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Energy Vault Secures 1.25 GW Texas AI Power Contract

Energy Vault announced on August 7 a commercial agreement to supply 1.25 GW of integrated, off-grid power infrastructure for a hyperscaler AI data center in Texas, projecting $500 million to $600 million in revenue impact across the second half of 2026 and 2027. The deployment combines battery energy storage, grid-forming power conversion systems, Caterpillar generator sets, and control software, with initial deployments expected within four to 12 months. CEO Robert Piconi called it the company's largest single contract to date.

read4 min views1 publishedAug 10, 2026
Energy Vault Secures 1.25 GW Texas AI Power Contract
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On August 7, Energy Vault announced a commercial agreement to supply 1.25 GW of integrated, off-grid power infrastructure for a hyperscaler AI data center in Texas. The deployment combines battery energy storage, grid-forming power conversion systems, Caterpillar generator sets, and control software, according to the company's release. Energy Vault projects $500 million to $600 million in revenue impact across the second half of 2026 and 2027.

Energy Vault announced on August 7 that it has secured an agreement to supply 1.25 GW of integrated power infrastructure for an unnamed hyperscaler AI data center project in Texas. The initial deployment is backed by a hyperscaler customer contract, according to the company's BusinessWire release, although Energy Vault, the data center developer, and the engineering, procurement, and construction partner have not publicly identified the customer or EPC firm.

The agreement covers battery energy storage systems, or BESS, grid-forming power conversion systems, and AI infrastructure control software. Energy Vault's release describes the architecture as an off-grid system combining dispatchable generation, battery storage, inverter systems, plant integration, and digital controls. The announcement also identifies Caterpillar generator sets as part of the power-generation configuration.

Data Center Dynamics described the transaction as Energy Vault's largest contract to date. Energy Vault chairman and CEO Robert Piconi said: "As our largest single contract executed to date, this milestone agreement represents another important step in Energy Vault's strategic evolution from an energy storage technology pioneer into an integrated energy infrastructure provider."

Off-grid capacity targets interconnection delays

Initial deployments are expected within four to 12 months, according to Energy Vault. The company stated that the off-grid design is intended to bring AI compute capacity online without waiting for conventional utility interconnection schedules.

That timing matters in Texas, where large-load interconnection demand has become a material constraint. ESS News reported that Texas Governor Greg Abbott cited 474 GW of grid-connection requests, with data centers representing 90% of those requests, while noting that not all proposed projects are expected to be completed. The same report noted that interconnection queues in some US markets can extend for five years or more.

The Energy Vault system is designed to coordinate generation, storage, and on-site electrical equipment in real time, according to the company. Data Center Dynamics reported that Energy Vault claims its monitoring platform can balance power flows, maintain voltage and frequency stability, reduce generator cycling, improve fuel efficiency, and respond rapidly to fluctuating AI-compute loads. These are operational claims from the company, rather than independently reported performance results.

Grid-forming power electronics are relevant in this configuration because they can establish voltage and frequency reference signals in an isolated power system, unlike grid-following inverters that rely on an existing utility grid reference. In data center settings, combining such controls with batteries and generators can provide a way to manage rapid changes in load while maintaining local power quality.

Revenue and compliance details

Energy Vault expects the agreement to contribute approximately $500 million to $600 million in revenue during the second half of 2026 and 2027, according to its release. Seeking Alpha separately reported the same projected revenue range following the announcement.

The company also described the battery system as compliant with Foreign Entity of Concern, or FEOC, requirements. ESS News reported that FEOC compliance is becoming a standard consideration for US projects seeking federal incentives.

Energy Vault has previously announced data center-related work in Texas. Data Center Dynamics reported that the company has an 8 MW project in Snyder, Texas, in partnership with Crusoe, with a possible expansion to 25 MW in a second phase. The newly announced 1.25 GW agreement is substantially larger, although its specific site, generation mix, storage duration, and commercial counterparties remain undisclosed.

For data infrastructure teams, the deal illustrates a broader industry response to constrained grid interconnection: large AI campuses are increasingly evaluating integrated generation, storage, power electronics, and controls as a single deployment problem. Such architectures can reduce dependence on utility-connection timing, but their practical economics and reliability depend on factors that have not been disclosed here, including generator fuel supply, battery duration, load profile, permitting, and operations arrangements.

Key Points #

  • 1Energy Vault's 1.25 GW Texas agreement combines storage, grid-forming conversion, generation, and software to support an unnamed hyperscaler AI data center.
  • 2The company projects $500 million to $600 million in revenue across late 2026 and 2027, making this its largest reported contract.
  • 3Comparable off-grid AI campus designs can reduce exposure to interconnection queues, while introducing operational dependencies on generation, storage duration, and fuel logistics.

Scoring Rationale #

A 1.25 GW power-infrastructure agreement is a notable development in the physical buildout supporting hyperscale AI compute. The deployment is particularly relevant to practitioners and infrastructure leaders facing power-availability constraints, though the end customer, site details, and performance specifications remain undisclosed.

Sources #

Primary source and supporting public references used for this report.

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