Optimizing Control Chain Latency in Liquid Cooled Data Center for Load Responsive Operation

High power servers are accelerating adoption of cold plate liquid cooling in data centers, but control-chain latency and thermal inertia can delay regulation after load changes and trigger transient swings that threaten temperature stability. This study develops a delay-aware Modelica model for a liquid cooled data center and validates it against measured operating conditions. To compare control options, a standardized percentage step-test protocol is proposed with three indicators—dynamic response time, dynamic fluctuation amplitude, and dynamic fluctuation ratio. Step-response simulations evaluate three single actuator strategies (constant differential pressure valve control, primary side variable flow pumping, and cooling tower outlet temperature control), and a combined condition database is built for coordinated pump–fan control with operating-point matching. Valve control responds fastest (38.3–41.3 s) but produces the largest fluctuations; variable flow pumping is smoother with response times of 44.2–72.9 s; and cooling tower temperature control is most stable but slowest (684–826 s). The optimized combined strategy reallocates control authority across operating conditions, reducing response time from 688.3 s to 73.7 s and lowering dynamic temperature swing risk by up to 1.3 °C. These results support load-responsive, plant-level transient-safe operation of liquid-cooled data-center cooling plants, particularly for secondary-side supply temperature control.