Understanding the Benefits of Dynamic Cooling Optimization

Cooling optimization in a data center provides a significant opportunity for reducing operating costs since cooling systems consume 34 percent of the power used by a data center, according to Lawrence Berkley National Laboratory.

Due to the need to maintain five nines (99.999 percent) reliability, data centers are too often overdesigned in terms of the cooling capacity, and operating budgets pay the price for this practice. When you look at all of the other components within the modern data center, it’s no wonder so many administrators are looking for better ways reduce costs and control cooling efficiency.

The best practice for cooling optimization in a data center starts with a thorough computational fluid dynamics (CFD) analysis of the cooling design. Today’s common practice is to apply CFD tools at the design or major retrofit stage in order to specify and optimize the cooling system components and layout, based on a proposed IT equipment environment. Yet this approach is unsuccessful because data centers are dynamic environments where the equipment population and layout changes over time, and where the heat signature changes constantly in response to computing traffic. So a typical CFD analysis represents only a snapshot in time and rarely reflects the dynamic operations of the data center 24/7/365.

Now data center managers can use a more effective, next generation analysis and planning tool, ActiveCFD software, to dynamically manage their cooling infrastructure and optimize performance and reliability while reducing operating costs.

In this white paper from CES Group, you’re able to see the benefits of using the ActiveCFD program in the day-to-day monitoring and optimization of a data center’s cooling infrastructure.

The ultimate idea is to create true cooling efficiency across all systems. The only way to do this is with real-time monitoring and dynamic optimization. This real-time CFD model of the data center is used to drive each air conditioner, chiller, and other components of the cooling infrastructure through its entire operating range. The goal of these simulations is to gauge the sensitivity of the inlet temperature of every server and rack equipment to changes in the performance of each critical component of the cooling infrastructure. The cooling parameters analyzed by the System Performance Analyzer (SPA) are:

Download this white paper today to learn how the Dynamic Cooling Optimization module with ActiveCFD can help a data center manager proactively monitor and control the facility’s cooling infrastructure by dynamically matching the cooling output to the prevailing heat load. As a result, operating expenditure can be reduced because wasted or unnecessary cooling capacity is eliminated.