A Thermal AnalysisOf P-Block

Presented by Owen Laroque

Contents

Background

Method of Analysis

The Zone

Results

The next step

Background

Statistical method

Box-Jenkins Feed-forward networks

Ideal conditions vs current

Method of analysis

Statistical Method

Thermodynamic and HVAC

Why is the thermodynamic approach better?

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

Thermodynamic and HVAC approach

Understanding the application of principles

What does occupancy and out door conditions actually do?

Data based analysis

HVAC vs Statistical approach

Statistical analysis is focused on finding optimal conditions

HVAC is focused on what the operating conditions are and why

Zoning

Multiple computers

Screen wall

Ranging Occupancy

High volume over multiple levels

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

Electrical load

High load environment

Lots of lighting

Lots of computers

Screen wall

Projectors

Brisbane Climate

28oC – 35oC

High humidity

Next to Highway therefore poor air quality

Data Supply air temperature from air handling unit

Return air temperature from zone

Relative humidity in zone

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

Return air temperature

Expected to be relatively consistent and stable

Expected to clearly drop when system is turned on

See affects of occupancy

Humidity See clear dehumidification

Is an indication to whether the system is on or not

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

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

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

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

Next steps

Conduct research on thermal comfort PMVs

See possible changes that can be made to operating conditions

Compare to benchmarks of other buildings