Effect of Architectural Building Design Parameters on Thermal Comfort and Energy Consumption in Higher Education Buildings
Abstract
:1. Introduction
2. Research Methods
2.1. Simulation Process Using Monte Carlo (MC) Technique
2.2. Prototype Description of the Application of BES Model to Building Design Example and Climate
- −32.80 latitude and 151.83 longitude.
- Altitude of 33 m above sea level.
- Mean annual minimum and maximum temperatures of 14.3 °C and 21.8 °C.
- Annual mean global radiation of 4.8 kWh/m2.
2.3. Determination of Input and Output Variables
2.4. Sampling and Assignment of Probability Density Functions
# | Input Parameter (Probability Distribution: Normal) | Input Units | Summary Statistics | ||||||
---|---|---|---|---|---|---|---|---|---|
Min | Max | Mean | Median | Q1 * (25%) | Q3 * (75%) | SD * | |||
1 | Window to wall ratio [11,16,51,56] | % | 5 | 75 | 40 | 40 | 33 | 47 | 10 |
2 | Cooling set-point temperature [16,51] | °C | 19 | 28 | 25 | 25 | 24 | 26 | 2 |
3 | Heating set-point temperature [16,51] | °C | 17 | 23 | 20 | 20 | 19 | 21 | 1 |
4 | Building orientation [11,56] | Angle (°θ ) | 0 (N) * | 315 | 157 | 135 | 45 | 225 | 103 |
5 | Occupancy density [86] | people/m2 | 0.1 | 0.5 | 0.3 | 0.3 | 0.3 | 0.3 | 0.05 |
6 | Mech. Vent. rate per area [87] | l/s/m2 | 2 | 8 | 5 | 5 | 4 | 6 | 1 |
7 | Thermal mass [16,51] | - | −1 | 1 | −0.001 | 0 | −1 | 1 | 0.8 |
8 | Roof window opens ratio [88,89] | % | 3 | 17 | 10 | 10 | 9 | 11 | 2 |
9 | Infiltration [16,86] | Ac/h | 0.4 | 2 | 1 | 1 | 0.9 | 1 | 0.2 |
# | Input Parameter (Probability Distribution: Discrete) | Input Details | |
---|---|---|---|
10 | External wall construction [11,16,56,88,91] | Description | Frequency |
| U-value = 1.949 * | 371 | |
R-value = 0.513 * | |||
| U-value = 0.950 | 370 | |
R-value = 1.053 | |||
| U-value = 0.403 | 367 | |
R-value = 2.482 | |||
| U-value = 0.351 | 372 | |
R-value = 2.846 | |||
| U-value = 2.767 | 366 | |
R-value = 0.361 | |||
11 | Roof construction [11,56,88,91] | ||
| U-value = 3.439 | 311 | |
R-value = 0.291 | |||
| U-value = 2.605 | 301 | |
R-value = 0.384 | |||
| U-value = 1.431 | 308 | |
R-value = 0.699 | |||
| U-value = 6.223 | 308 | |
R-value = 0.161 | |||
| U-value = 0.252 | 310 | |
R-value = 3.972 | |||
| U-value = 0.239 | 308 | |
R-value = 4.192 | |||
12 | Glazing type [11,16,56,88] | ||
| U-value = 6.257 | 362 | |
SHGC = 0.713 | |||
| U-value = 5.302 | 378 | |
SHGC = 0.320 | |||
| U-value = 2.708 | 365 | |
SHGC = 0.697 | |||
| U-value = 3.226 | 373 | |
SHGC = 0.619 | |||
| U-value = 1.798 | 368 | |
SHGC = 0.643 | |||
13 | Local shading type [11,86] | 0.5 m projection Louvre | 230 |
1.0 m projection Louvre | 235 | ||
1.5 m projection Louvre | 234 | ||
No shading | 222 | ||
0.5 m Overhang | 235 | ||
1.0 m Overhang | 231 | ||
1.5 m Overhang | 231 | ||
2.0 m Overhang | 228 | ||
14 | Location template [94,95] | Newcastle | 923 |
Sydney | 923 | ||
15 | Crack template (airtightness) [96,97,98] | Excellent | 364 |
Good | 373 | ||
Medium | 373 | ||
Poor | 366 | ||
Very poor | 372 |
3. Results and Discussion
3.1. Uncertainty Analysis (UA)
3.2. Sensitivity Analysis (SA)
3.2.1. Influential Factors on Energy Consumption for Each Output
3.2.2. Influential Factors on Thermal Comfort for each Output
3.3. The Effect of ABDPs on Indoor Thermal Environment
3.3.1. Effect of Cooling and Heating Set-Point Temperatures
3.3.2. Effect of Roof and Wall Construction and Thermal Mass
3.3.3. Effect of Glazing, Window to Wall Ratio and Shading Devices
3.3.4. Effect of Occupancy Density
3.3.5. Effect of Infiltration Rate and Mechanical Ventilation Rate per Area
3.3.6. Effect of Building Orientation
3.4. Relationship between Students’ Thermal Discomfort Hours and Building Energy Consumption
4. Conclusions
- (1)
- The simulation results showed a significant potential to optimise the ABDPs to achieve energy saving and thermal comfort in educational buildings in NSW, Australia.
- (2)
- Based on the parametric and sensitivity analyses, there is a very weak relationship between the students’ thermal discomfort hours and the building cooling/heating load. However, the cooling and heating set-point temperatures, as well as roof construction, had a significant impact on the sensitivity of the ABDPs for both building energy consumption and student thermal comfort (p = 0.0000).
