Keywords
taguchi, data center, sustainability, pue, carbon emission
Start Date
1-7-2010 12:00 AM
Abstract
This paper presents a methodology for measuring sustainability performance ofdata center facilities. Treating data center operation as a continuous production process, aTaguchi framework is used to estimate the sustainability impact due to power utilizationfrom the facility by calculating the loss to society as the facilities power utilizationbecomes less efficient than the Environmental Protection Agency’s guidelines. By trackingdata center sustainability performance with continuous production process metrics, it iseasy to identify and study performance characteristics, which if out of specification, havebroader environmental impacts. This method evaluates the data center’s excess energyconsumption as a performance quality control issue, and estimates the cost of poorperformance. Average power usage effectiveness (PUE) is a standard data centerperformance metric. In this case study PUE is tracked continuously to provide real-timeoperations and controls feedback. Further, PUE is mapped using the Taguchi frameworkand the U.S. EPA data center benchmark to the societal cost of non-conformance with theperformance benchmark performance deviation based on carbon emissions and associatedcarbon exchange markets. It is expected that the method used in this paper may provideuseful information to policy makers, engineers, and decision makers regarding sustainableIT data centers.
A Taguchi-Based Method for Assessing Data Center Sustainability
This paper presents a methodology for measuring sustainability performance ofdata center facilities. Treating data center operation as a continuous production process, aTaguchi framework is used to estimate the sustainability impact due to power utilizationfrom the facility by calculating the loss to society as the facilities power utilizationbecomes less efficient than the Environmental Protection Agency’s guidelines. By trackingdata center sustainability performance with continuous production process metrics, it iseasy to identify and study performance characteristics, which if out of specification, havebroader environmental impacts. This method evaluates the data center’s excess energyconsumption as a performance quality control issue, and estimates the cost of poorperformance. Average power usage effectiveness (PUE) is a standard data centerperformance metric. In this case study PUE is tracked continuously to provide real-timeoperations and controls feedback. Further, PUE is mapped using the Taguchi frameworkand the U.S. EPA data center benchmark to the societal cost of non-conformance with theperformance benchmark performance deviation based on carbon emissions and associatedcarbon exchange markets. It is expected that the method used in this paper may provideuseful information to policy makers, engineers, and decision makers regarding sustainableIT data centers.
