Model Factsheet

Overview / District Heating Transformation Thermo-hydraulic Simulation (dhTransSIM)
Name District Heating Transformation Thermo-hydraulic Simulation
Acronym dhTransSIM
Methodical Focus Simulation , Transformation / Decarbonisation , Performance Evaluation
Institution(s) Institute of Energy Economics and Rational Energy Use (IER); University of Stuttgart
Author(s) (institution, working field, active time period) Prof. Dr.-Ing. Markus Blesl; University of Stuttgart; active, Yichen Xu; M.Sc.; University of Stuttgart; active, Frank Wendel; M.Sc.; University of Stuttgart; inactive
Current contact person Prof. Dr.-Ing. Markus Blesl, Yichen Xu
Contact (e-mail) markus.blesl@ier.uni-stuttgart.de, yichen.xu@ier.uni-stuttgart.de
Website https://www.ier.uni-stuttgart.de/forschung/modelle/dhnTransLib/
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Primary Purpose Thermo-hydraulic simulation and followed by performance-oriented assessment of district heating networks. dhTransSIM supports the representation of network operation based on network topology, technical component data, heat-demand profiles and measurement-based boundary conditions. It is used to analyse temperatures, mass flows, heat flows, heat losses and operational deviations in existing or planned district heating networks.
Primary Outputs Time series of supply and return temperatures, mass or volume flows, heat flows, heat demand profiles, distribution heat losses, and selected pressure or hydraulic indicators where available. Additional outputs may include performance indicators, Excel/CSV result tables, and plots derived from the simulation and evaluation workflow.
Support / Community / Forum
Framework
Link to User Documentation -
Link to Developer/Code Documentation -
Documentation quality expandable
Source of funding Project-based
Number of developers less than 10
Number of users less than 10
Open Source
Planned to open up in the future
Costs None
Modelling software Dymola
Internal data processing software Python with Pandas; Excel
External optimizer
Additional software Excel; Python plotting and preprocessing tools
GUI
Modeled energy sectors (final energy) heat
Modeled demand sectors Households, Industry, Commercial sector
Modeled technologies: components for power generation or conversion
Renewables -
Conventional -
Modeled technologies: components for transfer, infrastructure or grid
Electricity -
Gas -
Heat distribution, transmission
Properties electrical grid -
Modeled technologies: components for storage -
User behaviour and demand side management User behaviour and demand-side management are not represented as endogenous behavioural modules in dhTransSim, but can be considered through pre-processing of the input time series. For example, heat demand profiles can be modified to represent user behaviour, load shifting, peak shaving, valley filling or other DSM strategies before they are used as boundary conditions in the thermo-hydraulic network simulation.
Changes in efficiency Changes in efficiency can be considered through scenario-specific adjustments of model parameters and input data. For example, changes in supply and return temperatures, pipe heat-loss parameters, demand profiles, operating strategies or substation-related assumptions can influence simulated heat losses, mass flows, heat flows and other efficiency-related indicators. Efficiency changes are therefore represented through modified model assumptions and evaluated via the resulting thermo-hydraulic and performance indicators.
Market models -
Geographical coverage
Geographic (spatial) resolution districts, households
Time resolution hour, 15 min, 1 min
Comment on geographic (spatial) resolution The geographical resolution is flexible and depends on the application case and data availability. A more detailed representation of pipes, nodes and consumers allows a finer spatial analysis, but requires more input data and usually increases simulation time.
Observation period <1 year, 1 year, >1 year
Additional dimensions (sector) economic
Model class (optimisation) -
Model class (simulation) Bottom up
Other
Short description of mathematical model class Modelica-based one-dimensional thermo-hydraulic network simulation using mass, momentum/hydraulic and energy-balance relations for district-heating pipes, nodes and boundary conditions. Heat transport and heat losses are represented through parameterized pipe and fluid properties.
Mathematical objective None
Approach to uncertainty Deterministic
Suited for many scenarios / monte-carlo
typical computation time less than a day
Typical computation hardware Desktop or workstation
Technical data anchored in the model Network topology, pipe lengths and diameters, pipe and fluid properties, heat-loss parameters, boundary conditions and consumer or demand-profile parameters are anchored in model input data.
Interfaces Dymola; Python/Excel
Model file format .mo
Input data file format .csv, .xlsx
Output data file format .csv + plots (.png/.html or similar)
Integration with other models
Integration of other models
Citation reference Zopff, C.; Brüggemann, T.; Sercan-Çalışmaz, K.; Blesl, M.; Wendel, F.; Xu, Y.; von Gneisenau, C. & Antoni, O. Technische, ökonomische und rechtliche Aspekte bei der Digitalisierung der Fernwärme, EuroHeat & Power, 2024, 4-5, 29-36; Wendel, F.; Blesl, M.; Mönch, M. & Huther, H. Transformationspfade und deren Einfluss auf die technische Nutzungsdauer erdverlegter Wärmeleitungen, EuroHeat & Power, 2019, 48, 32-38
Citation DOI -
Reference Studies/Models FW-Digital project report
Example research questions What can happen to a certain district heating network, if DSM is applied to it?
Model usage -
Model validation checked with measurements (measured data)
Example research questions What can happen to a certain district heating network, if DSM is applied to it?
further properties
Model specific properties -

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DEU Decarbonisation Pathway Deutschland district heating Energiebedarf Szenario regional modelling Fernwärme Heat Germany Energiewende temperature pressure heat demand