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FIGURE 8. Cooling-plant efficiency for Lawrence Berkeley National Laboratory-benchmarked data centers.

COOLING-SYSTEM EFFICIENCY
The key metrics and benchmarks for evaluating the efficiency of cooling systems in data centers are no different than those typically used in other commercial buildings. These include chiller-plant efficiency (kilowatt per ton) and pumping efficiency (horsepower per gallon per minute). Figure 8 shows cooling-plant efficiency for LBNL-benchmarked data centers. Based on data from the LBNL database, 0.8 kw per ton could be considered a good practice benchmark, while 0.6 kw per ton could be considered a better practice benchmark.

FIGURE 9. Simulated air-side-economizer-utilization potential for four locations.7

AIR-SIDE-ECONOMIZER UTILIZATION
Air-side-economizer utilization characterizes the extent to which an air-side-economizer system is being used to provide “free” cooling. It is defined as the percentage of hours in a year that an economizer system can be in full or complete operation (i.e., without any cooling being provided by the chiller plant). The number of hours that an air-side economizer is being utilized could be compared with the maximum hours possible for the climate in which the data center is located. This can be determined from simulation analysis. For example, Figure 9 shows results from a simulation of four different climate conditions. The Green Grid, a global consortium dedicated to developing and promoting data-center energy efficiency, has developed a tool to estimate savings from air- and water-side free cooling, although the assumptions are different than those used for the results presented in Figure 9.8

SUMMARY
Data-center operators can use the metrics discussed in this article to track the efficiency of their infrastructure systems. The system-level metrics in particular allow operators to help identify potential efficiency actions. Data from the LBNL benchmarking database show a wide range of efficiency across data centers.

DCIE is gaining increasing acceptance as a metric for overall infrastructure efficiency and can be computed in terms of site energy, source energy, or electrical load. However, DCIE does not address the efficiency of IT equipment. Organizations, such as The Green Grid, are working to develop productivity metrics (e.g., data-center energy productivity) that will characterize the work done per unit of energy. The challenge is to categorize the different kinds of work done in a data center and identify appropriate ways to measure them. As those metrics become available, they will complement the infrastructure metrics described in this article.

REFERENCES

1. U.S. EPA. (2007). Report to Congress on server and data center energy efficiency public law 109-43. Washington, DC: U.S. Environmental Protection Agency.
2. U.S. DOE. Data center energy profiler. (n.d.). Retrieved from http://dcpro.ppc.com
3. Greenberg, S., Khanna, A., & Tschudi, W. (2009, June). High performance computing with high efficiency. Paper to be presented at the 2009 ASHRAE Annual Conference, Louisville, KY.
4. ASHRAE. (2008). 2008 ASHRAE environmental guidelines for datacom equipment. Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers.
5. Herrlin, M.K. (2005). Rack cooling effectiveness in data centers and telecom central offices: The Rack Cooling Index (RCI). ASHRAE Transactions, 111, 725-731.
6. Herrlin, M.K. (2007, September). Improved data center energy efficiency and thermal performance by advanced airflow analysis. Paper presented at the Digital Power Forum, San Francisco, CA.
7. Syska Hennessy Group. The use of outside air economizers in data center environments. (n.d.) Retrieved from http://www.syska.com/thought/whitepapers/wpabstract.asp?idWhitePaper=14
8. The Green Grid. Free cooling estimated savings calculation tool. (n.d.) Retrieved from http://cooling.thegreengrid.org/calc_index.html

Paul Mathew, PhD, is a staff scientist; Steve Greenberg, PE, is an energy-management engineer; Srirupa Ganguly is a research associate; Dale Sartor, PE, is the applications team leader; and William Tschudi, PE, is a program manager for Lawrence Berkeley National Laboratory.