Zeo & Creekstone: How to Power Delta Gigasite AI Data Centre

2026-03-04 · Source: AI Magazine · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

Zeo Energy has partnered with Creekstone Energy to develop approximately 280 MW of solar and storage capacity for Creekstone's "Delta Gigasite" AI data center campus in Utah, which is projected to become the "world's largest AI-optimised data centre campus" with an eventual 10 GW power capacity. Creekstone's "gigasite," breaking ground in December 2025 and aiming for 300 MW of gas-powered capacity by early 2027, addresses the unprecedented power demands of AI workloads. Zeo Energy, having acquired Heliogen in August 2024, will leverage its long-duration energy storage expertise to provide uninterrupted renewable power, with a pre-feasibility study underway to optimize the solar and storage configuration. This collaboration, including Zeo potentially providing engineering and financing, aims to deliver cost-effective, low-emissions baseload power to hyperscalers and AI data center customers like Blue Sky AI, which has been allocated 50 MW. The project exemplifies the future of AI infrastructure, purpose-built for computational demands while integrating sustainable energy solutions.

Key takeaway

Creekstone Energy is developing the "Delta Gigasite" in Utah, projected to be the world's largest AI-optimized data center campus with a 10 GW power capacity. This campus integrates a 280 MW solar and long-duration storage solution from Zeo Energy, leveraging thermal/chemical storage to provide reliable, clean baseload power for AI workloads. This initiative directly addresses the critical need for scalable, sustainable infrastructure to support the exponential growth of advanced AI deployments.

Topics

• AI Data Centers
• Renewable Energy Integration
• Long-Duration Energy Storage
• Creekstone Energy Gigasite
• Zeo Energy Partnership

Best for: Investor, CTO, VP of Engineering/Data, AI Architect, MLOps Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.