- The construction of data centers in Europe is facing pressure from high electricity costs, with the UK electricity price reaching $111.65 per megawatt-hour, significantly higher than the $28 in the US, driving capital expenditure to shift towards lower-cost regions.
- China maintains high investment in power grid infrastructure, with Morgan Stanley (MS:US) estimating an investment of $560 billion by 2030, forming a significant advantage in computing power energy reserves.
- The cost of capacity in Europe's five major data center markets is expected to rise by 12% by 2026. If the regional grid integration process is hindered, its share in the global AI computing power market may face further pressure.
Cost Pressure on Europe's Computing Infrastructure
The core variable in the global AI computing power race is shifting from the ability to acquire advanced chips to the underlying energy supply. Europe, in the process of accelerating the expansion of supercomputing infrastructure, faces a significant energy cost disadvantage. Geopolitical uncertainty in the Middle East has led to an energy premium, directly pushing up electricity prices in the European region. Currently, the average electricity price in the UK is as high as $111.65 per megawatt-hour, Germany records $88.97, France $44.19, while the US is only $28. This significant cost difference is reshaping the capital expenditure paths of tech giants. Leading institutions like OpenAI have temporarily halted large infrastructure projects in the UK, reflecting the direct interference of high electricity prices and regulatory environments on business decisions. Research from HEC Paris indicates that the expansion of data centers in core hotspots such as the suburbs of Paris and London may lead to a further increase in local electricity prices by 20% to 40%.
Capital Expenditure Trends of Tech Giants
Against the backdrop of exponentially expanding computing power demand, electricity costs directly determine the marginal profit margin of AI services. Although Germany's Schwarz Group announced an investment of 11 billion euros to build a data center equipped with 100,000 chips and a power capacity of 200 megawatts, such huge capital expenditures still face a long payback period in the face of expensive operating costs. Companies like Microsoft (MSFT:US) have clearly expressed concerns about the long-term computing power energy gap. If AI model commercialization pricing is fully rolled out, the terminal service pricing in high electricity cost regions may face upward passive adjustments. In contrast, the Nordic region, with its abundant wind and hydroelectric resources and lower grid load, is absorbing the computing power demand spilling over from Central and Western Europe. The phenomenon of negative electricity prices in Finland at certain times provides a highly attractive operating environment for energy-intensive data centers.
Scale Gap in Power Infrastructure Between China and the US
While Europe is constrained by a fragmented energy structure, China and the US are demonstrating different resource endowments in building the foundation of computing power. The US currently maintains a lead in advanced algorithms and semiconductor hardware design, while China forms a scale effect by relying on its vast grid capacity and power generation increment. Data shows that China's power generation increment over the past decade is significant, with the total scale now more than twice that of the US. Goldman Sachs (GS:US) predicts that by 2030, China will have about 400 gigawatts of backup power capacity, three times the expected global data center power consumption. Morgan Stanley (MS:US) estimates that China will invest $560 billion in grid projects during the same period. If Europe fails to effectively integrate its cross-national grid facilities and optimize its energy storage structure, its ability to capture added value in the global technology supply chain may face a risk of continuous downward revision, given the already significant gap in data center scale.
