Research on evaluation and optimization of sustainable indoor environment of public buildings in Xi'an in summer

There have been more concerns over energy resource depletion and indoor comfort improvement along with the increased time spend in a building. Building operation requires more energy in the spaces of high occupancy density in public buildings in summer because most energy has been consumed to make t...

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Bibliographic Details
Published in:Intelligent buildings international (London) 2020-10, Vol.12 (4), p.271-283
Main Authors: Si, Yifang, Yu, Junqi, Wang, Nan, Ding, Xisheng, Yuan, Longfei
Format: Article
Language:English
Subjects:
Air conditioning
Air quality
Air temperature
Carbon dioxide
Comfort
Density
Depletion
Energy consumption
Energy sources
fuzzy comprehensive decision
Genetic algorithms
Indoor air pollution
Indoor environments
Meteorological parameters
multi-objective optimization
Multiple objective analysis
Occupancy
Optimization
Public buildings
Relative humidity
Resource depletion
Sorting algorithms
Summer
Sustainable indoor environment
Thermal environments
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Summary:There have been more concerns over energy resource depletion and indoor comfort improvement along with the increased time spend in a building. Building operation requires more energy in the spaces of high occupancy density in public buildings in summer because most energy has been consumed to make the indoor environment comfortable. Therefore, there is a conflicting issue for optimization, which is minimum energy consumption vs. maximum indoor comfort. In this paper, the indoor comfort model was established based on the weights of the thermal environment and air quality. The indoor air temperature, indoor relative humidity and indoor CO 2  concentration as KPI (Key performance indicators) are optimized dynamically according to different outdoor meteorological parameters and different indoor occupancy density by an improved multi-objective optimization method of Non-dominated Sorting Genetic Algorithm II (NSGA-II). A single suitable solution from the non-inferior solutions is selected by the method of fuzzy comprehensive decision. The single solution of those KPI can be used as the set point of air-conditioning controller. A case study was carried out and the corresponding simulation of optimization of energy and comfort was presented. The results showed that the methodology can achieve the maintenance of indoor comfort and energy consumption reduction.
ISSN:1750-8975
1756-6932
DOI:10.1080/17508975.2019.1567456