded generation and flexible demand, both of which are expected to play a growing role as the grid evolves. Understanding how these assets interact with existing infrastructure is critical to maintaining reliability while integrating more low carbon energy.
The project has already attracted industry recognition, with National Grid and Atos receiving the Unlocking Data Award at the Utility Week Awards in 2025. The award reflects a wider trend in which data maturity is increasingly linked to resilience and progress toward clean energy goals.
As electricity demand continues to rise, the ability to plan infrastructure proactively will shape how quickly the UK can decarbonise. Digital twins are not a substitute for physical investment, but they may determine how effectively that investment is deployed. For National Grid, Triton represents an attempt to ensure that data driven planning keeps pace with the scale of change facing the energy system.
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