In 2024, we saw a significant surge in data center demand fueled by the rapid growth of AI technology, which is projected to increase 160% by 2030. This unprecedented growth introduced a defining challenge of the AI era: how to balance the environmental impact of data centers with the urgent need to scale infrastructure to support AI advancements.
To meet this demand, companies are quickly building new data centers across a wide range of locations, from major urban centers to rural communities across the U.S., with regions like Northern Virginia, Texas, and Georgia emerging as key hubs driving this new era of energy demand. However, growing societal concerns over the significant energy consumption of these facilities are pushing data center operators to rethink and intensify their efforts to reduce their environmental footprint.
In response, we can anticipate a more unified, collaborative effort from key stakeholders to tackle the challenges created by the ongoing energy boom. While data centers’ energy guzzling issue may not be fully resolved by 2025, substantial progress will be made through a holistic approach that harnesses innovative solutions, such as virtual twin technology, to reduce the environmental impact of data centers and improve operational efficiency.
The Challenge: Managing AI’s Rising Energy Demands and Cooling Needs in Data Centers
Zooming in on AI’s energy consumption challenge, most of the energy consumption in data centers comes from servers, but also from complex cooling systems. The training and inference of AI models requires substantial computational power, driving the need for energy-intensive, GPU-powered servers. These servers, essential for processing vast amounts of data, generate excess heat due to their high power consumption, necessitating cooling systems that, in turn, consume even more energy. Maintaining optimal temperatures through these cooling systems is crucial to prevent overheating and avoid localized hotspots that could compromise system performance and reliability.
As a result, the power demands associated with AI-driven applications differ significantly from those of traditional data centers. For example, a single query on AI models like ChatGPT consumes 10 times more energy than that of a standard Google search. And historically, airflow cooling systems are no longer sufficient to evacuate all the heat produced by GPU servers. New technologies based on direct liquid cooling (DLC) are gradually being implemented to evacuate the heat provided by racks of more than 30 kW. By optimizing energy usage and enhancing operational performance, in 2025, virtual twin technology could revolutionize the way data centers manage energy consumption and improve overall efficiency.
Virtual Twins – The Game-Changer for Reducing Data Center Energy Consumption
To meet the growing global demand for sustainable data centers, data center engineers need a comprehensive look at the entire data center ecosystem to effectively model its framework. This framework should account for key factors such as various servers and their associated application workloads, HVAC systems and their airflow patterns, and the integration of DLC systems.
This is where virtual twins truly shine. By creating digital replicas of the data center, virtual twins enable stakeholders and operators to model and analyze real-world conditions throughout the data center’s lifecycle. These simulations provide the ability to conduct proactive, scenario-based analysis, allowing potential issues to be identified and addressed before they occur.
When it comes to energy consumption, virtual twins offer a detailed and comprehensive analysis of a data center’s energy behavior. By aggregating data from each subsystem — from the servers and their application loads to the DLC systems— the energy management systems, and even the power grid supplying the data center, virtual twins offer a holistic view of energy usage across the entire data center operation.
Equipped with this knowledge, operators can refine the design and performance of their cooling system, including DLC and airflow cooling. Virtual twins provide ultimate control over parameters, enabling optimized distribution of workloads across various servers. This control can also be automated to harmonize the rapid shifts in compute allocation with the slower response of climate control systems, ensuring optimal cooling performance at all times.
Furthermore, virtual twins can simulate the impact of compute workloads on energy consumption, heat generation, airflow dynamics, and the efficiency of cooling systems, including the performance of direct liquid cooling. This approach has the potential to reduce server energy consumption by up to 10% and lower cooling energy usage by as much as 30%, delivering significant savings in both energy costs and operational efficiency.
Looking Ahead: Laying the Groundwork for Sustainability in 2025
Overall, virtual twins will be instrumental in driving innovation across every facet of data center operations and energy management. With the AI boom showing no signs of slowing down, data center operators must adopt forward-thinking strategies to reduce their carbon footprint while meeting the growing demands of the market. As the industry evolves, virtual twins will not only enable more intelligent energy management but also serve as a cornerstone for the future of sustainable data centers.