Schneider Electric and ETAP have unveiled a cutting-edge digital twin that can accurately design and simulate the energy needs of AI factories. Leveraging the NVIDIA Omniverse™ Blueprint for AI Factory Digital Twins, Schneider Electric and ETAP are enabling the development of digital twins that integrate multiple inputs for mechanical, thermal, network, and electrical systems to simulate how an AI factory operates. This collaboration is poised to transform the design and operation of AI factories. While basic visualization of electrical systems was previously possible, the integration of ETAP and NVIDIA Omniverse technologies enables the creation of a complete AI Factory digital twin where multiple dynamics interact seamlessly. ETAP's modeling technology will create a virtual replica of a data center's electrical infrastructure and combine it with real-time electrical system data, advanced analytics, and insights. Intelligent algorithms analyze and predict energy consumption and distribution patterns, providing unprecedented information on:
Advanced design and simulation of electrical systems.
Dynamic analysis of "what if" scenarios.
Real-time monitoring of electrical infrastructure performance.
Advanced optimization of energy efficiency.
Predictive maintenance and system reliability assessment.
Infrastructure needs based on energy usage that can help reduce total cost of ownership.
From large-scale training clusters to inference servers, AI workloads are driving a significant increase in data center energy consumption. Unlike traditional computing tasks, AI operations—particularly model training and complex inference processes—require substantial computing power, leading to higher rack power densities. As AI adoption accelerates, startups, enterprises, colocation providers, and internet giants must rethink data center design and management to address the growing need for energy efficiency.
The collaboration between ETAP and NVIDIA introduces a "Grid to Chip" approach that addresses the challenges of power management, performance optimization, and energy efficiency in the AI era. Currently, data center operators can estimate average power consumption at the rack level, but ETAP's new digital twin aims to increase the accuracy of modeling dynamic load behavior at the chip level to improve power system design and optimize energy efficiency.
“As AI workloads grow in complexity and scale, precise power management is critical to ensuring efficiency, reliability, and sustainability,” said Dion Harris, Senior Director of HPC and AI Factory Solutions at NVIDIA. “Through our collaboration with ETAP and Schneider Electric, we are providing data center operators with unprecedented visibility and control over power dynamics, enabling them to optimize their infrastructure and accelerate AI adoption while improving operational resilience.”
"This collaboration represents more than just a technological solution," says Tanuj Khandelwal, CEO of ETAP. "We are fundamentally reimagining how data centers can be designed, managed, and optimized in the age of AI. By bridging electrical engineering with advanced virtualization and AI technologies, we are creating a new paradigm for infrastructure management."
Pankaj Sharma, Executive Vice President for Data Centers, Networks & Services at Schneider Electric, adds: “Collaboration, speed, and innovation are the driving forces behind the digital infrastructure transformation needed to accommodate AI workloads. Together, ETAP, Schneider Electric, and NVIDIA are not only advancing data center technology; we are empowering businesses to optimize operations and seamlessly navigate the energy requirements of AI.”
