摘要
建筑能耗分析是建筑节能设计的关键环节,传统建筑能耗分析往往时间上存在滞后性、分析结果粗糙、精度低。基于BIM平台建立了大连市某高校教学楼的建筑信息模型,通过Dynamo可视化编程实现了对建筑信息模型外围护结构参数的自动设置和提取。通过Green Building Studio的web端获取建筑能耗模拟云计算基础数据并进行能耗定量研究与回归分析。基于计量经济学一般方法,建立了年度耗电量和燃料使用量能耗计算模型并进行验证。结果表明,能耗计算方程准确性较高,误差率分别在5%和3.8%以内。该模型计算建筑能耗方便快捷,可操作性强,可用于建筑设计阶段寒冷地区的能耗计算,为能耗分析和建筑节能定量评价提供参考。
s： Building energy consumption analysis is a key part for building energy efficiency design. Time lags, rough estimations, and low accuracy are typical challenges to the traditional building energy consumption analysis. Based on BIM, a building information model of a teaching building in Dalian is established. The parameters of the external envelop enclosure of building information model is automatically set up and extracted by Dynamo visual program. The basic simulation parameters of building energy consumption are calculated by Web of Green Building Studio, and then the quantitative study on energy consumption and regression analysis are conducted. Based on the methods of econometrics, an energy consumption model of annual power consumption and annual fuel consumption are established and verified. The results show that the energy consumption calculation model has good accuracy and its error rate is less than 5% and 3.8% respectively. The proposed model has good calculation efficiency and operability. It can be used to calculate the energy consumption of buildings in cold regions at the design stage. It also provides references for energy consumption analyses and quantitative evaluations on building energy conservation.
作者
梁玉美
陈小波
LIANG Yu-mei;CHEN Xiao-bo(School of Investment ＆ Construction Management,Dongbei University of Finance ＆ Economics,Dalian 116025,China;School of Investment＆Construction Management,Construction Management Research Center,Dongbei University of Finance ＆ Economics,Dalian 116025,China)
出处
《工程管理学报》
2018年第3期86-91,共6页
Journal of Engineering Management
基金
国家自然科学基金青年科学基金项目(71701033)
大连市高层次创新人才支持计划"大连市青年科技之星"项目(2017RQ005)
关键词
BIM
Dynamo编程
外围护结构
能耗分析
回归模型
BIM： Dynamo programming
external envelopenclosure： energy consumptionanalysis
regression model
