# [BLDG-SIM] Statistical Estimate of Number of Units ON (peak demand)

Fred Porter fporter at archenergy.com
Fri Jun 4 09:34:58 PDT 1999

```The more cycling units you have, the LESS probable it is that they will all be on
constantly during a 15 minute demand window, when compared to a single unit. A
single cycling unit is more likely to cause an un-predicted peak above its hourly
average demand.

During a DSM evaluation project we tried to calibrate many basic DOE-2.1
simulations with monthly utility demand and consumption data. Some of the best
"behaved" buildings were big box retail stores with 20+ packaged units (and some
other characteristics that make them easy to simulate).

DOE-2.2 does have some capapabilities to account for sub-hourly HVAC demands,
even though it is an hourly simulation. I have not used these yet, however.

BKoran at aol.com wrote:

> This is a statistics problem.  I'm extremely competent with thermodynamics
> and most energy analysis, but I've only recently tried to estimate peak
> demand by month.  I can estimate the kW of an individual unit, but what is
> the expected peak kW during the month for a given number of similar units?
>
> I'm very curious, how do hourly analysis program do this?  It's easy to see
> that they might not handle peak demand very well.
>
> As I'm certain you're all aware, large businesses are
> generally charged each month according to the highest electrical demand
> recorded over a 15-minute period.
>
> Consider a site with number of packaged units for cooling.  The problem is to
> find out the maximum number of units that would be on at
> simultaneously (for at least 15 minutes), so that the peak electrical demand
> and associated demand charges can be estimated.
>
> N_units =number of units
> A_pct   =fraction of time each unit is on
>          during each time period considered
> N_pers  =number of time periods to be considered
> A_Prob  =minimum acceptable probability of occurrence
>
> For example, if I have 3 units, and each unit operates only 5 minutes each
> hour, the probability that all units are operating at once is low if I only
> look at 1 hour.
>
> However, if I consider 100 hours, the probability that all units are
> operating at once is much higher.
>
> If I have a large number of units, the number of units likely to be
> operating simultaneously will approach the product of the total number of
> units times the fraction of time each unit is on.
>
> I suppose I need to use a threshold probability to constrain the problem.
> So, with a probability greater than 70%, what is the maximum number of
> units operating simultaneously?  Even better, what is the maximum average
> number of units operating simultaneously over a 15-minute period?
>
> How do DOE-2, Trace, HAP, BLAST, etc. calculate a 15-minute peak demand?
>
> Bill Koran
>
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--
Fred W. Porter
Senior Engineer
Architectural Energy Corp.
2540 Frontier Ave. Suite 201
Boulder CO 80301
email: fporter at archenergy.com
phone: 303-444-4149
fax: 303-444-4304

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