Envision's 2 GW Renewable Park Shows AI Can Unlock 100% Green Power for Industry

For climate and energy professionals, the question is no longer just about adding more solar panels or wind turbines—it's about orchestrating an entirely new kind of energy system. Envision Energy's latest report, unveiled at VivaTech, argues that artificial intelligence is the missing piece to finally integrating massive renewable capacity into reliable, round-the-clock power for heavy industry and data centers.

On June 22, 2026, at the VivaTech innovation conference in Paris, Envision Energy introduced its sixth annual Net Zero Action Report, a document that seeks to redefine the role of energy infrastructure in an era increasingly dominated by artificial intelligence. The report argues that the industry must move beyond simply replacing fossil fuel generation with renewables; instead, it must engineer a "new-type power system" that tightly weaves together energy generation, storage, grid management, computing resources, and intelligent software. Envision calls this vision "AI Power Systems," a framework designed to deliver the abundant, reliable, and sustainable electricity that the AI-driven industrial revolution will demand.

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The centerpiece of the report is a practical demonstration: the Chifeng Net Zero Industrial Park in China, which operates on a 2-gigawatt, 100% renewable power base.

The centerpiece of the report is a practical demonstration: the Chifeng Net Zero Industrial Park in China, which operates on a 2-gigawatt, 100% renewable power base. At this facility, Envision has deployed its proprietary EnOS platform and an "Energy Foundation Model"—an AI system that orchestrates wind, solar, storage, computing workloads, and even green hydrogen production in real time. This integration, according to the company, enables unprecedented efficiencies by maximizing the value of every unit of green electricity and aligning limited grid capacity with the rapidly growing needs of GPU clusters. The partnership with Tencent underscores the commercial relevance, as hyperscale data center operators grapple with the dual challenge of skyrocketing electricity demands and decarbonization commitments.

Lei Zhang, Envision’s Founder and CEO, emphasized the philosophical shift: "Energy is not just the foundation of AI—it is the lifeblood of intelligence." His framing positions the power system as the core infrastructure for the intelligence age, akin to how transportation networks defined the industrial era. Such rhetoric may seem grandiose, but it reflects a growing recognition among policymakers and investors that the convergence of energy and digital infrastructure will shape economic competitiveness for decades.

The Chifeng model’s 2 GW scale is notable; it moves beyond pilot projects to a utility-scale demonstration that combines variable renewables with industrial loads and computational demand. Envision’s approach tackles a critical bottleneck: the current grid often cannot accommodate the simultaneous growth of electrified industry and data centers without massive curtailment or fossil-fuel backup. By embedding AI at every layer—from real-time weather forecasting for wind and solar output to dynamic load shifting for computing tasks—the system claims to maintain stability while running on 100% clean power.

From a market perspective, this aligns with global trends. The International Energy Agency projects that data center electricity consumption could double by 2030, with AI workloads being a primary driver. Simultaneously, governments are tightening emissions regulations and offering incentives for green industrial zones. Envision, already a major wind turbine manufacturer and energy storage provider, is leveraging its portfolio to offer an integrated "energy-as-a-service" model that could appeal to corporate buyers seeking guaranteed green power without the complexity of self-managing assets.

However, the report and the VivaTech presentation are, by nature, promotional. Independent validation of the Chifeng park’s performance metrics—its capacity factors, uptime, and cost-effectiveness compared to grid alternatives—will be crucial for broader adoption. The concept of an "Energy Foundation Model" also raises questions about data transparency, cybersecurity risks in converged infrastructure, and the replicability of the model in markets with less mature renewable deployment.