[Bldg-sim] 100 simulations
Joe Huang
yjhuang at whiteboxtechnologies.com
Fri Sep 11 13:04:53 PDT 2015
Parametric study of building variations is perhaps where computer simulations are at their
best in playing the what-if game!
It's troubling and unfortunate that there was more such studies back 20-30 years ago than
now, where the focus has been on developing ever more complicated building models and ever
more detailed algorithms, with the apparent goal of creating pristine one-time-use
building models.
I remember when I was first introduced to building energy simulations at UC Berkeley in
1980, one of my class assignments was to use Murray Milne's SOLAR-5 program to study the
change in loads for different building orientations. When I first went to LBNL (LBL in
those days :-)), I created a residential building energy data base for which I created 5
prototypical residential building models full of macros, which allowed me to do a hundred
parametric for each building model in 45 locations, stepping through common variations of
ceiling and wall insulation, window area/orientation/panes of glass, infiltration rates,
etc., or around 10,000-20,000 runs in all. These were then reduced to nonlinear equations
that drove simplified programs such as PEAR (Program for Energy Analysis of Residences,
LBNL 1987) or ARES (Automated Residential Energy Standard, PNNL 1989).
In 1990, I worked briefly for a East Coast consultant company that did a lot of
utility-supported DSM projects. For those, we would typically build a base building
model, and then ran it through a dozen or more EEMs requested by the A/E Team.
In 2004, I had a project to calculate U/SHGC trade-off equations for DOE's EnergyStar
Windows, for which I wrote a batch process for iterative DOE-2 simulations varying the
U-factor until the building energy use was within 0.02MBTU of the EnergyStar Window. The
same procedure could also be used to search for the minimum building energy cost, or
automated optimization.
What I'm trying to say is that parametric analysis has always been around, and not
particularly difficult to do as long as we move away from using GUI interfaces to writing
building input files with macros, and then add scripts to the batch file to set the macros
in the run stream.
Joe
Joe Huang
White Box Technologies, Inc.
346 Rheem Blvd., Suite 205A
Moraga CA 94556
yjhuang at whiteboxtechnologies.com
http://weather.whiteboxtechnologies.com for simulation-ready weather data
(o) (925)388-0265
(c) (510)928-2683
"building energy simulations at your fingertips"
On 9/11/2015 7:17 AM, R B wrote:
> Dan,
> You are right that most of the 'optimization' happens once all the massing/shape/room
> locations/configurations are finalized. Even now, I dread when I am asked to help with
> energy analysis during the early design phase since I have this at the back of the mind
> that the architect might come back with several totally new designs (shape/floors etc.)
> and I will have to redo the whole process. This has never happened in my case, and most
> decisions are WWR, insulation, glass types, shading and major system types.
> To get back to your question, for the type of analysis that you have outlined, you might
> want to look at the expert system based research in architecture departments where they
> work on automatic design generation. Carnegie Mellon comes to mind since I was involved
> in this type of work ages back (that was in the 90's.). Microstation/Autocad might have
> these kind of tools inbuilt by now (I havn't really kept up with this topic), and since
> they also have energy tools connection - what you are suggesting seems doable.
> -Rohini
>
> On Thu, Sep 10, 2015 at 4:33 PM, Dan Johnson <dan at designandenergy.com
> <mailto:dan at designandenergy.com>> wrote:
>
> Aaron and Jason, I like this thread. I noticed that the curve Aaron presented for
> WWR vs. Source Energy shows only a 4% difference in Source Energy over a range of
> 0-50% WWR---I would say a negligible difference from optimizing this component
> alone. An architect would shrug this off, despite the thought and computing power
> that went into it. This got me to thinking that, as an architect, the aspect my
> colleagues most have trouble with is the arrangement of building elements, rather
> than the optimization of each one.
>
> Jason's questions related to arrangement---how many floors? what shape
> building?---would be the most useful for conceptual design, in my opinion. I would
> leave alone insulation levels and even WWR at the programming/conceptual stage, and
> instead run hundreds of simulations with different *arrangements* of zones. I would
> further clarify this point by adding to Jason's questions list:
>
> 1. Does the conference room go on the east or west (re: sun exposure)? Under the
> roof, or in the basement?
> 2. How deep can floor plates be, and still achieve adequate daylighting?
> 3. What aspect ratio of the atrium vs. the floor plates gives us adequate natural
> ventilation?
> 4. If I put the fume hoods in the classroom, I have to ventilate the whole
> classroom, but if I put them only in prep rooms, that is a much smaller air
> volume...what difference does this make?
