Software-in-the-Loop-simulation of a District Heating System as Test

Environment for a Sophisticated Operating Software

Ophelia Frotscher

, Thomas Oppelt

, Thorsten Urbaneck

, Sebastian Otto

, Ingrid Heinrich

Andreas Schmidt

, Thomas Göschel

Ulf Uhlig

and Holger Frey

Chemnitz University of Technology, Faculty of Mechanical Engineering, Professorship Applied Thermodynamics,

09107 Chemnitz, Germany

Ingenieurbüro Last- und Energiemanagement LEM Software, Nordplatz 6, 04105 Leipzig, Germany

inetz GmbH, Augustusburger Straße 1, 09111 Chemnitz, Germany

Keywords: Software-in-the-Loop, District Heating, Renewable Energy, Operation, Simulation, Optimisation.

Abstract: With the expansion of renewable energies, district heating (DH) systems are becoming increasingly complex.

Various heat sources like solar thermal plants and combined heat and power (CHP) plants are integrated in

parallel, in addition thermal energy storages (TES) are often used to balance load and heat generation.

Sophisticated software solutions are required to optimise the plant operation. Based on deterministic physical

models and artificial neural networks, the software Heating Network Navigator (HN-Navi) is being developed

to optimise the operation of such systems. Since tests in the real system are not possible for reasons of supply

security, the HN-Navi is first tested in a software-in-the-loop (SiL) environment. TRNSYS (version 18) is

used as simulation software to create a complex reference model (CRM) as basis for the SiL environment.

The complexity of such real energy systems can lead to potentially high computing costs when it comes to

simulating or optimising their operation as realistically and accurately as possible. For this reason, both

software tools, i.e. HN-Navi and CRM, will be developed and tested with regard to the Brühl solar DH system

in Chemnitz (Germany), whereby the finished software will also be used for other heat supply systems.

TRNSYS offers the possibility to develop own models for all system components, with which a proper

reproduction of the real system can be achieved. Within the scope of the project, practical tests and extensive

quantitative software comparisons with the real system will also be carried out. The article reports on the

development of this SiL environment and its practical feasibility.

1 INTRODUCTION

More and more district heating systems in Europe

combine different heat sources like solar thermal

plants and combined heat and power (CHP) plants

(solar district heating, 2019). In most cases a thermal

energy storage (TES) is applied for balancing load

and heat generation, e. g. the solar district heating

(DH) systems in the Brühl quarter in Chemnitz

(Urbaneck et al., 2015; Urbeneck et al., 2017,

Shrestha et al. 2017; Urbaneck et al. 2017; Urbaneck

et al. 2017). The different components within such

systems lead to complex structures with mutual

influences. This means that a quantitatively optimal

operation can only be guaranteed through the use of

sophisticated software solutions.

For this reason, numerous projects are now

dealing with the optimization of energy supply

systems. Widely used approaches include the use of

prediction models to estimate the availability of

renewable energies and energy demand (Kuboth et

al., 2019) and improved simulation models to

predictively describe the plant behaviour of such

systems (Schweiger et al. 2018).

The approach of this project, which has been

running since July 2017, is the optimization of the

supply facilities. One of the advantages is the direct

contact with the network operator without troubling

the end customers and the optimization of the control

of all system components. The developed software

system is named Heating Network Navigator (HN-

Navi) (Oppelt et al., 2018; Oppelt et al., 2018) and is

intended to help heating network operators to achieve

an optimal system operation despite difficult

boundary conditions (integration of fluctuating

renewable energy sources, varying electricity prices,

etc.) and complex technical demands.

Frotscher, O., Oppelt, T., Urbaneck, T., Otto, S., Heinrich, I., Schmidt, A., Göschel, T., Uhlig, U. and Frey, H.

Software-in-the-Loop-simulation of a District Heating System as Test Environment for a Sophisticated Operating Software.

DOI: 10.5220/0007809602230230

In Proceedings of the 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2019), pages 223-230

ISBN: 978-989-758-381-0

223

Figure 1: Integration of the Heating Network Navigator into a quarter heating system.

Figure 1 schematically shows the planned

application of the HN-Navi to the particular town

quarter DH system (in this case: Brühl quarter,

Chemnitz, Germany) (Urbaneck et al. 2017).

Considering the specific requirements:

 optimal operation of TES,

 best possible utilisation of solar irradiance,

 minimize competition of solar heat and CHP,

 minimize network supply temperature,

 maximize temperature difference between supply

and return line of the network.

The HN-Navi generates recommendation for optimal

operation from stored (Past) and currently received

(Present) measurement data as well as load and

demand forecasts (Future). This advice for a defined

time horizon is then sent back to the process control

system in order to be considered. Additionally, the

HN-Navi continuously compares operational data

from past and present in order to detect errors in the

system (Error identification).

The project consists of three stages of

development:

1. Software developments: Development and

abstraction of simulation and prognosis models,

2. Software tests: Conducting the tests in a

Software-in-the-loop (SiL) environment,

3. Software application: Performing the practice

tests in the Brühl solar DH system at Chemnitz

(Brühl system) supported by the network

operator inetz.

The first development stage has already (status:

May 2019) been completed, so the first SiL-tests of

the optimization software have already been started.

Section 2 describe the developing of a complex

reference model (CRM) to the real system and the

HN-Navi while section 3 explains the creation of the

Software-in-the-Loop (SiL) environment. Section 4

gives an outlook on the following project steps.

