Simulation Spanish Hospital
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Transcript of Simulation Spanish Hospital
A spanish Hospital with 800 computers with very interesting projected savings
Simulations Report
Tuesday, October 19, 2010
Workings
• The software measures the PC energy state and the user activity each second.
• After a certain amount of inactivity time, the PCs are put in low power state
On
StandBy
Off
Active
Inactive
Tuesday, October 19, 2010
Math
• The power used in each state is inserted in the software, and the program does the calculus aggregating data.
• The total savings are projected based on known set.
90W
5W
1W∑ Time
Tuesday, October 19, 2010
So you don´t believe it?We´ve seen lots of people asking “how can you trust assumptions based on statistics?”
Our experience shows that order and control can make big changes in use and
savings of resources. (And our customer´s electricity bill agrees)
Tuesday, October 19, 2010
You still don´t believe it?
SURVEYOR math is based on scientific tests based in the work of several people, including:
ReferencesKawamoto-2001 - Kawamoto, Kaoru, Jonathan G. Koomey, Bruce Nordman, Richard E. Brown, Mary Ann Piette, Michael Ting, and Alan K. Meier. 2001, "Electricity Used by Office Equipment and Network Equipment in the U.S.: Detailed Report and Appendices." Energy Analysis Department, Lawrence Berkeley National Laboratory, Berkeley, CA. LBNL-45917, February, 2001.Roth-2002 - Roth, Kurt,W., Fred Goldstein, and Jonathan Kleinman. 2002, "Energy Consumption by Office and Telecommunications Equipment in Commercial Buildings,Volume I: Energy Consumption Baseline,Arthur D. Little, Inc. Cambridge, MA No. 72895-00, January, 2002. EPA-2000 – “Case Study:Automatic Activation of Energy Star Features in Monitors at US DOE’s Energy Efficiency and Renewable Energy Office.” Air and Radiation (6202J) Draft, December 2000. Roberson-2002 – Private conversation with Judy A. Roberson about draft work.
Tuesday, October 19, 2010
Data capture
• A database stores historic data and allows us to make comparisons
• Analysis tools allow us to do a tight project tracking during the lifetime of it (in real time)
This date started
the policies
The effect is noticed by the
appearance of stand-by
states (yellow bars)
Tuesday, October 19, 2010
Comparative criteria• Both periods: without holidays or
reduced working hours.
• 1) Initial period:
• without applied policies
• 2) Final period
• with applied policies
• with the platform stabilized
Tuesday, October 19, 2010
Compared periods
• Data from 'Period 1' was captured from 09/13/2010 to 09/27/2010. On average, 22 PCs were connected daily.
• Data from 'Period 2' was captured from 09/28/2010 to 09/11/2010. On average, 21 PCs were connected daily
Tuesday, October 19, 2010
Methodology
• 1st period: agent deployed in “audit mode”. With results on hand, we design savings policies to be applied in 2nd. period.
• 2nd period: agent put in “enforce mode”
• Comparison of results and projection to whole organization (estimates based on statistics and profile of company)
Tuesday, October 19, 2010
Results388 kWh saved per PC / yr *
34.000 € to be saved in 800 PC yearly
* this is the average for the whole hospital. Depending on computer types, it varies between 90 kWh and 800 kWh. What we can really say is that savings will be VERY important.
Tuesday, October 19, 2010
Graphic comparison
Tuesday, October 19, 2010
Lab 1-799 kWh (76,9% savings) per PC / year
It´s evident that the PC are left running 24 hours regardless use. The policies have immediate noticeable effects.This figure extrapolates the consumption of these computers to a set of 800 and annualized values
Tuesday, October 19, 2010
Lab 1average utilization hours
The effect of the policies in the power-on hours is perfectly observed (replaced by hours of stand-by)
CPU Display
Tuesday, October 19, 2010
Research Lab-615 kWh (56,9% savings) per PC / year
It´s seen that the PC are left running 24 hours. a day. The peak at the blue line indicates that for some reason the computers were turned on abnormally (or may be due to poor data collection, we're looking into analyzing logs) so the savings could improve further.
