Consulting-Specifying Engineer - October 2007 - (Page 46)

Source Water supply and conveyance Water treatment Water distribution Recycled water treatment Recycled water distribution End-use (agricultural, residential, commercial, industrial) Wastewater discharge Source Wastewater treatment Wastewater collection Figure 2 The interrelationship between water use and electrical consumption will impact the decision-making process on the overall strategy for data center planning. Source: California’s Water–Energy Relationship, Final Staff Report If one looks to the Balance Scorecard method produced in the 1990s by the Harvard Business School, they can glean some ideas on how to approach this complex problem. Because the focus will be on optimization, the analysis will be termed Energy Optimization Scorecard. If all of the issues can be aggregated into four primary, over-arching tenets that apply to data centers, developing an optimized a solution by analyzing and comparing the relative benefits and liabilities seems much more possible. Four fundamentals There are four fundamental beliefs that affect data center planning: • Operational continuity. One of the most unique aspects of any building type, data centers and other types of mission-critical facilities have zero tolerance for failure or shutdown due to maintenance. While there are varying degrees of required system availability, this is an area that generally has very little ability for compromise. The design, operation and integration of the facilities systems (power and cooling) and the IT systems (network and computer hardware) is where the reliability can be influenced the greatest. • Lifecycle cost. Not very different from other building types, getting the biggest bang for the buck is important. An important difference that must be recognized, however, is that utility costs for a data center become a very high percentage of the overall operational cost. Also, if alternatives are developed that reduce first cost by reducing reliability, the financial and reputation risks of a failure need to be accounted for in any lifecycle costing analysis. • Environmental impact. Knowing that a data center on a squarefoot basis will produce on the magnitude of 25 times more CO2 emissions than a typical commercial office building and will use 25 times more water, it is imperative to minimize the negative environmental impacts that are a byproduct of building and operating a data center. Also, understanding how the utility power that is feeding the data center is being generated also will have a big impact on the environment. • IT effectiveness. The other component to be considered is the ratio of power that is dedicated to the computer equipment. This ratio, commonly known as the power usage effectiveness, is a measure of how much power is being provisioned for the IT operations and is affected by reliability level, climate, system type and equipment type. Another area of efficiency that needs to be explored is specific power consumption of the computers vs. the computational output of the computer. This metric is used in the supercomputing field in the form of watts per FLOP (floating-point operations) where there are standard performance benchmarking tests. This is an area that still needs considerable discussion before a solid metric can be presented. By using parametric analysis to determine the interdependencies between the areas of impact and the how they affect the items in the energy optimization categories, an overall strategy can be developed. Because this analysis will have quantifiable results and can be done in an iterative fashion, several “what if” scenarios can be explored and an informed decision can be made. Even though the industry has taken a major step forward in looking at energy-efficient data centers, there still is a lot of work to do. Given the very specialized and critical nature of these facilities, the technical strategies for improving energy performance will prove far easier than the issues concerning operational continuity and other business drivers that are specific to each market sector. Nevertheless, developing and implementing a robust, objective framework for analysis and decision making will ensure a fully optimized outcome. 46 Consulting-Specifying Engineer • OCTOBER, 2007

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Consulting-Specifying Engineer - October 2007 Contents On the Web In the News M/E Roundtable How To Beat the Energy Codes Professional Practices Codes & Standards A Capital Job on Engineered Buiding Systems Going Green in Data Centers Overcurrent Protection: Fuses or Breakers? Third-Party Liability Management Report New Products Product Spotlight Jobs/Classifieds Specifier's Notebook

Consulting-Specifying Engineer - October 2007

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