A thermal analysis
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Transcript of A thermal analysis
![Page 1: A thermal analysis](https://reader031.fdocuments.in/reader031/viewer/2022021814/58edee251a28abef188b46b5/html5/thumbnails/1.jpg)
A Thermal AnalysisOf P-Block
Presented by Owen Laroque
![Page 2: A thermal analysis](https://reader031.fdocuments.in/reader031/viewer/2022021814/58edee251a28abef188b46b5/html5/thumbnails/2.jpg)
Contents
Background
Method of Analysis
The Zone
Results
The next step
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Background
Statistical method
Box-Jenkins Feed-forward networks
Ideal conditions vs current
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Method of analysis
Statistical Method
Thermodynamic and HVAC
Why is the thermodynamic approach better?
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Statistical Method
Application of the Box-Jenkins model
Find an optimisation equation that accounts for: Air temperature
Air velocity
etc.
Compare optimised to current condition
𝑉𝑠 =𝑉𝑠𝑚𝑎𝑥 − 𝑉𝑠
𝑚𝑖𝑛
𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛𝑉 − 𝑉𝑚𝑖𝑛 + 𝑉𝑠
𝑚𝑖𝑛
𝑂 = 𝑤𝑃𝑀𝑉𝑃𝑀𝑉𝑠 − 𝑃𝑀𝑉
𝑃𝑀𝑉𝑠+ 𝑤𝐶
𝐶𝑠 − 𝐶
𝐶𝑠
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Thermodynamic and HVAC approach
Understanding the application of principles
What does occupancy and out door conditions actually do?
Data based analysis
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HVAC vs Statistical approach
Statistical analysis is focused on finding optimal conditions
HVAC is focused on what the operating conditions are and why
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Zoning
Multiple computers
Screen wall
Ranging Occupancy
High volume over multiple levels
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Occupancy
Before semester vs During semester
Low occupancy outside of class times
High volume of people when classes are on
Study area means there is generally people around
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Electrical load
High load environment
Lots of lighting
Lots of computers
Screen wall
Projectors
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Brisbane Climate
28oC – 35oC
High humidity
Next to Highway therefore poor air quality
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Data Supply air temperature from air handling unit
Return air temperature from zone
Relative humidity in zone
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Supply air temperature
Expected to rise and fall with office hours
Low during peak times
High outside of peak times
See cooling load rise and fall
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Return air temperature
Expected to be relatively consistent and stable
Expected to clearly drop when system is turned on
See affects of occupancy
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Humidity See clear dehumidification
Is an indication to whether the system is on or not
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Temperature Difference
See rise and fall in cooling load
Used to calculate heat removed from the air in the zone Area under curve)
Q=mC∆T M and C are constant, ∆T is known
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Low Occupancy
It was expected that there would be no change in operation depending on occupancy
Appears to be a three-day model that is in use for before semester and during weekends of semester (Friday – Sunday)
Much lower use of the system
Seemingly an strategy to save money
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High Occupancy This is during the week of semester.
System was expected to be in use during office hours
System is actually used from early morning to mid-afternoon
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Low vs High occupancy
For low occupancy there is approximately 5.91kWh of cooling over the 3 day pattern before semester
For high occupancy there is 3.67 kWh of cooling over one day during semester
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Next steps
Conduct research on thermal comfort PMVs
See possible changes that can be made to operating conditions
Compare to benchmarks of other buildings