High-resolution combined building stock and building energy modeling to evaluate whole-life carbon emissions and saving potentials at the building and urban scale

2022 ◽  
Vol 177 ◽  
pp. 106000
Author(s):  
Felix Heisel ◽  
Joseph McGranahan ◽  
Joseph Ferdinando ◽  
Timur Dogan
2020 ◽  
Vol 207 ◽  
pp. 109590
Author(s):  
Bumjoon Kim ◽  
Yohei Yamaguchi ◽  
Shun Kimura ◽  
Yumei Ko ◽  
Kosuke Ikeda ◽  
...  

2019 ◽  
Vol 199 ◽  
pp. 547-561 ◽  
Author(s):  
Bumjoon Kim ◽  
Yohei Yamaguchi ◽  
Shun Kimura ◽  
Yumei Ko ◽  
Kosuke Ikeda ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1049
Author(s):  
Zhang Deng ◽  
Yixing Chen ◽  
Xiao Pan ◽  
Zhiwen Peng ◽  
Jingjing Yang

Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.


2016 ◽  
Vol 22 (1) ◽  
pp. 04015010 ◽  
Author(s):  
William O. Collinge ◽  
Justin C. DeBlois ◽  
Amy E. Landis ◽  
Laura A. Schaefer ◽  
Melissa M. Bilec

2020 ◽  
Vol 13 (5) ◽  
pp. 487-500
Author(s):  
Brian L. Ball ◽  
Nicholas Long ◽  
Katherine Fleming ◽  
Chris Balbach ◽  
Phylroy Lopez

2020 ◽  
Vol 279 ◽  
pp. 115834
Author(s):  
Usman Ali ◽  
Mohammad Haris Shamsi ◽  
Mark Bohacek ◽  
Karl Purcell ◽  
Cathal Hoare ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document