Geospatial Analysis of the Building Heat Demand and Distribution Losses in a District Heating Network
1
Institute of Geography–GIScience, Heidelberg University, Im Neuenheimer Feld 368, Heidelberg 69120, Germany
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Department of Geoinformatics–Z_GIS, University of Salzburg, Schillerstrasse 30, Salzburg 502, Austria
3
Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA
4
geomer GmbH, Im Breitspiel 11b, Heidelberg 69126, Germany
5
Clustermanager GeoNet.MRN, P7 20-21, Mannheim 68161, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(12), 219; https://doi.org/10.3390/ijgi5120219
Received: 6 October 2016 / Revised: 11 November 2016 / Accepted: 16 November 2016 / Published: 24 November 2016
The district heating (DH) demand of various systems has been simulated in several studies. Most studies focus on the temporal aspects rather than the spatial component. In this study, the DH demand for a medium-sized DH network in a city in southern Germany is simulated and analyzed in a spatially explicit approach. Initially, buildings are geo-located and attributes obtained from various sources including building type, ground area, and number of stories are merged. Thereafter, the annual primary energy demand for heating and domestic hot water is calculated for individual buildings. Subsequently, the energy demand is aggregated on the segment level of an existing DH network and the water flow is routed through the system. The simulation results show that the distribution losses are overall the highest at the end segments (given in percentage terms). However, centrally located pipes with a low throughflow are also simulated to have high losses. The spatial analyses are not only useful when addressing the current demand. Based on a scenario taking into account the refurbishment of buildings and a decentralization of energy production, the future demand was also addressed. Due to lower demand, the distribution losses given in percentage increase under such conditions.
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Keywords:
GIScience; network analyses; renewable energy
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MDPI and ACS Style
Törnros, T.; Resch, B.; Rupp, M.; Gündra, H. Geospatial Analysis of the Building Heat Demand and Distribution Losses in a District Heating Network. ISPRS Int. J. Geo-Inf. 2016, 5, 219.
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