Siemens and Reinhausen are advancing solid-state transformer development to support 36 kV to 800 VDC conversion for high-density AI data centers. This strategic move reflects the growing commercial demand for controllable medium-voltage power electronics driven by the massive power requirements of modern AI infrastructure.
Overview: The Shift to Controllable Power-Conversion Nodes
Siemens AG and Reinhausen announced in August 2026 their joint development of a solid-state transformer (SST) targeting grid voltages up to 36 kV with an 800 VDC output for AI-ready data centers. This strategic move underscores a broader industry transition. Solid-state power transformers are evolving from simple voltage-conversion components into controllable power-conversion nodes. These advanced nodes integrate voltage transformation, power-quality management, and bidirectional energy flow, addressing the complex intersection of grid capacity, physical footprint, and direct current requirements.
Technical Details: 36 kV to 800 VDC Architecture
The collaboration between Siemens and Reinhausen focuses on industrializing an SST capable of handling up to 36 kV grid voltages while delivering an 800 VDC output. This specific architecture aligns with the market's leading conversion topology, the AC-DC-DC-AC modular design, which holds a 39.0% market share in 2026. Furthermore, the reliance on Silicon Carbide (SiC) MOSFETs, commanding a 45.0% share in the semiconductor segment, highlights the industry's push for higher efficiency and power density. However, transitioning from pilot projects to commercial deployment requires overcoming significant technical hurdles. Suppliers must rigorously address insulation design, fault behavior, protection coordination, semiconductor thermal performance, and comprehensive utility documentation to ensure grid compatibility and operational safety.
Market Context: A USD 8.8 Billion Trajectory
The global solid-state power transformers market is on a robust growth trajectory, projected to surge from USD 1.5 billion in 2026 to USD 8.8 billion by 2036, reflecting a compound annual growth rate of 19.6%. The market, which reached USD 1.2 billion in 2025, is expected to generate a USD 7.3 billion absolute opportunity over the decade. Geographic momentum varies significantly across key regions. France leads with a forecasted 24.1% CAGR through 2036, driven by aggressive grid investment and charging infrastructure expansion. Germany follows closely at 22.5%, combining power-line expansion with a large fast-charging base. The United Kingdom, Japan, and the United States are projected to grow at 16.0%, 15.1%, and 14.1%, respectively. This disparity indicates that SST adoption will not follow a uniform global timetable, heavily depending on local grid approval requirements, charging density, and power demand.
Industry Impact: EV Hubs and Grid Modernization
Beyond data centers, EV charging hubs represent a primary demand driver, projected to capture 27.0% of market demand in 2026. These hubs benefit immensely from medium-voltage-to-DC conversion, which reduces intermediate equipment and alleviates severe space constraints. The competitive landscape is highly active and diverse. Eaton currently markets a medium-voltage SST boasting over 97% conversion efficiency at 800 VDC output. Meanwhile, GE Vernova stated in April 2026 that its SST investment remains on track, with the first product slated for delivery to a hyperscaler in fall 2026 for approximately six months of testing. Additionally, ABB invested in DG Matrix in March 2025 to collaborate on SST solutions tailored for AI data centers and other critical applications.
Implications for AI Data Centers
For AI-ready data centers, the industry shift toward 800 VDC architectures is necessitating a fundamental reevaluation of power infrastructure. Higher rack power densities demand compact, highly reliable power-conversion systems. The Siemens and Reinhausen initiative directly targets this critical niche, aiming to eliminate the bulky, inefficient legacy conversion stages. By providing a direct 36 kV to 800 VDC pathway, SSTs can drastically reduce the physical footprint of power delivery systems within the data center. This controllable conversion also enhances power-quality management, a critical factor for the sensitive, high-load computing equipment utilized in modern AI training and inference clusters, ensuring uninterrupted operations and optimal energy utilization.
Future Outlook: From Prototypes to Field Qualification
As noted by Fact.MR analysts, the next phase of the SST market will heavily favor platforms that can demonstrate proven field performance rather than relying on mere prototypes. Technical qualification is becoming just as critical as raw converter efficiency. The transition from laboratory demonstrations to widespread commercial deployment hinges on resolving medium-voltage hardware challenges, integrating advanced SiC power modules, and finalizing robust protection controls. As EV charging, distribution grids, and renewable microgrids continue to intersect with the massive power requirements of AI infrastructure, the solid-state transformer is poised to become a foundational, controllable element of the modernized, decentralized global power grid.