LAPSE:2018.0896
Published Article
LAPSE:2018.0896
Development of a Mobile Application for Building Energy Prediction Using Performance Prediction Model
Yu-Ri Kim, Hae Jin Kang
November 27, 2018
Recently, the Korean government has enforced disclosure of building energy performance, so that such information can help owners and prospective buyers to make suitable investment plans. Such a building energy performance policy of the government makes it mandatory for the building owners to obtain engineering audits and thereby evaluate the energy performance levels of their buildings. However, to calculate energy performance levels (i.e., asset rating methodology), a qualified expert needs to have access to at least the full project documentation and/or conduct an on-site inspection of the buildings. Energy performance certification costs a lot of time and money. Moreover, the database of certified buildings is still actually quite small. A need, therefore, is increasing for a simplified and user-friendly energy performance prediction tool for non-specialists. Also, a database which allows building owners and users to compare best practices is required. In this regard, the current study developed a simplified performance prediction model through experimental design, energy simulations and ANOVA (analysis of variance). Furthermore, using the new prediction model, a related mobile application was also developed.
Keywords
analysis of variance (ANOVA), energy performance certification, energy simulation, mobile application, prediction model
Suggested Citation
Kim YR, Kang HJ. Development of a Mobile Application for Building Energy Prediction Using Performance Prediction Model. (2018). LAPSE:2018.0896
Author Affiliations
Kim YR: Department of Architecture, Chung-Ang University, 84 Heuksoek-ro, Dongjak-gu, Seoul 06974, Korea
Kang HJ: Sustainable Design Team, SAMOO Architects and Engineers, 295 Olympic-ro, Songpa-gu, Seoul 05510, Korea
[Login] to see author email addresses.
Journal Name
Energies
Volume
9
Issue
3
Article Number
E160
Year
2016
Publication Date
2016-03-04
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en9030160, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2018.0896
This Record
External Link

doi:10.3390/en9030160
Publisher Version
Download
Files
[Download 1v1.pdf] (4.1 MB)
Nov 27, 2018
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
506
Version History
[v1] (Original Submission)
Nov 27, 2018
 
Verified by curator on
Nov 27, 2018
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2018.0896
 
Original Submitter
Calvin Tsay
Links to Related Works
Directly Related to This Work
Publisher Version