This paper was presented at the 2016 International Passive House Conference. It looks at how the 1st Passive House in Kranichstein, Germany, was optimized and how this influenced the development of the Passive House Standard. Another project in Saskatoon is also reviewed to show how this new PDT-Passivhaus optimizer software service can help designers and energy modelers find the best combination of assemblies, areas and components to achieve the comfort and performance targets of the Passive House Standard.
Optimizing Passive House: A look at Kranichstein (& Saskatoon) using PDT-Passivhaus
1. Bronwyn Barry, CPHD
Darmstadt, Germany
IPHC, April 2016
Optimizing Passive House:
A look at Kranichstein (& Saskatoon) through
the lens of PDT-Passivhaus
passivhaus.protolife.com
3. • The PHPP spreadsheet can be
intimidating
• Variable exploration requires tedious
manual labor or complex macro
programming skills
• No established habit of optimization
• Opportunities to meet the Passive
House Standard are being missed
Why the need for Optimization?
passivhaus.protolife.com3
4. Our Adventure: In search of PHPP ‘source cells’...
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Image Credit: L: www.britannica.com,
R: www.moviesdvdreleases.com
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8. What we’ve developed…
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Two options:
1. Single variable fixed
optimization
2. Full dynamic
optimization & data
Outputs are:
• Graphic
• Downloadable in visual
or numeric formats.
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9. How it works…
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Software as a Service
1. User creates an account
2. Uploads a PHPP
3. Selects variables
4. Run & review results
5. Uses outputs to modify
PHPP
Web
Interface
Upload
PPHP
wb
Download
results
ProtoLife Passivhaus Server
Repeatedly launch PHPP wb
to gather data
to optimize
Microsoft
Excel
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Saskatoon: Initial PHPP Results & Assemblies
The metric PHPP results
shown above, and assemblies
shown at right are
prior to optimization.
Assemblies chart: metric in
red and IP units in white.
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20. Saskatoon: PHPP Energy Balance Graph
Find this graph in your PHPP
(Usually on the Annual
Heating Sheet)
Review to identify which items
in your project are
losing the most energy?
For this project they are:
1. Windows
2. Ventilation
3. Exterior Wall - Ambient
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Saskatoon: Selected ranges…
2- Launch!
1- Adjust sliders to a
feasible range
Note: current
value for each
variable is
provided here
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23. The following variables have constant values
for all optimizations in this range:
Window Area: 12
Airtightness: 0.18
Specific Space Heating Demand = 25.022
Saskatoon: Full Optimize results…
1- Constants are Solid Choices!
2- Review
Lowest
Outputs next
3- Review
other large
clusters
25. Saskatoon: Make design changes…
BEFORE
AFTER
South & East Elevations North & West Elevations
(Your window style & placement may vary)
26. Saskatoon: Modified PHPP Assemblies…
With your PDT-Passivhaus outputs, use the results to modify your PHPP and select the
combination that best suits your project. For this project using fewer, higher performance
windows, plus a tighter building envelope, our floor, wall and roof assemblies don’t need to
be as well insulated. Choose what best reduces costs!
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28. Summary & Future Plans: PDT-Passivhaus
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Conclusions:
1. Heating Load target appears to be
best goal for most climates
2. Culture & habit of optimization needs
to be nurtured
3. Visualization of choices is helpful
Future Plans:
• Looking for user feedback
• Currently Free to Beta Users
• Updated for PHPP v.9 (metric and IP)
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