• Overview

We aim to develop a high-fidelity, physics-based EnergyPlus modeling framework for liquid-cooled data centers (LCDC) to address the large thermal loads generated by high-density AI server racks. While existing EnergyPlus-based data center models have largely been limited to air-cooled system configurations, this study expands the modeling scope to comprehensively represent both the Facility Water System (FWS) and the Technology Cooling System (TCS) of LCDCs in accordance with the ASHRAE Liquid Cooling Guideline. In particular, to reflect the allowable operating temperature ranges of liquid-cooled server racks, appropriate FWS configurations are established based on the TCS fluid classes defined in the guideline. These configurations include chiller/cooling tower systems, water-side economizers (WSE), and dry coolers, and are classified into the following cases:

• LCDC – Case A: Chiller Only / WSE Partial Cooling Mode
• LCDC – Case B: Cooling Tower Only
• LCDC – Case C: Dry Cooler Only

On the TCS side, the modeling framework incorporates major liquid-cooling components, including Coolant Distribution Units (CDUs), direct-to-chip liquid cooling, rear-door heat exchangers (RDHx), and immersion cooling. This framework is expected to support warmer facility water operation and longer free-cooling hours, thereby improving overall cooling system efficiency and reducing cooling energy use by approximately 20-30%.

• IIT and Cooling Load Modeling

Figure 3 presents the overall framework for IT and cooling load modeling. We define the cooling load of our data center models based on tray-level rated IT power for a 2 CPU and 4 GPU configuration (e.g., 6.7 kW) and rack-level rated power (e.g., 120 kW), which are broadly representative of AI training and inference services. Using these rated values, auxiliary loads beyond the servers, and a design-rated Cooling Power Usage Effectiveness (PUE, Total Energy/IT Energy) of 1.2, we estimate the rated IT and cooling loads for a 1 GW-class liquid-cooled data center (LCDC).

We then generate stochastic tray-level IT workloads at the millisecond scale and aggregate them to the rack and Coolant Distribution Unit (CDU) levels. At the cooling interface, direct-to-chip cooling removes heat directly from the primary compute components, while residual rack-level air-side heat is captured through rear-door heat exchangers (RDHx).

These aggregated IT workloads are then translated into minute-resolution cooling loads by accounting for the thermal inertia of the liquid-cooling loop, fluid transport delay, and the response characteristics of the cooling control system. Because the cooling infrastructure responds more slowly than the millisecond-scale IT workload, the resulting plant-level demand is naturally smoothed over time. The resulting composite load curve therefore captures not only the IT load itself, but also cooling tower fans, condenser-water-system (CWS) pumps, chillers, facility-water-system (FWS) pumps, technology-cooling-system (TCS) pumps, Coolant Distribution Units (CDUs), RDHx fans, and other relevant auxiliary loads, enabling a smoother and more physically realistic representation of the coupled IT-cooling dynamics.

Figure 1. IT and Cooling Load Modeling

• Liquid Cooling Data Center System

On the TCS side, the coolant distribution unit (CDU) is modeled to represent a hybrid cooling architecture in which heat generated by the primary compute components, such as CPUs and GPUs, is removed directly through cold-plate-based direct-to-chip cooling, while residual rack-level air-side heat is captured through active rear-door heat exchangers (RDHx). This enables a more realistic representation of the combined liquid-cooling and air-side supplemental cooling characteristics of AI data centers.

At Data Hall level, each system is designed with N+1 redundancy to ensure stable and reliable operation, and the potential application of thermal energy storage tanks is also considered to enhance emergency response capability and provide additional operational flexibility.

Figure 2. System Overview of the Liquid Cooling Data Center