On April 10, 2026, the global AI industry witnessed two pivotal events: OpenAI officially suspended its “Stargate” supercomputing center project in the UK, and Maine became the first US state to enact legislation restricting the construction of large-scale data centers. While these two events may appear isolated, they collectively signal a broader trend—global AI infrastructure is under a “double squeeze” from escalating energy costs and increasingly stringent regulatory policies.

The ramifications of these events extend far beyond mere “project suspension” or “legislative restrictions.” They herald a fundamental shift in the logic underpinning global computing power distribution, presenting China with a rare strategic window for advancing its computing power industry.

■ “Stargate” Suspension: An Inevitable Retreat

High Costs Compel OpenAI to Pause

The immediate cause of OpenAI's suspension of the UK “Stargate” project is straightforward: UK industrial electricity prices rank among the highest globally, the grid connection timeline extends up to 18 months, and, coupled with regulatory uncertainties following the EU's AI Act implementation and obstacles in copyright legislation, the project's long-term return on investment falls significantly short of expectations.

This decision is driven by commercial rationale. In September 2025, OpenAI partnered with UK data center startup Nscale and chip giant NVIDIA to launch the UK iteration of the “Stargate” project, aiming to deploy up to 8,000 NVIDIA GPUs. This initiative was envisioned as a cornerstone for the UK to establish itself as a global AI hub and was included in the country's £31 billion technology investment plan.

However, reality fell short of ambition. The UK's energy cost challenges are more severe than anticipated. According to 2025 data from the International Energy Agency (IEA), UK industrial electricity prices hover around £258 per megawatt-hour (i.e., £0.258 per kWh, or approximately RMB 2.3649 per kWh). Since 2023, these prices have surged by over 124%, the highest among G7 nations.

For an AI supercomputing center with a designed capacity of several hundred megawatts, annual electricity costs would be exorbitant. Moreover, the 18-month grid connection timeline means that even if construction commenced immediately, the project would remain non-operational for at least a year and a half.

In its statement, OpenAI emphasized resuming the project “when regulatory environments and energy costs align with long-term infrastructure investment”—a classic “temporary withdrawal” formulation. In essence, unless UK energy costs plummet or regulatory policies clarify, this project is likely to be indefinitely shelved.

Maine's “Construction Ban”: Balancing Livelihoods and Environmental Concerns

Concurrently, the Maine State Legislature passed a more symbolic bill—proposing a ban on constructing data centers exceeding 20 megawatts until the end of November 2027. This makes Maine the first US state to legislate against large-scale data center construction.

What does 20 megawatts signify? It equates to the electricity consumption of 20,000 households. A medium-sized data center typically consumes between 5 and 50 megawatts. Maine's bill targets large data centers, reflecting deep-seated concerns from local environmental groups and lawmakers about “energy competition”: high-energy-consuming data centers could inflate residential electricity costs and crowd out electricity resources for civilian use.

Notably, the tech industry did not remain silent. They argued that data centers would generate jobs, tax revenue, and investment, offsetting the decline of traditional industries in the region. However, the legislative outcome indicates that local governments prioritize “balancing livelihoods and industry” over “prioritizing investment attraction.”

Maine's move sets a precedent, with more US local governments likely to follow suit with similar energy consumption control policies. For AI companies, this means selecting data center locations will become increasingly challenging.

The Underlying Logic of the “Double Dilemma”

Viewed together—OpenAI's suspension of its UK project and Maine's legislative ban on data center construction—a clear pattern emerges: global AI infrastructure is under a “double squeeze” from rigid energy cost constraints and stricter regulatory policies.

In recent years, tech giants have aggressively deployed AI computing power globally, adhering to a simple logic—build data centers where demand and markets exist. However, this logic is now being upended. Rigid energy cost constraints mean AI supercomputing centers can no longer be built “on a whim,” and stricter regulatory policies have significantly increased investment return uncertainties.

The UK and US cases are not isolated. The EU's AI Act imposes stricter compliance requirements on AI companies, while copyright legislation uncertainties increase legal risks in using training data. For AI giants pursuing global deployment, “stability” is becoming as crucial a location parameter as “performance.”

■ Global Computing Power Landscape Reshuffled: China's Strategic Window Period

China's “Proactive Deployment” in Computing Power Policy

Against the backdrop of a global AI infrastructure “cooldown,” China is leveraging unique policy advantages. Since 2026, China has introduced a series of stringent policies, establishing the world's most comprehensive regulatory and support system for computing power.

The most symbolic policy is the “80% Green Electricity” mandate. The National Data Administration explicitly requires newly built and expanded data centers in the eight “East Data West Computing” hub nodes to have a green electricity consumption ratio of ≥80%, with green certificates as the sole accounting voucher, and implements a “one-vote veto”—projects failing to meet this standard will not receive energy consumption approval and will be prohibited from grid connection. This requirement has evolved from a “target” in 2023 to an “entry threshold” in 2026, eliminating the possibility of companies “cutting corners.”