- (3)
- Increasing the cooling set-point temperature from 22 °C to 28 °C and using a U-value of 0.239 W/m2K in roof construction can reduce the operative temperatures by 14.2% and 20.0%, respectively. These reductions could significantly lower the thermal discomfort hours by 6.0 and 3.25 times, respectively.
- (4)
- The findings of this study are particularly useful for architectural design teams because they enable designers to decide easily which of the sensitive ABDPs are more important than the others based on the simulation outcomes. Moreover, architectural design teams can save time by not focusing on ABDPs that have small effects on thermal comfort and energy consumption.
- (5)
- However, there remains a number of important challenges and areas for additional study. For example, there is a need for more studies regarding indoor thermal performance and students’ thermal comfort, as well as students’ academic performance. More work is required to design performance criteria to quantitatively evaluate the ABDPs with UA and SA capabilities.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Acronyms
ABCB | Australian Building Codes Board |
ABDPs | Architectural Building Design Parameters |
BCA | Building Code of Australia |
BES | Building Energy Simulation |
EPW | EnergyPlus Weather file |
HVAC | Heating, Ventilation and Air Conditioning |
IAQ | Indoor Air Quality |
IEQ | Indoor Environmental Quality |
LHS | Latin Hypercube Sampling |
MC | Monte Carlo |
MV | Mechanical Ventilation |
NSW | New South Wales |
PA | Parametric Analysis |
PMV | Predicted Mean Vote |
PPD | Predicted Percentage Dissatisfaction |
ROC | Rate Of Change |
SA | Sensitivity Analyses |
SD | Standard Deviation |
SHGC | Solar Heat Gain Coefficient |
SRC | Standardised Regression Coefficient |
UA | Uncertainty Analysis |
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The Extent of the Impact | ABDPs | Output 1 Thermal Discomfort Hours | ABDPs | Output 2 Energy Consumption | ||
---|---|---|---|---|---|---|
SRC | p-Value | SRC | p-Value | |||
Cooling set-point temperature (°C) | 0.5705 | 0.0000 * | Cooling set-point temperature (°C) | −0.6926 | 0.0000 * | |
Flat roof construction | −0.4317 | 0.0000 * | Flat roof construction | −0.4086 | 0.0000 * | |
Heating set-point temperature (°C) | −0.3389 | 0.0000 * | Heating set-point temperature (°C) | 0.1852 | 0.0000 * | |
Occupancy density (people/m2) | −0.0501 | 0.0006 * | External wall construction | 0.0553 | 0.0001 * | |
Glazing type | −0.0409 | 0.0049 * | ||||
Mech. vent rate per area (l/s/m2) | 0.0345 | 0.0178 * | Infiltration (ac/h) | 0.0525 | 0.0001 * | |
Infiltration (ac/h) | 0.0319 | 0.0282 * | Window to wall ratio (%) | 0.0519 | 0.0001 * | |
Occupancy density (people/m2) | 0.0472 | 0.0006 * | ||||
Crack template (airtightness) | −0.0272 | 0.0612 | Crack template (airtightness) | −0.0214 | 0.1165 | |
External wall construction | 0.0259 | 0.0749 | Roof window opens ratio (%) | −0.0214 | 0.1166 | |
Building orientation (°) | 0.0176 | 0.2270 | Thermal mass | −0.0157 | 0.2478 | |
Window to wall ratio (%) | −0.0162 | 0.2646 | Building rotation (°) | 0.0129 | 0.3436 | |
Local shading type | −0.0087 | 0.5496 | Mech. vent rate per area (l/s-m2) | 0.0099 | 0.4695 | |
Thermal mass | −0.0061 | 0.6743 | Location template | −0.0097 | 0.4744 | |
Location template | −0.0028 | 0.8472 | Local shading type | −0.0085 | 0.5306 | |
Roof window opens (%) | −0.0027 | 0.8531 | Glazing type | 0.0029 | 0.8302 |
Correlations | |||
---|---|---|---|
Discomfort (All Clothing) (h) | Total Site Energy Consumption (kWh) | ||
Discomfort (All Clothing) (h) | Pearson Correlation | 1 | −0.033 |
Sig. (2-tailed) | - | 0.153 | |
N | 1845 | 1845 | |
Total site energy consumption (kWh) | Pearson Correlation | −0.033 | 1 |
Sig. (2-tailed) | 0.153 | - | |
N | 1845 | 1845 |
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Alghamdi, S.; Tang, W.; Kanjanabootra, S.; Alterman, D. Effect of Architectural Building Design Parameters on Thermal Comfort and Energy Consumption in Higher Education Buildings. Buildings 2022, 12, 329. https://doi.org/10.3390/buildings12030329
Alghamdi S, Tang W, Kanjanabootra S, Alterman D. Effect of Architectural Building Design Parameters on Thermal Comfort and Energy Consumption in Higher Education Buildings. Buildings. 2022; 12(3):329. https://doi.org/10.3390/buildings12030329
Chicago/Turabian StyleAlghamdi, Salah, Waiching Tang, Sittimont Kanjanabootra, and Dariusz Alterman. 2022. "Effect of Architectural Building Design Parameters on Thermal Comfort and Energy Consumption in Higher Education Buildings" Buildings 12, no. 3: 329. https://doi.org/10.3390/buildings12030329