Power usage effectiveness

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Power usage effectiveness (PUE) is a measure of how efficiently a computer data center uses energy; specifically, how much energy is used by the computing equipment (in contrast to cooling and other overhead).

PUE is the ratio of total amount of energy used by a computer data center facility [1][2][3][4][5][6][7][8] to the energy delivered to computing equipment.

PUE was developed by a consortium called The Green Grid. PUE is the inverse of data center infrastructure efficiency (DCIE). An ideal PUE is 1.0. Anything that isn't considered a computing device in a data center (i.e. lighting, cooling, etc.) falls into the category of facility energy consumption.

 \mathrm{PUE}  =  {\mbox{Total Facility Energy} \over \mbox{IT Equipment Energy}}

Issues and problems with the power usage effectiveness[edit]

The PUE metric is the most popular method of calculating energy efficiency. Although it is the most effective in comparison to other metrics, the Power Usage Effectiveness comes with its share of flaws. This is the most frequently used metric for operators, facility technicians, and building architects to determine how energy efficient their data center buildings are (Jumie). Some professionals even brag about their Power Usage Effectiveness being lower than others. Naturally, it is not a surprise that in some cases an operator may “accidentally” not count the energy used for lighting, resulting in lower Power Usage Effectiveness. For example, the data center’s ratio would be recorded as a 1.5 when the true value should be a 1.6. Not counting all energy-consuming devices to make your data center building seem more energy efficient is an ongoing issue. In other words, this problem is more linked to a human mistake, rather than an issue with the Power Usage Effectiveness metric system itself. The one real problem we are quite aware of is regarding the issue of temperature within the cities that the data centers are built. For example, a data center located in Alaska cannot be effectively compared to a data center in Miami. It is essential to consider the differing climates between the two locations. A colder climate results to a lesser need for a massive cooling system. It is a significant factor that the energy needed for cooling systems must be accurately calculated. Cooling systems account for roughly 30 percent of consumed energy in a facility, while the data center equipment accounts for nearly 50 percent (Jumie). A possible result of this problem is that even though the data center in Miami may have a final Power Usage Effectiveness of 1.8 and the data center in Alaska may be at a ratio of 1.7, the proper result could be that Miami is still more energy efficient if it was placed in an area of equal temperature. All in all, finding simple, yet recurring issues such as the problems associated with the effect of varying temperatures in cities and learning how to properly calculate all the facility energy consumption is very essential. By doing so, continuing to reduce these problems ensures that further progress and higher standards are always being pushed to improve the success of the Power Usage Effectiveness for future data center facilities.[9]

Benefits and limitation[edit]

PUE was introduced in 2006 and promoted by the Green Grid (a non-profit organization of IT professionals) in 2007, and has become the most commonly used metric for reporting the energy efficiency of data centres (Gemma). Although it is named the 'power usage effectiveness', the metric actually measures the energy use of the data centre (Gemma). The PUE metric is helpful because it has several important benefits. First of all, the companies using the metric could record the change of usage effectiveness. Therefore, they could keep checking the data center's efficiency seasonally and annually. Also, the companies could improve the date center to make it work more efficient by improving the cooling system and turn off the unnecessary electric devices to reduce electricity consumption. Another benefit of the PUE metric is it creates competition, “driving efficiencies up as advertised PUE values become lower" (Gemma). Companies use PUE as a marketing tool to present how efficient their data center is. Companies try to lower their PUE value, which means the data centers work more efficiently and reduce electricity consumption. However, there are some issues of the PUE metric. Rather than the issues mentioned in last paragraph, some other issues are the efficiency of the power supply network and calculating the accurate IT load. According to the sensitivity analysis by Gemma, " Total energy consumption is equal to the total amount of energy used by the equipment and infrastructure in the facility (WT) plus the energy losses due to inefficiencies in the power delivery network (WL), hence: PUE=(WT+WL)/WIT." Based on the equation, the inefficiencies of the power delivery network (WL ) will increase the total energy consumption of the data center. The PUE value goes up as the data center becomes less efficient. IT load is another important issue of the PUE metric. "It is crucial that an accurate IT load is used for the PUE, and that it is not based upon the rated power use of the equipment. Accuracy in the IT load is one of the major factors affecting the measurement of the PUE metric, as utilization of the servers has an important effect on IT energy consumption and hence the overall PUE value"(Gemma). For example, a data center with high PUE value and high server utilization could be more efficient than a data center with low PUE value and low server utilization.[10]

