Artificial intelligence (AI) and machine learning are rapidly transforming the world, from how we work and live to how industries make decisions. Yet, as these technologies evolve, they bring with them a challenge that rests firmly on the shoulders of the electricity grid.
The proliferation of data centres, especially the new generation of hyperscale facilities, is driving a surge in global energy demand. According to the International Energy Agency’s Energy and AI report, data centres worldwide are expected to more than double their electricity consumption by 2030, reaching around 945 TWh. In the United States alone, nearly half of the country’s electricity demand growth between now and 2030 will come from data processing. By then, the US will consume more electricity for data than for producing aluminium, steel, cement and chemicals combined.
Goldman Sachs Research paints an even steeper picture. Their analysis forecasts a 165% rise in data centre power demand by the end of this decade compared with 2023. By 2030, they predict around 122 GW of capacity will be online. As AI workloads intensify, power density will rise as well, climbing from 162 kW per square foot in 2023 to 176 kW in 2027.
This escalating energy demand is not only an environmental concern but also a fundamental infrastructure challenge. Goldman Sachs estimates that $720 billion in global grid investment may be required by 2030 to support this expansion. However, grid development is not a quick or simple task. As the report’s author James Schneider notes, permitting and building new transmission projects can take several years, creating a bottleneck that risks slowing data centre growth if regions are not proactive.
Grid connection delays are already proving to be major barriers to data centre development. A Slaughter & May report highlights that in the UK, connection delays can stretch up to 15 years, with seven to ten-year queues common across Europe. In some cases, projects are facing waits of over a decade, dramatically increasing costs and delaying returns on investment.
Even where connections exist, grid constraints can drive up wholesale electricity prices and capacity premiums, further reducing project viability. Governments in countries such as Australia, Canada and the UK are now working to reform connection rules, but analysis by Ember suggests that limited grid capacity continues to steer investment decisions.
According to Ember, the urgency of time-to-market is pushing data centre developers toward regions with more flexible and less congested grids, particularly the Nordics and Southern Europe. They forecast that by 2030, data centre market growth in these regions could be double that of traditional hubs such as Frankfurt, London, Paris and Dublin. By 2035, half of Europe’s data centre capacity may sit outside these legacy centres.
However, Ember also makes an important point. Smart and strategic choices by system operators can dramatically ease these constraints. Instead of expanding infrastructure at vast cost and over long timescales, grid-enhancing technologies can help make the most of existing assets. Among these, Dynamic Line Rating (DLR) is already proving to be one of the most effective tools for unlocking hidden grid capacity.
In most transmission networks, power conductors are conservatively rated to guarantee safety and reliability. Higher ambient temperatures lead to higher conductor temperatures, which can cause the lines to sag, reducing clearance and increasing the risk of contact with trees or other structures. To prevent this, traditional Static Line Ratings (SLR) are based on worst-case scenarios that assume the least favourable environmental conditions.
While this ensures safety, it also leaves vast amounts of capacity unused. Dynamic Line Rating (DLR) changes this by using real-world, real-time data to determine how much current a line can safely carry.
For example, while solar radiation may heat a conductor, higher wind speeds often cool it, allowing more power to flow safely. Capturing and analysing such highly localised variations, which can be influenced by terrain or even individual trees, is key to freeing up existing capacity.
Ampacimon achieves this through its patented, self-powered sensor technology, which gathers precise vibration and temperature data directly from conductors. These sensors measure vibration frequencies using accelerometers, enabling accurate real-time estimation of sag and conductor temperature. Combined with machine learning models and high-resolution weather forecasting, the result is a highly accurate calculation of a line’s true ampacity at any given moment.
Even small errors in estimating conductor temperature or sag can have significant implications. Ampacimon’s DLR platform delivers this data with exceptional precision. By doing so, it can unlock up to 40% additional capacity on existing lines, enabling operators to defer costly upgrades and reduce network congestion. This additional capacity can also support new data centre connections, helping regions meet demand safely and economically, while maintaining reliability standards.
Across Europe and the Americas, Ampacimon’s DLR systems are already deployed at scale. One striking example comes from Denmark, where Energinet, the state-owned transmission system operator, is investing heavily to strengthen its grid.
Between 2023 and 2026, Energinet plans to spend DKK 41 billion (US$6.5 billion) on transmission upgrades, adding 3,300 km of new conductors. Yet even with that investment, demand pressures mean that additional capacity is needed immediately. Building new lines or reconductoring existing ones is costly and time-consuming, so Energinet turned to DLR to relieve existing bottlenecks.
By replacing static ratings with dynamic, real-time assessments of conductor temperature and environmental conditions, Energinet can accurately forecast the true thermal capacity of its lines. This enables it to unlock latent grid potential and ease congestion, supporting new load growth, including data centres, far more rapidly than traditional reinforcement methods could achieve.
The rise of AI and the data-driven economy demands grids that are not just larger but smarter. The solution lies in technology that enables operators to maximise existing infrastructure while maintaining safety, reliability and sustainability.
Ampacimon’s Dynamic Line Rating systems are proving that it is possible to deliver more capacity, faster and at lower cost. This is precisely what is needed to power the next wave of digital transformation.
In short, the path to a smart society begins with smart grids. As the data revolution gathers pace, grid-enhancing technologies like DLR are ensuring that the energy system can keep up.
You can no longer participate in this event but you can access its recording