Impact of Urban Planning Indicator on Spatial Distribution of Residential Heating and Cooling Energy Demand

被引：6
作者：
Liu, Meng [1 ,2 ]
Zhong, Yiqun [1 ,2 ]
Tan, Jingyue [1 ,2 ]
机构：
[1] Chongqing Univ, Minist Sci & Technol, Natl Ctr Int Res Low Carbon & Green Bldg, Chongqing 400045, Peoples R China
[2] Chongqing Univ, Minist Educ, Joint Int Res Lab Green Bldg & Built Environm, Chongqing 400045, Peoples R China
来源：
10TH INTERNATIONAL SYMPOSIUM ON HEATING, VENTILATION AND AIR CONDITIONING, ISHVAC2017 | 2017年 / 205卷
基金：
中国国家自然科学基金; 英国工程与自然科学研究理事会;
关键词：
Urban planning indicator; Residential heating and cooling; Energy demand; Spatial distri-bution; MODELING TECHNIQUES; CONSUMPTION; PERFORMANCE; SIMULATION; SECTOR; FORM;
D O I：
10.1016/j.proeng.2017.10.150
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
In order to estimate the residential heating and cooling energy demand in the urban scale, it's essential to get a comprehensive knowledge of the spatial distribution of the residential energy demand. Urban planning indicator is closely linked with urban form, and consequently influence the energy demand. This research aims to define the building factors which influence the residential heating and cooling energy demand, and analyses the spatial distribution of these factors in Yuzhong district of Chongqing, China. The crucial urban planning indictors is determined to analyze the impact on the building factors. Thus, it's possible to estimate its impact on the energy demand spatial distribution. (c) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：959 / 966
页数：8
相关论文
共 21 条
[1]   Modelling energy efficiency performance of residential building stocks based on Bayesian statistical inference [J].
Braulio-Gonzalo, Marta ;
Juan, Pablo ;
Bovea, Maria D. ;
Jose Rua, Maria .
ENVIRONMENTAL MODELLING & SOFTWARE, 2016, 83 :198-211
[2]  
Chen Xi, 2016, APPL ENERGY
[3]   Energy modelling of district cooling system for new urban development [J].
Chow, TT ;
Fong, KF ;
Chan, ALS ;
Yau, R ;
Au, WH ;
Cheng, V .
ENERGY AND BUILDINGS, 2004, 36 (11) :1153-1162
[4]   A simplified method to predict hourly building cooling load for urban energy planning [J].
Duanmu, Lin ;
Wang, Zhenjiang ;
Zhai, Zhiqiang John ;
Li, Xiangli .
ENERGY AND BUILDINGS, 2013, 58 :281-291
[5]   The impact of urban form on US residential energy use [J].
Ewing, Reid ;
Rong, Fang .
HOUSING POLICY DEBATE, 2008, 19 (01) :1-30
[6]  
Fu Lin, 2008, URBAN DEV RES, P151
[7]   Impact of urban planning on household's residential decisions: An agent-based simulation model for Vienna [J].
Gaube, Veronika ;
Remesch, Alexander .
ENVIRONMENTAL MODELLING & SOFTWARE, 2013, 45 :92-103
[8]  
Griffith B, 2006, METHODOLOGY ANAL TEC
[9]  
Guo Jia Xiang, 2013, RESIDENTIAL ENERGY C
[10]   Using building energy simulation and geospatial modeling techniques to determine high resolution building sector energy consumption profiles [J].
Heiple, Shem ;
Sailor, David J. .
ENERGY AND BUILDINGS, 2008, 40 (08) :1426-1436
123