Next Article in Journal / Special Issue
Enhancement of a District Heating Substation as Part of a Low-Investment Optimization Strategy for District Heating Systems
Previous Article in Journal
Carbon Sequestration Potential of Forest Invasive Species: A Case Study with Acacia dealbata Link
Previous Article in Special Issue
Experiences from City-Scale Simulation of Thermal Grids
Article

A Method for Optimizing and Spatially Distributing Heating Systems by Coupling an Urban Energy Simulation Platform and an Energy System Model

1
Fraunhofer Institute for Solar Energy Systems, Heidenhofstr. 2, 79110 Freiburg, Germany
2
Stuttgart University of Applied Sciences, Schellingstr. 24, 70174 Stuttgart, Germany
3
Institute for Visualization and Interactive Systems, Faculty of Computer Science, Electrical Engineering and Information Technology, University of Stuttgart, Keplerstraße 7, 70174 Stuttgart, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Ingo Leusbrock
Received: 31 March 2021 / Revised: 24 April 2021 / Accepted: 11 May 2021 / Published: 18 May 2021
District heating is seen as an important concept to decarbonize heating systems and meet climate mitigation goals. However, the decision related to where central heating is most viable is dependent on many different aspects, like heating densities or current heating structures. An urban energy simulation platform based on 3D building objects can improve the accuracy of energy demand calculation on building level, but lacks a system perspective. Energy system models help to find economically optimal solutions for entire energy systems, including the optimal amount of centrally supplied heat, but do not usually provide information on building level. Coupling both methods through a novel heating grid disaggregation algorithm, we propose a framework that does three things simultaneously: optimize energy systems that can comprise all demand sectors as well as sector coupling, assess the role of centralized heating in such optimized energy systems, and determine the layouts of supplying district heating grids with a spatial resolution on the street level. The algorithm is tested on two case studies; one, an urban city quarter, and the other, a rural town. In the urban city quarter, district heating is economically feasible in all scenarios. Using heat pumps in addition to CHPs increases the optimal amount of centrally supplied heat. In the rural quarter, central heat pumps guarantee the feasibility of district heating, while standalone CHPs are more expensive than decentral heating technologies. View Full-Text
Keywords: energy system optimization; district heating; energy system modelling; 3D building model; urban energy simulation platform energy system optimization; district heating; energy system modelling; 3D building model; urban energy simulation platform
Show Figures

Figure 1

MDPI and ACS Style

Steingrube, A.; Bao, K.; Wieland, S.; Lalama, A.; Kabiro, P.M.; Coors, V.; Schröter, B. A Method for Optimizing and Spatially Distributing Heating Systems by Coupling an Urban Energy Simulation Platform and an Energy System Model. Resources 2021, 10, 52. https://0-doi-org.brum.beds.ac.uk/10.3390/resources10050052

AMA Style

Steingrube A, Bao K, Wieland S, Lalama A, Kabiro PM, Coors V, Schröter B. A Method for Optimizing and Spatially Distributing Heating Systems by Coupling an Urban Energy Simulation Platform and an Energy System Model. Resources. 2021; 10(5):52. https://0-doi-org.brum.beds.ac.uk/10.3390/resources10050052

Chicago/Turabian Style

Steingrube, Annette, Keyu Bao, Stefan Wieland, Andrés Lalama, Pithon M. Kabiro, Volker Coors, and Bastian Schröter. 2021. "A Method for Optimizing and Spatially Distributing Heating Systems by Coupling an Urban Energy Simulation Platform and an Energy System Model" Resources 10, no. 5: 52. https://0-doi-org.brum.beds.ac.uk/10.3390/resources10050052

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop