The data centres that enable AI to function require vast amounts of energy. There are arguments that if data centres can be flexible in their demand, they could serve as a grid asset, particularly in periods when consumer demand is lower than supply.

But electricity demand is increasing at unprecedented rates, and the areas typically pegged for data centre developments do not have the infrastructure to support it.

Building out that infrastructure is the responsibility of the National Grid, which operates the high‑voltage electricity transmission network in England and Wales. At the Clean Power 2030 Summit, hosted by our publisher Solar Media in London on 30 June-1 July, a panel will address impact of data centres and AI on electricity demand.

Joining the panel, titled ‘Data Centres, AI & Digital Infrastructure: When Demand Arrives Faster Than the Grid’, is National Grid’s head of network architecture & innovation, David Adkins.

Adkins spoke to Solar Power Portal ahead of the event about how National Grid is planning for the increased demand from AI and digitalisation, as well as how it is using the technology to its benefit.

Tickets are still available for the Clean Power 2030 Summit. View the full agenda on the event website and book your ticket to attend. Our readers can secure 20% off tickets with the code SPP20.

Solar Power Portal: The growth of AI and data centres is driving significant electricity demand. How is National Grid preparing the network to meet this surge, while maintaining reliability?

David Adkins: The growth of AI and data centres is a step-change in electricity demand, but it’s also an opportunity to rethink how demand interacts with the grid. Our approach is twofold: investing to expand capacity where it’s needed while maintaining system resilience and getting smarter in how we plan and operate the system.

We’re progressing major reinforcement programmes to bring forward capacity alongside reforms to speed up connection timelines. At the same time, we’re taking a whole-system view, using forecasting, scenario modelling and closer coordination with customers to anticipate demand earlier and plan accordingly. That allows us to plan ahead rather than react, while maintaining the reliability the system depends on.

Digitalisation is often cited as key to managing more complex energy systems. How are tools like digital twins helping you plan and operate the grid more efficiently as demand grows?

As the system becomes more complex, digitalisation is essential to managing uncertainty and planning efficiently. We’re using advanced modelling and digital tools, such as the Triton digital twin developed in partnership with Atos, and our internally developed Neptune. These allows us to better understand how demand will evolve, and how it interacts with generation patterns.

These capabilities allow us to simulate different scenarios, optimise network utilisation, and make more informed investment decisions. In practice, that means getting ahead of constraints rather than reacting to them and ensuring the system can accommodate new demand in a cost-efficient way.

Grid enhancing technologies are gaining attention as a way to unlock additional capacity from existing infrastructure. Can you share how these solutions are being deployed, and their impact so far?

Grid enhancing technologies are a key part of unlocking capacity from the existing network, and dynamic line rating is one of the clearest examples. Dynamic line rating (DLR) uses real-time data on conductor conditions and local weather—such as wind and temperature—to calculate how much power a line can safely carry at any given moment, rather than relying on conservative static assumptions. That gives operators a more accurate view of available capacity and can safely increase the amount of power flowing across existing overhead lines when conditions allow.

We recently announced a significant expansion of DLR across our network, making better use of existing infrastructure, reducing constraints, enabling more renewable power to flow across the network, and lowering costs for consumers.

With data centres often requiring large, continuous power loads, how are you working with industry to support flexible or smarter energy use?

We’re working closely with industry to enable data centres to become active participants in the energy system, rather than passive consumers. Through partnerships such as our work with Emerald AI, we’re showing how data centres can adjust workloads in response to grid signals, temporarily lowering demand during peak periods and increasing it when capacity is available. This is enabled by software that acts as a bridge between the grid and the data centre, allowing real-time coordination of energy use.

This supports system stability and it opens up more flexible, and potentially faster, connection pathways for customers. We are working with Ofgem and government to understand how codes can be updated to support the use of flex to reduce network build and accelerate connections.

Looking ahead, what does a future-ready grid look like in a world increasingly shaped by AI, and what role will National Grid play in enabling that transition?

A future-ready grid is more flexible, more digital and more interactive. Rather than a one-way system, it’s a network where large users like AI data centres respond dynamically to system needs, helping to balance supply and demand in real time. It’s also a system where digital tools give us greater visibility and predictive capability, enabling smarter investment and operation.

National Grid’s role is to help orchestrate that system, connecting new demand, enabling low carbon generation, and creating the conditions for flexibility to scale. Ultimately, our goal is simple: to ensure the grid can support economic growth from AI and digital industries, while remaining reliable, affordable, and aligned to net zero.

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