| 引用本文: | 甄蒙,孙澄,董琪.东北严寒地区农村住宅热环境优化设计[J].哈尔滨工业大学学报,2016,48(10):183.DOI:10.11918/j.issn.0367-6234.2016.10.027 |
| ZHEN Meng,SUN Cheng,DONG Qi.Thermal environment optimization design of rural residential buildings in severe cold regions of northeast China[J].Journal of Harbin Institute of Technology,2016,48(10):183.DOI:10.11918/j.issn.0367-6234.2016.10.027 |
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| 摘要: |
| 为提高东北严寒地区农村住宅室内热舒适水平，并降低采暖能耗，通过实地测试、软件模拟对其重要影响因素进行了量化分析，并建立了采暖能耗预测模型.采用BES-01型温度采集记录器、DeST-h软件研究了体形系数、窗墙面积比、围护结构传热系数、朝向、吸收系数、热惰性、附加阳光间、冰雪覆盖层等10项因素对农村住宅热环境的影响.实验结果表明：东北严寒地区农村住宅体形系数、窗墙面积比、围护结构传热系数与采暖能耗正相关，正南及南偏东为最佳朝向，吸收系数与采暖能耗负相关，附加阳光间能够有效改善室内热环境，冰雪覆盖层能够起到屋面保温作用，采暖能耗预测模型能够为农村居民建造节能住宅提供设计依据，研究能够引导并提升东北严寒地区农村住宅的节能设计水平.
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| 关键词: 东北严寒地区 农村住宅 采暖能耗 预测模型 |
| DOI：10.11918/j.issn.0367-6234.2016.10.027 |
| 分类号:TU111.4 |
| 文献标识码:A |
| 基金项目:国家自然科学基金面上项目(51278149) |
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| Thermal environment optimization design of rural residential buildings in severe cold regions of northeast China |
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ZHEN Meng, SUN Cheng, DONG Qi
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（School of Architecture, Harbin Institute of Technology, Harbin 150006, China）
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| Abstract: |
| In order to improve indoor thermal comfort and reduce the energy consumed for heating in rural residential buildings in severe cold regions of northeast China,the paper analyzed the influencing factors using field survey and software simulation and established the heating energy consumption prediction model. The paper studied the influence factors of shape coefficient,window to wall ratio,heat transfer coefficient of building envelope,orientation,absorption coefficient,thermal inertia,attached sunspace,snow cover with the help of BES-01 temperature recorder and DeST-h software. The results showed that the shape coefficient,windows to wall area ratio and heat transfer coefficient were positively correlated with heating energy consumption,the best orientation is south and southeast,absorption coefficient was negatively correlated with heating energy consumption,attached sunspace can effectively improve indoor thermal environment,and snow cover can play a role in roof insulation. The prediction model can provide design basis for rural energy-saving residential buildings. The paper can guide and improve energy efficiency design level of rural residential buildings in severe cold regions of northeast China.
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| Key words: severe cold regions of northeast China rural residential buildings heat consumption prediction model |
