[Equest-users] eQUEST Calculations
tjm at geatain.com
tjm at geatain.com
Tue May 22 11:40:49 PDT 2018
All,
Thanks for all your help with this, you have given me a much better picture
of the field.
Curious to find out one more thing. Wonder what confidence interval between
model output and utility consumption data may be expected with reasonable
effort of 10-12 modeling hours for straightforward 100,000 square foot
building if we have two different scenarios:
1. Good as-built drawings for a 15 yr old building.
2. No historical drawings and mostly estimated/guesswork for 100 year
old building.
All reasonable assumptions welcome.
Thanks again,
Tom
Tom McGovern, PE, LEED AP
Geatain Engineering
112 West 34th Street, 18th Floor
New York, NY 10120
Office: (844) 443-2824
Cell: (631) 521-3594
<http://www.geatain.com> www.geatain.com
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From: Equest-users <equest-users-bounces at lists.onebuilding.org> On Behalf Of
David Eldridge via Equest-users
Sent: Tuesday, May 22, 2018 11:55 AM
To: equest-users at onebuilding.org
Subject: Re: [Equest-users] eQUEST Calculations
I was going to mention GenOpt as one option, and which actually just showed
up in another thread on bldg.-sim mailing list.
However, the "standard" GenOpt installation can optimize one function, so as
a calibration tool there would be an additional step to develop a CV (RMSE)
and/or mean bias error for the results compared to the real utility data.
The autotune methods such as a presentation from Dr. New at ORNL given to
IBPSA-USA and ASHRAE, or optimization platforms give a better control over
the parameters to be varied. The code that you can get from GitHub to do
this though is for EnergyPlus, not eQUEST or DOE2.2.
With GenOpt I also don't believe you'd be able to supply ranges for all the
variables - so the program would minimize error but a solution could include
nonsensical parameters if that satisfied the error function.
David
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From: Equest-users <equest-users-bounces at lists.onebuilding.org
<mailto:equest-users-bounces at lists.onebuilding.org> > on behalf of Jones,
Christopher via Equest-users <equest-users at lists.onebuilding.org
<mailto:equest-users at lists.onebuilding.org> >
Sent: Tuesday, May 22, 2018 10:28:37 AM
To: Kathryn Kerns; Aaron Powers; Nicholas Caton
Cc: equest-users at onebuilding.org <mailto:equest-users at onebuilding.org>
Subject: Re: [Equest-users] eQUEST Calculations
As Niels Bohr said, “Prediction is very difficult, especially about the
future”.
Christopher R Jones, P.Eng.
T+ 1 416-644-0252
From: Equest-users [mailto:equest-users-bounces at lists.onebuilding.org] On
Behalf Of Kathryn Kerns via Equest-users
Sent: Tuesday, May 22, 2018 11:19 AM
To: Aaron Powers <caaronpowers at gmail.com <mailto:caaronpowers at gmail.com> >;
Nicholas Caton <Nicholas.Caton at schneider-electric.com
<mailto:Nicholas.Caton at schneider-electric.com> >
Cc: equest-users at onebuilding.org <mailto:equest-users at onebuilding.org>
Subject: Re: [Equest-users] eQUEST Calculations
I have never been a fan of those performance contracting energy savings
projects and our company has steered clear of them for the reasons listed
below. I have done fluid and thermal finite element modeling and energy
modeling for about 30 years off and on, and the only thing that can be said
for these models is they show the user how something changes as a result of
changing certain variables. The models do not predict the future nor do they
justify the past.
Sometimes a difficult concept to get across to people.
Kathryn Kerns
Systems Specialist
BCE Engineers, Inc.
| Ph: 253.922.0446 | Fx: 253.922.0896 |
From: Equest-users <equest-users-bounces at lists.onebuilding.org
<mailto:equest-users-bounces at lists.onebuilding.org> > On Behalf Of Aaron
Powers via Equest-users
Sent: Monday, May 21, 2018 5:30 PM
To: Nicholas Caton <Nicholas.Caton at schneider-electric.com
<mailto:Nicholas.Caton at schneider-electric.com> >
Cc: equest-users at onebuilding.org <mailto:equest-users at onebuilding.org>
Subject: Re: [Equest-users] eQUEST Calculations
Very well put Nick, and an important perspective from the world where
savings projections are guaranteed. 2 + 2 = 4, but so does 10 - 6
On Mon, May 21, 2018 at 7:13 PM, Nicholas Caton via Equest-users
<equest-users at lists.onebuilding.org
<mailto:equest-users at lists.onebuilding.org> > wrote:
As an energy engineer in the performance contracting side of the industry, a
defining skillset for my job is creating and then calibrating models to fit
historical utility data. We calibrate our models to a degree of rigor
allowing our business to guarantee savings projected from those models (and
write shortfall checks when we’re wrong). I don’t generally talk up my
background, but I think in this case it helps to know where my voice is
coming from to press a nuanced response:
It's possible (again, not built-in) to automate iterative model input
manipulation to “auto-tune” a building energy simulation to match a set of
utility bills. You can even get the curves to fit extremely tightly over
multiple meters. I’ve gone so far as to build some such tools from scratch,
and that experience has taught me some very important lessons I didn’t set
out to find. Among them, an “auto-tuned” model where many inputs are guided
by randomization and computer logic can in practice become very difficult to
trust for projecting savings, even on a relative “doesn’t need to be seen on
the bills” level.
