• • • DATA CENTRE MANAGEMENT • • •
How energy suppliers can
navigate the data centre surge By Daniel Cross, Ph.D., Senior Director of Load Forecasting, POWWR
anything the industry has faced before. These facilities, the backbone of the digital economy, are expanding at a staggering pace, consuming more electricity than entire cities. The rapid acceleration of artificial intelligence (AI) is only exacerbating the trend, pushing energy usage to unprecedented levels.
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According to Goldman Sachs, AI-driven data centres could increase global power demand by 165 per cent by 2030. In the U.S. alone, data centre electricity consumption is expected to double, reaching up to 8 per cent of national power demand. This surge is forcing suppliers to rethink how they forecast and manage load while protecting already tight margins.
Why data centres are different Unlike traditional commercial customers, data centres present unique forecasting challenges that make them a difficult load to manage. The biggest issue is that historical energy consumption does
nergy suppliers are no strangers to shifting demand patterns, but the surge in power consumption from data centres is unlike
not always reflect future demand. Many data centres are built with massive expansion plans in mind, meaning their early energy usage numbers may be deceptively low. Suppliers that base contracts on these initial figures may find themselves scrambling to adjust when actual demand surges beyond expectations. Calculating the base load stability of a data centre can also be tricky. While they operate with relatively steady energy demand that is not tied to weather fluctuations, this does not mean they are risk-free. Data centres are also limited in their ability to shift usage to off-peak hours, making them less flexible participants in demand response programs compared to other large energy consumers.
Many energy suppliers may assume that once a data centre is online, it becomes a set-it-and-forget-it customer. Yet, this is risky. While base load stability means scheduling adjustments are minimal, financial risk remains if usage patterns do not align with forecasts. Suppliers need to take a more nuanced approach when pricing and hedging these contracts.
Managing the unpredictable Energy suppliers must adopt more sophisticated forecasting and risk management strategies to navigate the growth of data centres. Traditional methods that rely on historical data alone won’t be sufficient for data centres that plan to ramp up or start up for the first time. Instead, suppliers need to integrate real-time interval data (IDR) and advanced metering systems (AMS) to refine their projections and make smarter hedging decisions. One of the most effective risk management strategies is block hedging, which allows suppliers to minimise exposure to sudden demand fluctuations. Demand response programs can be useful tools for some data centres, but they are only viable in situations where workloads can be scheduled for off-peak hours. Since many data centres require continuous uptime, suppliers need to determine whether demand response participation is realistic before factoring it into their pricing models.
The structure of energy contracts also plays a crucial role in mitigating risk. The key is ensuring that energy contracts are priced in a way that accounts for the unpredictability of data centre ramp-up periods and usage patterns. One of the most important steps suppliers can take is strengthening collaboration with data centre operators. By improving communication around expected usage patterns and expansion plans, suppliers can better anticipate demand shifts and structure contracts accordingly. Regulatory adaptation is another crucial
factor. As policies are adjusted to accommodate AI-driven energy demand, suppliers must stay ahead of emerging compliance requirements to avoid unnecessary penalties or pricing disadvantages. The ability to quickly adjust to new regulations will be a key differentiator in this evolving market.
As data centres continue their rapid expansion, they are no longer niche energy consumers. They are crucial to modern infrastructure, and their impact on energy markets will only intensify as AI-driven applications demand ever-increasing computational power. This growth is driving the need for continuous energy expansion, straining grid capacity and forcing utilities to adapt to a more volatile demand landscape. Those that develop smarter forecasting models, adapt their pricing strategies, and refine their risk management approaches will be best positioned to secure greater profitability, market stability and long-term competitiveness in the data centre boom.
12 ELECTRICAL ENGINEERING • APRIL 2025
electricalengineeringmagazine.co.uk
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