The PUE (Power Usage Effectiveness) tiered thresholds are equally stringent. Western smart computing centers must have a PUE ≤ 1.20, eastern centers ≤ 1.25, and newly built large-scale data centers ≤ 1.1—far below the national average of 1.38. PUE represents the ratio of total data center energy consumption to IT equipment energy consumption, with lower values indicating higher energy efficiency. A PUE of 1.1 means that for every 1 kWh of electricity consumed, only 0.1 kWh is used for non-IT equipment such as cooling and lighting.

“Computing-Electricity Synergy” is a more forward-looking initiative. The 2026 government work report included “computing-electricity synergy” in new infrastructure projects for the first time, promoting deep integration of computing power and the power system through direct green electricity supply and integrated source-grid-load-storage systems to achieve “strengthening computing with electricity and promoting electricity with computing.”

China's policy design rationale is clear: instead of making passive adjustments after problems arise, it sets high standards and strict requirements in advance to drive industry upgrades. This “proactive deployment” approach has positioned China advantageously in the global computing power competition.

“Natural Advantages” in Energy Endowment

China's western provinces (Inner Mongolia, Guizhou, Gansu, Ningxia, etc.) boast vast wind, solar, and hydroelectric resources, providing low-cost and stable energy support for the computing power industry.

The cost advantage is substantial. The direct green electricity supply price in western hub nodes is as low as RMB 0.28–0.36 per kWh, and even below RMB 0.4 in some regions, far lower than overseas markets like the UK and the US. This means that for the same computing output, operating costs in China may be only half or even lower than those overseas.

Resource matching is equally precise. The “East Data West Computing” initiative aligns eastern computing demand with western green electricity supply, avoiding the “energy mismatch + high costs” dilemma faced by overseas markets. Eastern regions have scarce land and high energy costs but significant computing demand, while western regions have abundant energy and land but lack sufficient consumption scenarios. “East Data West Computing” achieves a win-win situation.

The consumption value is even more critical. The computing power industry has become an important scenario for green electricity consumption, helping to address the issue of “wind and solar curtailment” in the west. Wind and solar power generation are intermittent and volatile, with nighttime wind curtailment and daytime solar curtailment being common. However, if data centers are built alongside, this “wasted” electricity can be “consumed,” forming a virtuous cycle of “computing power + green electricity.”

“Full-Chain Advantages” in Industrial Support

At the equipment and technology level, China has formed a complete industrial chain. In areas such as liquid-cooled servers, intelligent temperature control, and data center infrastructure, leading companies have reached international advanced levels. Tech giants like Tencent, Alibaba Cloud, and Huawei have achieved advanced PUE levels of ≤1.06, with some projects even below 1.1.

In terms of implementation experience, hub clusters such as Gui'an and Horingear have built large-scale computing centers with green electricity accounting for over 90%, forming a replicable “computing-electricity synergy” model. These cases provide templates for nationwide promotion and prove the feasibility of the “Chinese approach.”

In terms of policy support, various regions have introduced support policies such as “computing vouchers” and energy-saving retrofit subsidies to reduce enterprise landing costs and accelerate the aggregation of the computing power industry. For example, Inner Mongolia not only offers low electricity prices but also provides tax incentives and land guarantees, creating a complete business environment.

■ Industrial Opportunities: Three Key Sectors Enter a Golden Period

1. Green Electricity Sector: From “Passive Consumption” to “Active Supply”

The obstacles faced by overseas AI infrastructure essentially highlight the unsustainability of high-energy-consumption models. This will directly benefit China's green electricity industry, driving a shift from “passive consumption” to “active supply.”

Rigid demand is surging. According to data from the China Academy of Information and Communications Technology, China's data centers consumed approximately 200 billion kWh of electricity in 2025, accounting for about 2% of total societal electricity consumption. With the rigid requirement of 80% green electricity, new computing power projects will directly drive significant growth in green electricity consumption. Based on an average annual increase of 500,000 kW in computing power and 8,000 operational hours per year across the eight hub nodes, the annual new green electricity demand would be approximately 40 billion kWh.

Business models are accelerating innovation. Direct green electricity connections and aggregated green electricity supply will become mainstream models. Western green electricity resources will be continuously transmitted eastward through “computing power corridors,” opening up new space for green electricity consumption. More and more energy companies will realize that instead of struggling to sell electricity on spot markets, they can sign long-term agreements with computing power companies to secure stable orders.

Policy dividends continue to be released. Computing-electricity synergy policies promote deep binding of green electricity and computing power, providing green electricity companies with stable long-term agreements and enhancing profit certainty. For wind and solar operators, computing power customers are becoming new “prized assets.”

2. Energy Storage Sector: From “Supporting Role” to “Standard Configuration”

Energy storage is the “stabilizer” for green electricity and a “standard component” for computing power infrastructure.

Rigid supporting demand is rising. Given the intermittency of green electricity, computing centers need energy storage to achieve “peak shaving and valley filling” and ensure stable computing operations. Energy storage has shifted from a past “optional accessory” to a “must-have.” Especially in regions with significant electricity price fluctuations, the value of energy storage is even more pronounced.

