1. 浙江大学 建筑工程学院,杭州,310058
2. 浙江大学 后勤管理处,杭州,310058
陈淑琴(1981—), 女, 副教授, 博士生导师
纸质出版:2019
移动端阅览
陈淑琴, 张喜勇, 屈利娟, 等. 区域建筑空调电力负荷特征指标体系及案例[J]. 哈尔滨工业大学学报, 2019,51(4):187-193.
CHEN Shuqin, ZHANG Xiyong, QU Lijuan, et al. Indices system to analyze the characteristics of air conditioning electrical loads of regional buildings and a case study[J]. 2019, 51(4): 187-193.
陈淑琴, 张喜勇, 屈利娟, 等. 区域建筑空调电力负荷特征指标体系及案例[J]. 哈尔滨工业大学学报, 2019,51(4):187-193. DOI: 10.11918/j.issn.0367-6234.201801116.
CHEN Shuqin, ZHANG Xiyong, QU Lijuan, et al. Indices system to analyze the characteristics of air conditioning electrical loads of regional buildings and a case study[J]. 2019, 51(4): 187-193. DOI: 10.11918/j.issn.0367-6234.201801116.
区域建筑负荷是该区域各类建筑负荷在时间和空间上的有序耦合
电力负荷特征的把握是区域能源规划的基础.为分析区域建筑空调电力负荷特征
从区域建筑空调电力负荷的时间动态特征、负荷波动特征、以及单体建筑和区域建筑负荷的耦合关系等方面建立区域建筑负荷分析指标体系
并利用GIS将建筑负荷信息可视化.最后以一典型高校校园建筑为例
利用上述方法对该校校园建筑的夏季空调电力负荷特征进行分析
得到该校各类建筑和区域建筑的夏季空调电力负荷特征及其耦合关系.分析结果表明: 就负荷水平而言该校科研类、办公类建筑负荷水平最高
教学类建筑单位面积负荷小于宿舍类建筑
但日尖峰负荷和日平均负荷则大于宿舍类建筑;就负荷波动性而言
科研、宿舍建筑日、周负荷波动小
办公和教学类建筑波动大;就单体建筑对区域负荷贡献而言
科研类、办公类
教学类建筑对区域尖峰负荷贡献大
宿舍较小.各类建筑运行模式和使用时长是影响建筑负荷特征的重要因素;区域负荷特征与区域内建筑种类和配比有关
适当的建筑类型配比有助于减小区域负荷的波动性.不同指标分析的侧重点不同
本方法所建立的指标体系可以较为全面地反映区域建筑负荷特征、以及与单体建筑负荷的耦合关系.
The load of regional buildings is the orderly coupling of the loads of different type of buildings in the region
and the mastery of electrical load characteristics are the basis of regional energy planning. To analyze the characteristics of the air conditioning electrical loads of regional buildings
an analytic indices system was established from the perspectives of dynamic features
load fluctuation features
and the load coupling relationship between the individual buildings and the regional buildings. Geographic Information System was used to visualize the characteristics of the regional loads. A typical university campus was taken as an example
and the characteristics of the air-conditioning electrical loads of the buildings on this campus were analyzed. In terms of load level
research buildings and office buildings had the highest load; teaching buildings had smaller unit area load but higher daily peak load and daily average load compared with dormitory buildings.The fluctuation of the daily and weekly load was small for research buildings and dormitories
while office buildings and teaching buildings fluctuated greatly. As for the contribution of individual buildings to the regional load
research buildings
office buildings
and teaching buildings had the larger contribution to the regional peak load
while the dormitories contributed smaller. The pattern and the length of the building operation are important factors that affect the load characteristics. The regional load characteristics are related to the types and numbers of buildings
and the appropriate proportion of building types can reduce the fluctuation of the regional load. Different indices focus on different points
and the indices system developed in this paper can fully reflect the regional load characteristics and the coupling relationship with individual buildings.
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