西安市夏季公共建筑室内环境可持续性评价与优化研究

IF 2.1 Q2 CONSTRUCTION & BUILDING TECHNOLOGY Intelligent Buildings International Pub Date : 2020-10-01 DOI:10.1080/17508975.2019.1567456
Yifang Si, Junqi Yu, Nan Wang, Xisheng Ding, Longfei Yuan
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引用次数: 2

摘要

摘要随着人们在建筑中花费时间的增加,人们越来越关注能源消耗和室内舒适度的提高。夏季,在公共建筑的高占用密度空间中,建筑运营需要更多的能源,因为大部分能源都是为了使室内环境舒适而消耗的。因此,优化存在一个矛盾的问题,即最小能耗与最大室内舒适度。本文基于热环境和空气质量的权重,建立了室内舒适度模型。采用改进的非支配排序遗传算法Ⅱ(NSGA-II)多目标优化方法,根据不同的室外气象参数和不同的室内占用密度,对作为关键性能指标的室内气温、室内相对湿度和室内CO2浓度进行动态优化。采用模糊综合决策的方法,从非劣解中选出一个合适的解。这些KPI的单一解可以用作空调控制器的设置点。通过案例分析,对能量和舒适度的优化进行了相应的仿真。结果表明,该方法可以实现室内舒适度的保持和能耗的降低。
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Research on evaluation and optimization of sustainable indoor environment of public buildings in Xi’an in summer
ABSTRACT 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 CO2 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.
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来源期刊
Intelligent Buildings International
Intelligent Buildings International CONSTRUCTION & BUILDING TECHNOLOGY-
CiteScore
4.60
自引率
4.30%
发文量
8
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