Envision Deploys SST-Based 800V DC Power at Ulanqab AI Data Center – Unite.AI

Envision said on November 2, 2026, that an integrated 800-volt direct current (800V DC) power system is now powering real-time computing workloads at its Galaxy AI data center campus in Ulanqab, China, a deployment the company described in its announcement as the world’s first commercial use of such a system in a large-scale AI data center.

The announcement states that the system provides power end-to-end, from medium voltage AC input to the server rack, and is already commercially operational ahead of broader industry adoption, providing a reference for AI data centers transitioning to 800V DC power infrastructure.

Solid-state transformers and real-time coordination

The newly implemented system integrates three hardware layers: solid-state transformers (SSTs), battery energy storage (BESS), and equipment that regulates direct current voltage for the computing hardware. Coordinating them is Envision’s Dubhe Controller, which works with the company’s Dubhe Energy Foundation Model and regulates the transformers and batteries in real time so that the power supply tracks computing demand, including sudden load swings.

According to Envision, the implementation is based on three capabilities: stable SST conversion directly from 10 kilovolt medium voltage to an 800 V DC bus under all operating conditions; battery storage that provides both second-scale power support and small-scale backup; and millisecond-level coordination between SST and storage that locally absorbs GPU load fluctuations.

Envision said the 800V DC architecture simplifies AI data center power systems, citing greater power conversion and watt-bit efficiency, a more compact equipment footprint, and reduced cabling and copper requirements. Those benefits, the company said, can reduce infrastructure costs and support higher computing density within the same space.

Increasing power demand per rack

The announcement frames the deployment in relation to a specific operational problem: As demand for AI computing accelerates, operators must provide more power to each rack within a confined space while keeping supply stable as computing loads fluctuate sharply from moment to moment.

“AI data centers need power systems that coordinate renewable energy, energy storage and the grid to meet computing demand,” said Kevin Huang, Senior Vice President of Envision Energy and President of Energy Storage and AIDC Power Systems. Huang said the live system demonstrates an end-to-end architecture that connects renewable supply with computing demand, calling it a critical step in moving energy-computing coordination from strategic vision to daily operational practice.

Galaxy Campus and Gobi Mission

The Galaxy campus, in Ulanqab, Inner Mongolia, began operations in August 2026, when Envision commissioned the site on Aug. 6, anchored by a 120,000-square-meter AI supercomputing facility, according to the company’s commissioning announcement at the time. That record described the campus as designed to reach a capacity of more than 2 GW; the November 2 release states a planned capacity of 3 GW and says the campus is designed to support up to one million AI accelerators operating in parallel at full capacity, with more than 80% of its expected power coming from direct connections of renewable electricity.

Envision’s Galaxy campus page markets the site as a carbon-neutral AI data center, advertising long-term fixed electricity prices at 20% below grid rates with a 10-year price lock, bundled electricity and green certificates, and a 60% green energy direct supply ratio.

Envision said it aims to scale up the approach through Mission Gobi, an initiative unveiled at VivaTech in Paris in June 2026 with Galaxy as its first flagship project. Mission Gobi is aiming for 5GW of green AI data center capacity in desert regions around the world by 2030, and the company presents this as a replicable project, arguing that developing even 1% of global desert and Gobi regions could support terawatt-scale computing capabilities at highly competitive costs.