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

John P. Karasaki, P.E. jpkarasa at cbg-engrs.com
Thu Jun 3 08:38:57 PDT 1999

```The energy simulation programs you mention don't calculate any variables in
15 minute intervals.  1 hour time slices are the standard.  DOE2 doesn't use
statistics*.  It takes a sledge hammer approach and sums up the coincident
loads from all the calculations it does.

I don't think you can estimate AC equipment demand with the statistics
variables you mention.  The number of AC units on at any time is a function
of the internal and external building loads, the thermal inertia of the
building and contents, and the equipment operating schedule set by the
building operator.

We had a project in which we had the good fortune of over 2 years of chiller
data and coincident weather data.  The goal was to come up with a series (a
minimal amount!) of equations by which we could predict a building's cooling
load based on outdoor air parameters.

We were not able to do it as there were too many inconsistencies and too
many variables.  e.g. so what if it is 100 F out if that occurs on a Sunday
when the building isn't occupied; or worse, a Monday that also just happens
to be a holiday.

It seems the more one tries to simplify a complex process, the more the
accuracy of the results are compromised.

I hope you fair better!  Good luck!

*Maybe only in window blind scheduling?

-----Original Message-----
From: BKoran at aol.com [mailto:BKoran at aol.com]
Sent: Wednesday, June 02, 1999 3:51 PM
To: BLDG-SIM at gard.com
Subject: [BLDG-SIM] Statistical Estimate of Number of Units ON (peak
demand)

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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