This figure extrapolates the consumption of these computers to a set of 800 and annualized values
Tuesday, October 19, 2010
Research Labaverage utilization hours
The effect of the policies in the power-ON hours is perfectly observed (replaced by hours of stand-by)
Data on 10/2 and 10/3 may be due to data corruption or PC malfunction
CPU Display
Tuesday, October 19, 2010
Admin 1-258 kWh (52,4% savings) per PC/year
It´s seen that the PC are left on almost 24 hours. There are notable savings avoiding the energy waste because of the weekends misuse.
This figure extrapolates the consumption of these computers to a set of 800 and annualized values
Tuesday, October 19, 2010
Admin 1average utilization hours
The green bars indicate that these users were already responsible about the use of their computers. The yellow bars appear when we gain standby hours (much less consumption) avoiding additional waste.
CPU Display
Tuesday, October 19, 2010
IT-63,1 kWh (21,1% savings) per PC/year
The close correlation between curves indicates that users are very responsible (or that they are alert about the test case because they are the implementers ... is normal.) Notwithstanding this, 21% savings is very important because it demonstrates the potential of the solution to optimize consumption even when the user is careful (eliminates idling time during the day).
This figure extrapolates the consumption of these computers to a set of 800 and annualized values
Tuesday, October 19, 2010
ITaverage utilization hours
The exception that proves the rule: in our experience, IT users are the most lawless on energy issues. In this particular case they aren´t... or were alerted to the test (may be the case as they are those who have done it).
Similarly, the yellow bars are moments of rest gained during the day
CPU Display
Tuesday, October 19, 2010
Imaging-678 kWh (74% savings) per PC/year
There was already a decrease in the first period (due to lower utilization hours), but policy implementation greatly reduces consumption even more. These equipment must surely be ON all day, and use is in very short periods during the day.
This figure extrapolates the consumption of these computers to a set of 800 and annualized values
Tuesday, October 19, 2010
Imagingaverage utilization hours
Again, the case of a service running 24/7, in which policy implementation greatly improves the use of resources.
CPU Display
Tuesday, October 19, 2010
Secretaries-209 kWh (40,6% savings) per PC/year
Again the gains come from reduced consumption during weekends. The days when no policies are applied reveal less consuming than when they are set, due to the different activities of people within any given 2 working days (in an intense day with policies applied you can spend more than in a light one without them)
This figure extrapolates the consumption of these computers to a set of 800 and annualized values
Tuesday, October 19, 2010
Secretariesaverage utilization hours
(not enough data)
Tuesday, October 19, 2010
Front Office-98,9 kWh (15,7% savings) per PC/year
Reduced consumption on weekends. It is inferred that the users of these machines have tasks like "data entry" or processing orders and making continued use of the equipment.
This figure extrapolates the consumption of these computers to a set of 800 and annualized values
Tuesday, October 19, 2010
Front Officeaverage utilization hours
A repeating case about a continuos working service, where policies applied improve so much the savings.
CPU Display
Tuesday, October 19, 2010
Recommendations
• Do not take this information to the letter. The software estimates are conservative: when used data from the PC without considering the load of CPU, peripherals, disk, etc, the usual consumption power is much greater than estimated and therefore the savings are higher.
• As the result depends on people behavior (not a laboratory testing out of reality), and no one works the same from day to day or week to week, it is impossible to consider the conditions between 2 periods as 100% equivalent . To accomplish this we should clone two people´s behaviors, or put two subjects in a laboratory (one with software and one without it) and force them to use the PC in EXACTLY the same way.
• Wait a few months and see the electricity bill. The result will be visible where most noticeable (comparison from year to year).
Tuesday, October 19, 2010