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Data Center Knowledge 数据中心行业· Drew Robb·· 18 天前AI 评分87

「英中对照」谷歌披露电网互动型AI数据中心能源与设施技术路线

Google’s Grid-Interactive AI Data Centers: From Backup to Grid Partner

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谷歌在2026年休斯敦数据中心世界电力大会上,披露了适配年增7倍算力需求的电网互动型AI数据中心全栈技术布局。当前其方案涵盖将备用电池储能转化为电网支撑资源、54V机架级电池备用、液冷、闭环制冷等设计,官方称减少冗余供电转换环节可提效约1.5%。谷歌正推进800VDC配电、固态变压器等技术成熟,相关标准化设施规范将通过开放计算项目对外发布。

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Inside a Google New Albany data center buildings in Central Ohio

Inside one of Google's New Albany data center buildings in Central Ohio.Google

AI infrastructure is expanding at an unprecedented pace. Google now processes more than 3 quadrillion AI tokens per month, representing a sevenfold increase in compute demand from May 2025 to May 2026. Meeting this velocity requires innovation in energy efficiency and power delivery.

Tom Garvens, vice president of advanced technology innovation at Google, outlined this challenge during a keynote at Data Center World Power 2026 in Houston, held Sept. 21-23. He described Google’s full-stack approach to scaling AI, positioning data centers as active partners in stabilizing local grids.

Turning Backup Power into Grid Services

To bridge the speed mismatch between rapid AI rollout and multiyear timelines typical for utility capacity expansion, Google has developed energy strategies that transform backup assets into grid-supportive resources, streamline operations during peak demand, make load shaping more intelligent, and prevent disruptive power swings – while supporting utility resilience.

Related:Solid-State Transformers Power Next-Gen AI Data Centers

Beyond these strategies, Google is reviewing and redesigning the entire AI data center ecosystem – from chip to utility. This includes optimizing for liquid cooling, low-voltage direct current (LVDC) architectures, intelligent algorithms, and facility design. A core pillar of this work is publishing standardized power and facility technology specifications through communities such as the Open Compute Project (OCP), enabling the industry to build interoperable, efficient, and sustainable infrastructure.

“Google has tightly coupled vertical integration in AI along with close partnerships with energy providers,” Garvens said. “We develop and design our own data centers, chips, servers, and rack designs. By having control of our entire hardware and software stack, we can optimize these things together for sustainability and energy efficiency.”

Powering AI at Gigawatt Scale

Google is investing alongside utilities to add grid capacity. That assistance is vital as a gigawatt-class data center campus can comprise hundreds of thousands of interconnected chips running a single workload. Google’s approach is twofold: work with utility partners to streamline power delivery and adjust its own hardware and software to be more grid-friendly.

“Utilities are [setting] different requirements that we must demonstrate that we can meet,” Garvens noted. “Google, Meta, Microsoft, and Nvidia have come together to define an interface spec on how utilities and hyperscalers can interface with each other.”

Battery energy storage systems (BESS) have become critical in Google’s campus designs for onsite energy storage and for buffering rapidly fluctuating workloads. Buffering smooths power and voltage transitions. Backup generators remain in use, but diesel does not scale well to campuses at 1 GW and beyond. BESS are increasingly used to provide standby power, supported by demand-response agreements with utilities for peak shaving.

Related:How Microsoft and Google Plan and Place AI Workloads

“When peak needs are beyond what we've got power for, we can get that from local storage,” Garvens explained.

Rather than competing for constrained capacity in saturated markets, Google has been identifying remote sites with ample land and available power. The company is also considering campus developments in small towns where the data center would be a primary employer, he said.

Another design change: Google has moved away from centralized Uninterruptible Power Supply (UPS) systems, favoring rack-level battery backup operating around 54 VDC. Eliminating an extra AC-DC-AC conversion step yields approximately a 1.5% efficiency gain.

“We do all of our power conversion at the top of our racks, where we take our AC down to 54 volts, and then we run DC through our racks; our battery backup also runs at that voltage,” Garvens said.

Related:How Power Electronics Cut Generator Run Hours in AI-Scale Data Centers

Inside the Rack: 54 VDC Today, 800 VDC Tomorrow

Google has introduced changes at the chip, rack, and facility levels, supported by software that can intermix workloads to smooth overall load and make it more predictable.

Rack density remains a major challenge. Roadmaps anticipate racks approaching 1 MW each over the next year or two. That necessitates liquid cooling for at least the hotter elements within the racks.

Delivering the required current at lower voltages would demand bus bars and cabling with significantly more copper. This calls for a higher distribution voltage. Google is pursuing a gradual migration toward 800 VDC for power distribution, which is expected to take a couple of years to mature.

In the meantime, Google has implemented “sidecars” alongside its racks – adjacent power-distribution enclosures that house cabling and power gear – reserving the racks for high-density servers. The tradeoff is floor space. When 800 VDC becomes broadly available, those sidecars can be converted to additional AI server racks.

“We're working with the industry on bringing solid-state transformers to maturity,” Garvens said. “We are also continuing to improve our power usage effectiveness [PUE]. We can't ever get to 1.0, but we continue to challenge ourselves to get as close to it as possible.”

Workload Shifting and Water-Smart Cooling

With dozens of data centers in operation and many more in development, Google can be fluid about where it runs workloads. Garvens offered an example:

“If there's a heat wave in Ohio and we were running a big workload, we've got agreements in place whereby with the right amount of foresight we can shut certain workloads down or move them elsewhere if they're critical,” he said. “We have a portfolio where we can shift things around.”

Water strategy is another focus area. The company is investing in closed-loop cooling systems – sealed liquid circuits where the working fluid remains within the system and makeup water is minimized. This marks a shift from designs that consumed large quantities of water. There is no single approach; depending on conditions – altitude, humidity, water table, drought risk, and community needs – Google works with partners to determine the appropriate power capacity and the best cooling design.

“We work with our partners in terms of what's available and figure out what is the right amount of power we can get and what water usage or closed-loop design is most appropriate,” Garvens noted.

Keeping Pace with Silicon Roadmaps

Each new generation of silicon tends to draw more power, and multiple chips are arriving every year.

“The most precious thing we have is a watt: you don't want to ever strand a watt,” Garvens said. “So, making our data center and our designs as crisp as we can for as far out as we can see in these roadmaps, it's why our partnerships with our silicon and GPU design teams are so critical.”

About the Author

Drew Robb

Contributor

Drew Robb has been a full-time professional writer and editor for more than twenty years. He currently works freelance for a number of IT publications.

来源:Data Center Knowledge 数据中心行业 · datacenterknowledge.com