| 居住建筑室内热环境低能耗营造的多目标设计方法 |
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| 引用本文： | 喻伟,王迪,李百战. 居住建筑室内热环境低能耗营造的多目标设计方法[J]. 土木建筑与环境工程, 2016, 0(4): 13-19. DOI: 10.11835/j.issn.1674-4764.2016.04.003 |
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| 作者姓名： | 喻伟 王迪 李百战 |
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| 作者单位： | 重庆大学 城市建设与环境工程学院 教育部绿色建筑与人居环境营造国际合作联合实验室,重庆,400045 |
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| 基金项目： | 国家自然科学基金(51408079、51578086)；建筑安全与环境国家重点实验室开放课题基金(BSBE2014-10)；重庆市研究生科研创新项目(CYB15040)@@@@National Natural Science Foundation of China (No．51408079，51578086)；Opening Funds of State Key Laboratory of Building Safety and Built Environment (No．BSBE2014-10)；Chongqing Graduate Research Innovation Project (CYB15040) |
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| 摘 要： | 人居环境改善涉及重大民生问题,节能减排是国家重大战略。因此,有必要寻求合理的居住建筑设计方法,使设计方案既满足居民的室内热舒适需求又能降低建筑能耗。基于多目标遗传优化算法,建立能够对建筑设计方案进行优化、实现增加室内热舒适时间比例的同时降低建筑全年冷热负荷的居住建筑设计双目标优化模型。最后,以重庆典型户型为实例进行优化,优化后的设计方案建筑全年冷热负荷降低了47.74%,室内热舒适时间比例提高了3.94%,验证了模型的可行性和准确性。
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| 关 键 词： | 热舒适 建筑能耗 多目标优化 适应度函数 |
Multi-obj ective design method of improving the indoor thermal environment with low energy consumption in residential building |
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| Yu Wei,Wang Di,Li Baizhan. Multi-obj ective design method of improving the indoor thermal environment with low energy consumption in residential building[J]. Journal of Civil,Architectrual & Environment Engineering, 2016, 0(4): 13-19. DOI: 10.11835/j.issn.1674-4764.2016.04.003 |
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| Authors: | Yu Wei Wang Di Li Baizhan |
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| Abstract: | To improve the living environment is a major livelihood issue,and energy saving and emission reduction is a major national strategy.Therefore,it is necessary to seek a reasonable design method which could not only meet the needs of residents in the indoor thermal comfort and reduce the building energy consumption of residential building.Based on the genetic algorithm,a multi-objective optimization model of residential building design is established which can optimize the design to increase the indoor thermal comfort time and reduce the annual cooling and heating load.Finally,taking the typical apartment of Chongqing as an example,the annual cooling and heating load of the optimized design plan is decreased by 47 .74% and the indoor thermal comfort time ratio is increased by 3 .94%,which verify the feasibility and accuracy of the model. |
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| Keywords: | thermal comfort building energy consumption multiobj ective optimization fitness function |
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