As AI racks approach megawatt-scale power densities, Meir Adest, Co-Founder and VP Core Technologies at SolarEdge, explains why DC-native energy architecture is becoming increasingly difficult for data centre operators to ignore.

AI is reshaping the data centre landscape at extraordinary speed. Hyperscale operators are racing to deploy infrastructure capable of supporting increasingly power-hungry workloads, with more than 100 GW of new AI data centre capacity expected globally between 2026 and 2030.

At the heart of this shift is a fundamental change in compute density. Traditional server racks typically operate at around 10 kW. Today, AI racks are approaching 1 MW, representing a two-order-of-magnitude increase in power demand within the same physical footprint. This escalation is exposing a constraint that has, until now, remained largely invisible: the limitations of the underlying energy architecture in sustaining future demand.

The limitations of AC infrastructure

Despite the digital nature of modern computing, the energy systems powering data centres remain rooted in a model developed more than a century ago. Alternating current (AC) became the standard because it enabled efficient long-distance transmission at a time when direct current (DC) could not.

However, every core component inside a data centre, from GPUs to batteries, fundamentally operates on DC power. As a result, today’s infrastructure relies on a continuous cycle of conversions: AC from the grid is stepped down, converted to DC for storage, inverted back to AC for distribution and, finally, converted again to DC at the chip level.

This process introduces a ‘conversion tax’: between 10% and 30% of incoming energy can be lost before it reaches the compute load. Crucially, these losses create a double penalty. Energy lost as heat must be actively removed by cooling systems, requiring additional energy consumption.

In an era when power availability is becoming a limiting factor for data centre expansion, every percentage point of efficiency matters. Each incremental loss represents not only reduced compute capacity from a fixed grid connection, but also a substantial financial impact at scale. Across gigawatt-class facilities, even a single percentage point of inefficiency can translate into millions in lost value, reinforcing the need to maximise the proportion of energy that reaches the processors themselves.

In an era where power availability is becoming a limiting factor for data centre expansion, every percentage point of efficiency matters. Each incremental loss represents not only reduced compute capacity from a fixed grid connection, but also substantial financial impact at scale. Across gigawatt-class facilities, even a single percentage point of inefficiency can translate into millions in lost value, reinforcing the need to maximise the proportion of energy that reaches the processors themselves.

Why AI is driving a move to DC

Historically, these inefficiencies were tolerable. Rack densities were low enough for energy losses to be absorbed without fundamentally constraining performance. AI changes this calculation.

With racks approaching megawatt scale, the physical and thermal limits of AC infrastructure are being reached. NVIDIA and other technology companies are now advocating for 800V DC architectures as a means of supporting megawatt-scale racks.

The rationale is straightforward. Higher-voltage DC systems enable lower current for the same power delivery, reducing resistive losses and allowing significantly more power to be transmitted through existing conductors. In practical terms, 800V DC can deliver more power while reducing copper usage, installation complexity and cost. However, implementing it requires a fundamental redesign of how energy is delivered within the data centre.

Mapping the transition from AC to DC

The transition to DC-native architecture is not a single step, but a staged evolution. Today, most data centres operate in what can be described as Stage 0, where power is distributed entirely in AC, with DC conversion occurring only at the point of use.

Stage 1 introduces targeted improvements through retrofits such as sidecar solutions, enabling the introduction of 800V DC racks and resulting in system efficiencies of between 85% and 93%. While valuable, these approaches are widely viewed as interim measures.

A more significant shift occurs with Stage 2, where elements of the infrastructure, mainly the UPS systems, begin to operate on DC. This hybrid approach removes unnecessary conversions, allowing system efficiency to rise to between 91% and 96%.

Stage 3 represents the move towards a fundamentally DC-native data centre. Here, traditional transformers are replaced by solid-state transformers that convert medium-voltage AC directly to DC. This simplifies the power chain and can enable efficiencies of between 94% and 97%.

Stage 4 builds on this with a fully integrated DC architecture, combining advanced solid-state transformers connected directly to 34.5 kV grids, DC-based UPS systems and intelligent energy management. At this stage, total system efficiencies could approach 98%, increasing the proportion of incoming power available for compute.

While some operators will progress incrementally, leapfrogging intermediate stages may, in some cases, prove more cost-effective and operationally simpler. For data centres being planned today, designing for 800V DC may be more effective than preparing to retrofit the architecture at a later stage.

The role of solid-state transformers

At the core of this transition is the solid-state transformer (SST). Unlike conventional transformers, which are typically large, site-specific and limited in functionality, solid-state transformers are intended to integrate conversion and control into a single, modular system. They are designed to connect directly to medium-voltage grid infrastructure and deliver high-voltage DC in a single step, eliminating multiple layers of conversion.

Advances in semiconductor materials, particularly silicon carbide, are enabling SSTs to operate at higher voltages with lower switching losses, improving efficiency and performance.

Beyond efficiency gains, solid-state transformers can offer additional advantages. Their modular design could support faster manufacturing and deployment than traditional bespoke transformers, reducing lead times and enabling a quicker transition to operation. Built-in redundancy at the module level can also enhance system resilience and reduce reliance on a single point of failure.

However, technical challenges remain. Although 800V DC architecture already exists in utility-scale solar installations and electric vehicles, implementing it in SSTs presents a significant engineering challenge. Directly interfacing with grid-level voltages, such as Europe’s 33 kV grid or the 34.5 kV grid in the US, without intermediate conversion stages is complex and requires considerable expertise in DC energy architecture.

Implications for the grid

The benefits of DC architecture extend beyond the data centre itself. As power demand from AI infrastructure grows, concerns around grid capacity and stability are intensifying. In many regions, access to sufficient power is already limiting data centre expansion.

By improving energy efficiency, DC-native systems enable operators to extract more compute from the same grid connection, reducing the need for additional capacity. Lower losses also translate into reduced cooling requirements, further easing overall energy demand.

In addition, integrating DC-based energy storage and intelligent control systems should allow data centres to interact with the grid more dynamically. DC UPS systems, for example, can act as a buffer, smoothing demand fluctuations and mitigating the impact of sudden load changes.

Overcoming barriers to adoption

Despite the potential benefits, the transition to DC is not without challenges. First, there is the question of infrastructure change. Moving beyond early-stage retrofits requires the replacement of key components within the power chain, which can be complex.

Second, regulatory frameworks for DC systems are not yet fully mature. Standards for safety, certification and operation are still being developed, particularly for higher voltage levels.

Finally, there is a skills gap. Designing and deploying DC-native systems requires specialist expertise that is not yet widespread across the industry. However, these challenges are typical of any major technological shift, and work on standards, products and skills is already under way.

The transition timeline

The transition is beginning to take shape. The industry is expected to see prototype and early pilot deployments of DC architectures and solid-state transformers during 2026. By 2027, SSTs are expected to begin reaching commercial availability, with initial commercial projects following. From 2028 onwards, as megawatt-scale AI racks become more widely deployed, DC infrastructure will need to scale rapidly to meet demand.

Looking further ahead, the industry is already considering a future transition to 1,500V DC systems. While this could offer additional efficiency gains, it would also introduce new technical and safety challenges that would need to be addressed through further innovation and standardisation.

The direction of travel

As AI continues to push the boundaries of power density, the limitations of traditional infrastructure are becoming more apparent. DC architecture offers a potential path to higher efficiency, greater scalability and closer alignment with the needs of next-generation workloads.

The question is increasingly not whether this transition will happen, but how quickly the industry can execute it. Data centres are among the first sectors to face this challenge at scale, but they are unlikely to be the last. As the technology matures, the shift towards DC-native energy systems could become more widespread.