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Schneider Electric and ETAP have introduced a digital twin that helps to enhance the accuracy of power system design and simulation for AI Factories. Using the NVIDIA Omniverse™ Blueprint for AI factory digital twins, this collaboration helps to enable the development of digital twins that integrate multiple inputs, including mechanical, thermal, networking, and electrical systems, to simulate AI Factory operations. The collaboration is set to help AI Factory design and operations by providing enhanced insight and control over electrical systems and power requirements, offering potential efficiency, reliability, and sustainability benefits.
Key Features and Benefits
Comprehensive AI Factory Digital Twin: Integrates ETAP and NVIDIA Omniverse technologies to create a dynamic virtual model where multiple system interactions are analyzed.
Electrical Infrastructure Modeling: Uses ETAP’s modeling technology to develop a virtual replica of a data center’s electrical system, combining real-time power data, analytics, and insights.
Intelligent Power System Analysis: Predicts power consumption and distribution patterns through advanced algorithms.
Operational Enhancements: Provides capabilities such as:
More advanced electrical system design and simulation
Dynamic “What-If” scenario analysis
Real-time electrical infrastructure performance tracking
Enhanced energy efficiency optimization
Predictive maintenance and system reliability assessment
Infrastructure planning based on power usage to reduce total cost of ownership
Addressing AI’s Growing Power Demands
AI workloads, from large-scale training clusters to edge inference servers, are driving increased power consumption in data centers.
Unlike traditional computing, AI model training and complex inference tasks require significantly more computational power, leading to higher rack power densities.
Data center operators must rethink design and management strategies to further optimize power efficiency and reliability.
“Grid to Chip” Power Management Approach
ETAP and NVIDIA’s collaboration helps to enhance power management, performance optimization, and energy efficiency in AI Factories.
Traditional power estimation methods focus on average consumption at the rack level, while ETAP’s digital twin helps to enable more precise modeling down to the chip level.
This approach helps to improve power system design and optimize energy efficiency, supporting the evolving needs of AI-driven infrastructure.
Industry Impact and Future Outlook
The collaboration highlights ongoing efforts to help improve data center efficiency while enhancing grid reliability and performance.
By leveraging digital twin technology, Schneider Electric and ETAP are working to help enable smarter, more sustainable AI infrastructure management.
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