SolarEdge Advances Solid-State Transformer Deployment for AI Data Centers, Pilots Set for 2027

SolarEdge has completed the demonstration of a solid-state transformer (SST) prototype designed for AI data centers, with plans to finalize proof of concept by the end of 2026 and initiate pilot deployments in 2027. The company aims to capture the high-efficiency power supply market, as SST technology is expected to become a critical infrastructure for next-generation AI data centers.

Editorial Team8/12/2026Updated 8/12/2026

SolarEdge Accelerates SST Commercialization, Targets AI Data Center Power Supply Opportunities

Global solar inverter leader SolarEdge recently announced the completion of a solid-state transformer (SST) prototype demonstration tailored for AI data centers, showcasing operational results to potential clients and engineering teams. The company plans to finalize its proof of concept (PoC) by the end of 2026, followed by pilot deployments in 2027, with revenue contributions expected to begin in 2028.

In 2025, SolarEdge partnered with German semiconductor giant Infineon to develop a modular SST platform with a capacity of 2 to 5 MW. The collaboration combines Infineon’s silicon carbide (SiC) power components with SolarEdge’s power conversion control technology, aiming to achieve a conversion efficiency exceeding 99%. This platform is designed to meet the urgent demand for high-efficiency and high-reliability power supply in AI data centers.

SST Technology Emerges as New Benchmark for AI Data Center Power Supply

As AI applications rapidly expand, the power consumption of data center GPUs continues to rise, exacerbating energy losses caused by multiple AC/DC conversions in traditional alternating current (AC) power architectures. SST technology enables direct conversion from medium-voltage AC to high-voltage direct current (HVDC), eliminating the need for traditional transformers and uninterruptible power supply (UPS) systems. This not only significantly improves power supply efficiency but also increases the available computing power for GPUs. Industry experts widely regard SST as a vital power equipment for next-generation AI data centers.

AI data centers are gradually transitioning toward HVDC power architectures to address the challenges posed by escalating GPU power consumption. The adoption of SST technology is expected to resolve efficiency bottlenecks in traditional power supply systems, enabling data centers to save substantial energy costs. SolarEdge’s prototype demonstration highlights the company’s technical prowess in the SST domain and lays the groundwork for future commercialization.

Multiple Players Compete in SST Market, 2027 Marks a Critical Milestone

While SST technology remains in the early stages of commercialization, competition is intensifying. In addition to SolarEdge, power management leaders such as Eaton and GE Vernova, along with Taiwanese firms Delta Electronics and Lite-On Technology, have all invested in related technology development. Most industry players plan to initiate pilot programs or commercial rollouts in 2027, aiming to secure a foothold in the AI data center power supply market.

SolarEdge’s core business has traditionally focused on solar inverters, power optimizers, and energy management systems. However, in recent years, the company has faced declining demand in the U.S. residential solar market due to high interest rates and uncertainties surrounding tax credit policies. As a result, SolarEdge has actively expanded into emerging markets, with AI data center power solutions becoming a key strategic focus. The company’s SST technology is viewed as a new growth driver. During its latest earnings call, SolarEdge emphasized that the commercialization of SST will proceed as planned, with pilot deployments in 2027 expected to contribute meaningfully to revenue starting in 2028.

Despite the promising outlook for SST technology, commercialization still faces several challenges. No industry player has yet disclosed specific efficiency data or cost structures for SST products, and market acceptance of the new technology will require time to validate. Additionally, AI data centers demand exceptionally high reliability from power supply equipment, and whether SST can meet long-term operational stability requirements remains to be verified through real-world deployments. Industry observers anticipate that the 2027 pilot deployments will be a pivotal step in determining the success of SST commercialization.

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