Novel validated method for GIS based automated dynamic urban building energy simulations

P. Nageler, G. Zahrer, R. Heimrath, T. Mach, F. Mauthner, I. Leusbrock, H. Schranzhofer and C. Hochenauer

Energy, 2017, vol. 139, issue C, 142-154

Abstract: The modelling of whole urban districts requires an automated process to parameterize simulation tools. This paper presents a validated methodology for fully automated building modelling within urban districts based on publicly available data. Dynamic building models with detailed heating systems are created in the simulation environment IDA ICE. The method of data collecting and processing and result visualization in a geographical information system (GIS) and the data storage procedure in a PostgreSQL database is described in detail. The building simulation model is validated with consumption data available from 69 buildings of the town Gleisdorf (Austria). The results of the annual heating and domestic hot water demand show a good approximation to the measurement data with a mean deviation of −0.98%. The urban simulation process was then extended to the whole community with its 1945 buildings. This method helps to model and quantitatively describe current building stock in an efficient and timesaving way and enables to develop future smart energy systems, in which the buildings interact with the district heating networks, with limited effort.

Keywords: Dynamic urban building energy simulation; Automation; GIS; IDA ICE; PostgreSQL database (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054421731335X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:139:y:2017:i:c:p:142-154

DOI: 10.1016/j.energy.2017.07.151

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().