Optimizing Passive House: A look at Kranichstein (& Saskatoon) using PDT-Passivhaus

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

Overview:
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322.5
400
15.2
26.4
70
200
0.825
0.96
66
198
0.15
0.9
8.285
12.964
TreatedFloorAreaforAnnual...1
WindowSurfaceArea
WalltoAmbientSurfaceArea
HRV/ERVRecovery%Efficiency
ThermalMassBenefit
Airtightnessbenefit
SpecificSpaceHeatingDemand
variable
value
Full optimization, top 1 − 20 results
• The need for optimization &
the birth of PDT-Passivhaus
• Looking at Kranichstein – was
it optimized?
• A demo project in Saskatoon
• Future Plans & Questions
2

• 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

Our Adventure: In search of PHPP ‘source cells’...
Image Credit: L: www.britannica.com,
R: www.moviesdvdreleases.com
4

Your intrepid explorers
Norman Packard Ralph Barhydt Bronwyn Barry William Barhydt
5

In search of variables…
passivhaus.protolife.com6

Where we began…
Variable
specification
Graphical
output
7

What we’ve developed…
Two options:
1. Single variable fixed
optimization
2. Full dynamic
optimization & data
Outputs are:
• Graphic
• Downloadable in visual
or numeric formats.
8

How it works…
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
9

Looking at Kranichstein…

Kranichstein: By the Assemblies…
Exterior Wall U-Value Basement Ceiling U-Value
Roof U-Value Window Surface Area
11

Kranichstein: By Window Areas…
North Window Area West Window Area
South Window Area
12

Kranichstein: Heat Load vs Heating Demand…
Window Surface Area Avg. Window U-Value Exterior Wall U-Value
Roof U-Value HRV/ERV Recovery % Efficiency Airtightness Benefit
Window Spacer Psi Value South Window Area
13

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21.7
39.925
0.688
0.96
0.12
0.4
0.504
0.93
0.1
0.125
1.904
3.714
WindowSurfaceArea
HRV/ERVRecovery%Efficiency
Airtightnessbenefit
WindowFrameU−Value
ExteriorwallU−value
SpecificSpaceHeatingDemand
variable
value
Kranichstein: Hypothetical explorations…
Radical Heating Demand Reduction if… but WHY?
14

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0.504
0.788
0.036
0.074
0.35
0.525
9.206
9.343
WindowFrameU−Value
WindowSpacerPsiValue
WindowGlassU−Value
SpecificHeatingLoad
variable
value
Kranichstein: Window Replacement…
Best Window U-Value
= 0.35 W/(m2K)
Window Frame U-Value
= 0.504 W/(m2K)
Spacer Psi Value as critical for
heat loss (more for hygiene)
Findings:
Not a significant reduction in
the overall Heat Load
15

Kranichstein: Added Solar instead…
Image Credit: @wolfgangfeist
16

Saskatoon Example Project Optimization
A small project in a challenging climate…

18
Saskatoon: Climate and Location

19
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.

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

21
Saskatoon:‘Full Optimize’ Option…
1- Select the ‘Full Optimize’ tab
2- Select your Target
3- Select your Variables
4- Configure

22
Saskatoon: Selected ranges…
2- Launch!
1- Adjust sliders to a
feasible range
Note: current
value for each
variable is
provided here

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

24
Saskatoon: Explore Heat Load Target…
1- Try Heating Load
2- Try new Variables
3- Configure

Saskatoon: Make design changes…
BEFORE
AFTER
South & East Elevations North & West Elevations
(Your window style & placement may vary)

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!

Saskatoon: Success!
This project meets the PH Standard via Heating Load

Summary & Future Plans: PDT-Passivhaus
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)
28

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Twitter: @PDT_Passivhaus
Thank You
Bronwyn Barry, CPHD
passivhaus@protolife.com
Questions?

Optimizing Passive House: A look at Kranichstein (& Saskatoon) using PDT-Passivhaus

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