On the other hand, if you careful to bound “auto-tuning” techniques to
reasonable input ranges, and specifically to address “unknowable” model
inputs which cannot be measured or reasonably estimated/inferred, the
results can become much more useful, even enlightening. This “optimal”
usage of the likes of monte carlo analysis, with and without machine
learning algorithms, is anything but an “easy” button.
I use doe2/eQuest as my primary energy simulation platform, however all of
the above advice is platform-agnostic and holds true whether you’re
crunching degree-day analyses in excel or wielding rooms of supercomputers
in the cloud with e+.
If calibration matters, and you’re not doing so just to tick some
prescriptive box, best practice during model development is to keep mindful
track of which inputs are:
1. Known
a. General Hierarchy of “Known:” Design/Construction Documents <
As-Builts < RCx reports < Current field measurements & observations
b. Be mindful that construction documents and nameplate data are better
than nothing, but commonly do not match reality and may be better considered
as “informed estimates.” Allow some room for doubt.
2. Estimated
a. For existing buildings, this most inputs will be “estimated.”
b. If for example you have to define fan power based on scheduled
static pressure loss and airflows on the drawings
that’s just aligning your
estimate with the designer’s. Actual is probably something different.
c. Software defaults you understand are ready to “own” or explain fall
under this category
d. This includes anything “auto-sized”
3. Guesswork
a. This includes software defaults that you are relying upon but
haven’t yet investigated/understood.
b. This includes “known unknowns” for lack of information / resources.
c. A pretty common example is envelope constructions where (a) you have
no architectural details/specifications to reference all the layers in the
middle and (b) you aren’t budgeted/resourced to tear up a client’s walls to
find out what’s inside.
Considering the degree of input complexity for something like an eQuest
model, I feel there will always be some blend of all if these input
categories for every project and every individual modeler. Experience
helps, though as the years pile on, for every new topic I get a lock on
measuring/estimating, I feel like I learn about two more issues that were
previously not on my radar
“the more I see the less I know!”
Having rough estimates and unknowns is fine, but the more that you know or
else can reasonably estimate, the better your initial calibration results
will turn out, and the quicker the process of iteratively “tuning” a model
will go. When you have a good record kept of which inputs are particularly
solid vs. estimated/guesswork, you can work your way up the tree, marrying
that knowledge to assumed/tested input sensitivity on the results, and plot
a course to find your way back to the billed amounts!
Hope this is helpful!
~Nick
Nick Caton, P.E., BEMP
Senior Energy Engineer
Regional Energy Engineering Manager
Energy and Sustainability Services
Schneider Electric
D 913.564.6361
M 785.410.3317
F 913.564.6380
E <mailto:nicholas.caton at schneider-electric.com>
nicholas.caton at schneider-electric.com
15200 Santa Fe Trail Drive
Suite 204
Lenexa, KS 66219
United States
From: Equest-users [mailto:equest-users-bounces at lists.onebuilding.org
<mailto:equest-users-bounces at lists.onebuilding.org> ] On Behalf Of David
Eldridge via Equest-users
Sent: Saturday, May 19, 2018 2:08 PM
To: equest-users at onebuilding.org <mailto:equest-users at onebuilding.org>
Subject: Re: [Equest-users] eQUEST Calculations
If you mean automatically adjusting the parameters of the model inputs to
minimize error against the actual utility data by using a basis such as
ASHRAE Guideline 14, then no eQUEST does not have that capability built in.
You wouldn’t be changing the internal calculations – some review of the
inputs and outputs should provide insight into what variables are known and
which are assumed and may have a reasonable range of values resulting in a
better fit to the utility data.
With some on-site data such as what you’d be collecting for energy audits
anyway, you can usually get an accurate model to start with, or with few
iterations.
There are other code/programs/platforms available that can help optimize,
but requires a little more effort up front to either run the programming
yourself or using a packaged program to setup the modeling files in a
different program and tell the optimization program which variables have
which range of values to be allowed.
I hope this helps.
David
David S. Eldridge, Jr., P.E., LEED AP BD+C, BEMP, BEAP, HBDP
Associate
Direct: (847) 316-9224 | Mobile: (773) 490-5038
Grumman/Butkus Associates | 820 Davis Street, Suite 300 | Evanston, IL 60201
Energy Efficiency Consultants and Sustainable Design Engineers
<http://grummanbutkus.com/> grummanbutkus.com |
<http://grummanbutkus.com/blog> Blog |
<https://www.facebook.com/pages/GrummanButkus-Associates/1385285015032526>
Facebook | <https://twitter.com/grummanbutkus> Twitter
From: Equest-users [mailto:equest-users-bounces at lists.onebuilding.org] On
Behalf Of Tom McGovern via Equest-users
Sent: Friday, May 18, 2018 4:45 PM
To: equest-users at lists.onebuilding.org
<mailto:equest-users at lists.onebuilding.org>
Subject: Re: [Equest-users] eQUEST Calculations
Hello,
Have a question regarding the internal calculations performed by eQUEST. Am
new to eQUEST and just looking to understand some basics. Trying to figure
out if there is some way to modify internal eQUEST calculations so baseline
model may be adjusted to fit existing utility bills or if there is no way to
modify internal eQUEST calculations and we need various end arounds to fit
baseline eQUEST model to fit existing utility bills.
Thanks,
Tom McGovern
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