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Intelligent Algorithm-Based Modeling of Lighting and Thermal Environment Balance in Green Buildings

Hui Xiong

Hui Xiong

Xiamen Institute of TechnologyXiamen, China
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Xiong, Hui
  
21. März 2025
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Online veröffentlicht: 21. März 2025
Eingereicht: 07. Nov. 2024
Akzeptiert: 19. Feb. 2025
DOI: https://doi.org/10.2478/amns-2025-0581
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© 2025 Hui Xiong, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Double-glazed curtain wall
Double-glazed curtain wall

Figure 2.

Flowchart of genetic algorithm
Flowchart of genetic algorithm

Figure 3.

Flowchart of the NSGA algorithm
Flowchart of the NSGA algorithm

Figure 4.

Results of 30 generations of southbound dual-objective optimization
Results of 30 generations of southbound dual-objective optimization

Figure 5.

Southbound parameter optimization process
Southbound parameter optimization process

Figure 6.

Results of 30 generations of eastbound dual-objective optimization
Results of 30 generations of eastbound dual-objective optimization

Figure 7.

Eastbound parameter optimization process
Eastbound parameter optimization process

Figure 8.

Comparison of whole-day variation curves of dry bulb temperature
Comparison of whole-day variation curves of dry bulb temperature

Figure 9.

Contrast of maximum vertical temperature difference in each sunshade condition
Contrast of maximum vertical temperature difference in each sunshade condition

Figure 10.

Maximum vertical temperature difference in each centilation condition
Maximum vertical temperature difference in each centilation condition

Figure 11.

Temperature difference between glass surfaces in each sunshade condition
Temperature difference between glass surfaces in each sunshade condition

Figure 12.

Temperature difference between glass surfaces in each ventilation condition
Temperature difference between glass surfaces in each ventilation condition

Figure 13.

Contrast of indoor illuminance in each sunshade condition
Contrast of indoor illuminance in each sunshade condition

Eastbound Pareto solution set

ID Width Angle Altitude Energy-saving effect/% UDI variation/%
1 2.2 32 1.1 51.26 -6.24
2 2.2 38 1.2 51.29 -4.73
3 2.2 33 1.3 50.04 -1.21
4 2.2 35 1.4 49.92 -1.15
5 2.2 38 1.5 49.28 0.04
6 2.2 32 1.8 48.97 0.25
7 2.2 23 1.7 47.65 1.41
8 2.2 23 1.5 47.54 1.62
9 2.2 18 1.8 46.32 1.76
10 2.2 14 1.8 45.91 1.91

Lighting standard values on the reference plane of each lighting level

Lighting level Side lighting Overhead lighting
Standard value of lighting coefficient/% Standard value of indoor natural illumination/lux Standard value of lighting coefficient/% Standard value of indoor natural illumination/lux
I 5 750 5 750
II 4 600 3 450
III 3 450 2 300
IV 2 300 1 150
V 1 150 0.5 75

Southbound Pareto solution set

ID Width Angle Altitude Energy-saving effect/% UDI variation/%
1 2.2 38 1.7 76.24 -0.27
2 2.2 41 1.7 76.42 -0.23
3 2.2 42 1.8 76.25 1.05
4 2.2 35 1.8 76.24 1.14
5 2.2 38 1.8 76.23 0.26
6 2.2 32 1.8 76.04 3.47
7 2.2 28 1.8 75.38 2.69
8 2.2 29 1.7 75.24 2.21
9 2.2 26 1.8 75.22 3.42
10 2.2 23 1.8 74.36 3.48
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