> 5. If I cluster all my public circulation to one side, and naturally ventilate this,
> how much energy do I save vs. distributed circulation that is conditioned with fans?
> 6. Add a giant, beautiful glass staircase---do I save enough elevator energy to
> offset the conditioning of the staircase?
>
> In typical optimization modeling, the geometry is fixed and we vary the component
> parameters. I'd like to see the opposite.
>
> If the auto-generating algorithm could produce a 3D mass diagram of color-coded zone
> blobs, perhaps as a Sketchup object, that would communicate well.
>
> Again, architects tend to have trouble with the spatial arrangement of zones as
> something driven by performance. Perhaps the most useful thing at the
> programming/concept design stage is help with arrangement. Thank you, Dan J
>
> Dan Johnson | Design and Energy | 510.325.5672 <tel:510.325.5672>
> Assoc. AIA, ASHRAE, LEED AP, CEPE, CPHC | 907 Ramona Ave. Albany California 94706
>
>
> ---------- Forwarded message ----------
> From: Aaron Powers <caaronpowers at gmail.com <mailto:caaronpowers at gmail.com>>
> To: Jason Glazer <jglazer at gard.com <mailto:jglazer at gard.com>>
> Cc: bldg-sim at onebuilding.org <mailto:bldg-sim at onebuilding.org>
> Date: Thu, 10 Sep 2015 12:46:16 -0500
> Subject: Re: [Bldg-sim] 100 simulations
> Jason,
>
> This is something I'm interested in as well. I think all the preliminary design
> factors that you mentioned are great things to look at. On the later parts of
> the design process, control parameters are also good things to look at (CHW
> plant control optimization, air-side control optimization, etc.).
>
> One way to convey the information is through simple 2D plots. Below is an
> example of 200 DOE2 simulations while varying the window to wall ratio and
> another plot of 81 simulations varying the window shading coefficient.
>
> Inline image 1Inline image 2
>
>
>
> Unfortunately, this does not convey the interactive nature of optimization over
> multiple variables. Using multidimensional optimization algorithms can be
> another useful tool, but they can be tricky. As an example, below is a case of
> looking for the optimal minimum condenser water flow in a variable flow
> condenser system. From looking at the first plot, the function seems relatively
> smooth and it's obvious that there's an optimal in the neighborhood of 0.6.
> However, if you zoom in (second plot), you can see that the data is not very
> smooth, and there are all kinds of jagged local minima/maxima. These will tend
> to throw off most optimization algorithms, which is why I think it's helpful to
> consider looking at automated mass simulations before taking on the problem of
> optimization.
>
> Inline image 5
>
> Inline image 4
> Aaron
>
> On Wed, Sep 9, 2015 at 4:33 PM, Jason Glazer <jglazer at gard.com
> <mailto:jglazer at gard.com>> wrote:
>
> I am just finishing up a project that performed about 60 automated
> simulations (using Python with EnergyPlus and Eppy) for a series of
> buildings in a bunch of cities. The power of automating simulations to
> understand the energy savings of different measures is very impressive no
> matter what tools are being used. It has made me wonder about when does
> automation make the most sense during the design process and what
> information can be provided to an architect or entire building design team
> to encourage low energy building design. I am thinking one of the most
> influential times might be during the architectural programming and early
> conceptual design steps. At this point the number of separate pieces of
> information is probably low enough that it could be filled out on a web form:
>
> - number of occupants
>
> - amount of area needed for different types of spaces
>
> - location of the lot lines
>
> - building location
>
> Conceivably, with that information, all sorts of various building
> configurations could be created automatically by a clever script then
> simulated and the resulting answers summarized.
>
> - How many floor building uses the least energy?
>
> - What shape building uses the least energy?
>
> - What is the impact of more roof insulation?
>
> - What is the impact of more or less fenestration on loads and daylighting?
>
> I would not expect the design team to use any of the automatically created
> building models directly but it might influence the design process in a good
> way if it was easy to get and easy to understand. I understand people have
> been researching the optimization of these kinds of factors but I am not
> sure that is necessary. Maybe just several different series of simulations
> illustrating various building options and their impact onenergy might be
> enough to get the discussion going.
>
> - So what questions do you think could be answered by such an automated
> system during early conceptual design?
>
> - How would you best convey that information to the building design team?
>
> - Are there other times that a suite of automated simulations would make sense?
>
> A lot of useful information could be generated with a hundred automated
> simulations!
>
> Jason
>
> --
> Jason Glazer, P.E., GARD Analytics, 90.1 ECB chair
> Admin for onebuilding.org <http://onebuilding.org> building performance
> mailing lists
>
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>
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