Notable efficient companies[edit]

Data centers belong to companies worldwide. Larger companies have to be kept in check, however, to ensure that energy is not wasted in the details. As stated before, most companies will flaunt how efficient their data centers can be. For example, the data center in Chicago is named, " Lakeside Technology," and is approximately 1.1 million square feet.[11] Soon there is going to be a data center complete in Langfang, China, that is going to be 6.3 million square feet. These huge numbers can be intimidating. At the same time, these places must be kept in check to ensure little to no power is wasted. In the United States, there are two of the most notable data center efficient companies. In October 2008, Google's Data center was noted to have a ratio of 1.21 PUE across all 6 of its centers, which is considered as close to perfect as currently possible. Right behind Google, was Microsoft, which had another notable PUE ratio of 1.22 [12] Many argue that a PUE is only used to lure potential company or share owners in to prove how efficient their data centers are. According to a case study on Science Direct, " an estimated PUE is practically meaningless unless the IT is working at full capacity".[13] This also means that any supporting systems or infrastructure are working at full capacity as well. However, commercial companies are not the only ones to have data centers or PUE's. Government structures and firms have data centers and must be extremely efficient as well. Government institutions are attempting to still reduce the costs of IT rates and at the same time keep their efficiency at good rates too. Because Government institutions must work with large budgetary constraints, it is difficult to have efficient PUE's while working within the constraints and also keep the management of the data centers at a reasonable level. Telecommunicationn companies also have large data centers. These telecoms companies are always looking for ways to increase efficiency of their data centers while at the same time reducing the cost of managing them. These management issues usually include utility bills that spike and surge, causing rising and falling PUE rates, causing a static and fluctuating PUE rate. They also try to add flexible data centers. All of these, however, are under the assumptions of non-changing factors, such as inflation, any fatal technological errors, political issues, and even social factors. If any of these had a significant change, obviously the companies would need to adapt and make any changes necessary to keep efficiency and effectiveness high to reduce costs of running the data centers and managing them as well.

See also[edit]


  1. ^ SearchDataCenter.com - power usage effectiveness (PUE)
  2. ^ Digital Realty Trust- PUE Data Center Efficiency Metric
  3. ^ Engineered Systems - Optimizing Power Usage Effectiveness In Data Centers
  4. ^ The Green Grid - The Green Grid Data Center Power Efficiency Metrics: PUE and DCiE
  5. ^ Google - Efficient Computing - Data Center Efficiency Measurements
  6. ^ Dell - Best Practices for Increasing Data Center Energy Efficiency
  7. ^ Cisco Systems - Cisco Energywise
  8. ^ Google Data Center Optimization - [1]
  9. ^ Jumie Yuventi, Roshan Mehdizadeh. “A critical analysis of Power Usage Effectiveness and its use in communicating data center energy consumption.” Energy and Building 64 (2013) 90-94 : Web. 17 November 2014.
  10. ^ Gemma A. Brady, Nikil Kapur, Jonathan L. Summers, Harvey M. Thompson “A case study and critical assessment in calculating power usage effectiveness for a data centre”Energy Conversion and Management 74 December 2013 155-181: Web. 18 November 2014.
  11. ^ "The 5 Largest Data Centers in the World." Forbes. Forbes Magazine, n.d. Web. 17 Nov. 2014.
  12. ^ Tuf, Steve. "Power Usage Effectiveness." It.toolbox. Toolbox, n.d. Web. 17 Nov. 2014.
  13. ^ Brady, Gemma, Nikil Kapur, Jonathan Summers, and Harvey Thompson. "A Case Study and Critical Assessment in Calculating Power Usage Effectiveness for a Data Centre." Energy Conversion & Management, 76 (2013): 155-161.