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


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


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)


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.


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)


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


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


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)


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.


Graphic comparison


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


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


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


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


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.



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


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).



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


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.



Imagingaverage utilization hours

Again, the case of a service running 24/7, in which policy implementation greatly improves the use of resources.

CPU Display


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)



Secretariesaverage utilization hours

(not enough data)


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.



Front Officeaverage utilization hours

A repeating case about a continuos working service, where policies applied improve so much the savings.

CPU Display


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).


simulation spanish hospital

Documents

savings policies

hours of stand

standby hours

pc energy state

pc year

notable savings

total savings

energy waste