Technological iterations are accelerating. Liquid-cooled energy storage, compressed air energy storage, and other technologies are being rapidly implemented, improving energy storage efficiency and safety while reducing overall costs. By 2025, energy storage cell prices had dropped by over 60% compared to 2022, significantly improving economic viability. In 2026, as scale effects further materialize, energy storage costs are expected to continue declining.

Policy support is intensifying. Computing-electricity synergy pilots explicitly encourage the integrated construction of energy storage and computing centers, with local governments providing additional subsidies to reduce enterprise investments. In regions like Inner Mongolia and Gansu, the co-construction of energy storage projects and data centers has become the norm.

3. Computing Power Network Sector: From “Decentralized Layout” to “Regional Aggregation”

Global AI computing resources will accelerate their aggregation in China, especially in western hub nodes with green electricity and compliance advantages.

The reshaping of the landscape is accelerating. Obstacles in overseas computing power deployment are leading to a reconfiguration of global AI computing resources. Leveraging its policy stability, low energy costs, and mature industrial support, China is expected to accommodate more international computing demand. Western nodes such as Gui'an, Ulanqab, Horingear, and Zhongwei are becoming significantly more attractive.

The division of labor is becoming increasingly specialized. The eastern region will concentrate on low-latency computing and AI applications, while the western region will handle high-energy-consuming computing training and data storage, thereby establishing a “coordinated east-west, nationwide” computing power framework. This division is not merely a “transfer of outdated capacity” but a strategic alignment based on comparative advantages.

Technological advancements are accelerating. The intelligent scheduling of computing power networks and the collaboration between cloud, edge, and end devices are being swiftly implemented, enhancing computing efficiency and reducing overall energy consumption. By 2025, a national integrated computing power network had started to materialize, and by 2026, cross-regional scheduling channels are expected to be further expanded.

■ Comparison and Insights: China's Comparative Strengths

Differences in Policy Approaches

The attitudes of the UK and the US toward AI infrastructure reveal a distinctly “market-oriented” stance—governments seldom intervene, leaving decisions to enterprises. However, the drawback of this model is that when energy costs rise and regulatory environments worsen, companies can only respond by withdrawing or shelving projects, effectively “voting with their feet.”

China's approach differs significantly. The government takes a proactive role in planning and deployment, guiding the orderly development of the computing power industry through national-level strategies like “East Data West Computing.” Although less flexible than a purely market-oriented model, this “planning-first” strategy exhibits greater resilience in addressing systemic risks.

Differences in Energy Strategies

The UK's challenge lies in its high and volatile energy costs. Expensive industrial electricity, lengthy grid connection processes, and low proportions of green electricity collectively place the UK at a competitive disadvantage in the AI computing power race.

Maine, in the US, has taken an opposite approach—restricting data center construction due to concerns over energy competition. While this “one-size-fits-all” policy safeguards civilian electricity use, it also somewhat stifles industrial development.

China's strategy emphasizes “balance”—promoting green and efficient industry development through stringent policies such as green electricity ratios and PUE controls, while achieving precise energy supply-demand matching through initiatives like “East Data West Computing.” This “combination of facilitation and restriction” approach is more sustainable.

Differences in Industrial Ecosystems

Globally, China stands out as one of the few countries with a complete computing power industrial chain. From chips to servers, data centers to network equipment, and software to applications, China possesses the corresponding industrial foundations. This full-chain advantage endows China with stronger risk resilience in the face of external shocks.

The UK's issue is its fragmented industrial support. It relies on imports for chips and equipment, and while it boasts talent, it falls short in supporting a complete industrial chain. The US, despite its technological edge, grapples with escalating energy and regulatory constraints. China's strength lies in its stable policies, low energy costs, and comprehensive industrial support—all three are crucial.

■ Opportunities Amidst Challenges

OpenAI's decision to suspend the UK “Stargate” project and Maine's legislative ban on large-scale data center construction may appear as “local issues,” but they actually serve as warning signals marking a new phase in global AI infrastructure development. Stringent energy cost constraints and tighter regulatory policies are reshaping the fundamental logic of global computing power distribution.

For China, this presents both challenges and opportunities.

The challenge lies in the need to continually enhance technological capabilities to meet increasingly stringent environmental and energy consumption standards. The opportunity lies in leveraging its three major strengths—policy coordination, energy resources, and industrial support—to secure a more advantageous position in the global computing power competition.

The author believes that the next 3–5 years will be a pivotal period. China's computing power companies should focus on three key directions:

First, greening. Actively deploy energy-saving technologies and green electricity support to comply with new energy consumption and green electricity regulations. A PUE below 1.1 and green electricity ratios exceeding 80% will become standard requirements.

Second, regionalization. Concentrate on western regions abundant in green electricity and East-West Computing hubs to reduce costs and policy risks. “West Computing for East Use” will emerge as the mainstream model.

Third, collaboration. Strengthen cooperation with energy and power companies to forge an integrated ecosystem of 'computing power + green power + energy storage'. It is challenging for a single company to navigate the complex multi-party landscape, and forming ecological alliances is the way forward.

The reconfiguration of the global computing power landscape has just commenced. In this competition devoid of physical conflict, China has already gained a favorable foothold. However, its ultimate success hinges on policy execution and industrial development in the years ahead.