2 SOFTWARE DEVELOPMENT

As stated above the aim of this to project is to use the

HN-Navi in the real Brühl system. Since tests in the

real system are not possible for reasons of supply

security, the HN-Navi is first tested in a software-in-

the-loop (SiL) environment. TRNSYS (version 18) is

used as simulation software to create a CRM as basis

for the SiL environment.

In response to the requirements, the development

is done in the following steps:

1. Analysis of the real Brühl system with a heat

transfer station (HTST), two solar thermal fields,

a TES and a low temperature network,

2. Development of accurate models of the system

components for the CRM.

3. Development of the forecast models and

abstraction of the system component models for

the HN-Navi.

2.1 Analysis of the Brühl System

The main components of the plant are two solar

thermal collector fields, a two-zone-storage TES and

a HTST which connects the low-temperature network

Heat flow

Measured data

Advice t process control systemo

Collector ﬁeld flow rate Network supply temperature

Auxilliary heating request

Heating Network Navigator

Error identiﬁcation

Thermal energy storage Quarter heating networkSolar thermal plant

Primary DH network

CHP plant

Quarter heating supply system

Past

(historical database)

Present

(measeured data)

Future

(ANN, system models)

Message t network operatoro

SIMULTECH 2019 - 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

224

Figure 2: Simplified structure of the heat transfer substation (supply center), solar collector fields and two-zone storage of the

solar DH system Brühl (without pumps) and schematic representation of the most important measured system values required

by the Heating Network Navigator.

to the primary DH network. The supplied city quarter

(Brühl Chemnitz (Shrestha et al., 2018) includes

mainly apartment buildings with more than 1,300

residential units, a school and the university library.

Figure 2 schematically shows the hydraulic

design of the Brühl system. The TES can be charged

either via the HTST, the solar thermal collector fields

or the return flow from the supply system. Similarly,

the quarter can be supplied via the solar collector

fields, the TES, the HTST or in combination thereof.

The possible operating modes are listed in Table 1. A

more detailed description can be found by Shrestha

et. al. which demonstrates the entire complexity of

the system (Shrestha et al., 2018).

In addition to the various operating modes, each

system has its own specific requirements, which has

to be taken into account in the software tools.

The most important points concerning the solar DH

system Brühl are:

Network and HTST:

 Low-temperature network with supply

temperatures of about 70 °C.

 Hydraulic decoupling of the primary DH network

from the Brühl system due to pressure and

Table 1: Operating modes of the supply center for

supplying the Brühl quarter.

Operating

modes of the

supply center

Heat source

HTST

TES

Collector

fields

Yes

temperature differences in both systems.

 Consisting of a preheating (prh) and a

postheating (poh) stage each with two heat

exchanger groups (HX).

 Preheating stage using the return flow from the

primary DH network Chemnitz.

 Postheating stage using the supply flow from the

primary DH network Chemnitz (Differences

between DH systems in Table 2).

TES:

 Two-zone TES storing with a maximum

operation temperature up to 108 °C.

low-temperature network

HX prh1 - HX poh2 -

T T

V V

... heat exchanger

... postheating

... preheating

... temperature sensor

... flow rate sensor

poh

prh

return line

supply line

Software-in-the-Loop-simulation of a District Heating System as Test Environment for a Sophisticated Operating Software

225

 Charging and discharging with radial diffusors in

levels 1…4 (Figure 2), depending on operation

mode.

Table 2: Maximum pressure and temperature in the supply

line of the primary DH network and the low temperature

network (Brühl system).

Supply line

Primary DH

network

Solar DH

system

Brühl

Pressure [bar]

5,5

Temperature [°C]

140

Collector fields:

 Water is used as heat transfer medium.

 No heat exchangers between solar circuit and

supply system are required.

 Frost protection is provided by an active hot

water flow, obtained from the TES or the return

flow from the Brühl quarter (not shown in Figure

2).

2.2 The Complex Reference Model

TRNSYS (version 18) is a software environment to

simulate a variety of energy systems (TRNSYS,

2017). TRNSYS is a Fortran 95 based and well-

validated software package to consider models of

many components of energy systems. It is also

possible to the end user to implement own models.

The user-specific components can be inserted

modularly into the simulation, which facilitates the

adaptation to extensions and to future systems. In

addition, TRNSYS offers various interfaces for data

exchange (import and export) as well as for other

programs (e.g. MATLAB). For these reasons the

CRM developed here is based on TRNSYS.

To map the DH system, the most important step is the

selection of suitable components in TRNSYS which

are called Types. The various available Types were

compared to the real system on the basis of their

reproduction quality. For example the model of the

solar collector should match the efficiency curve, the

matched flow control and the collector connection,

while taking the multi-node model, the incident angle

modifier and the heat capacity of the collector into

account. Table 3 shows available Types for the model

of the flat plate collector.

Due to the high database (minute values since

May 2017) from the monitoring of the real plant, the

simulation results can be verified directly to the

measured values (Figure 2). In the example of the

solar collector the Type 539 TESS library is sufficient

accurate and is used in the simulation (TRNSYS,

2017).

For other components (e.g. TES, HTST) no

adequate models are available in TRNSYS. These

had to be created within the scope of this project.

Another important aspect in simulating complex DH

systems in TRNSYS is the realistic control of the

interaction of the individual model components. A

separate Type (Control Unit) was developed for this

purpose, see Figure 3.

This Type establishes the link between quarter

network, HTST, collector fields and TES. It

determines the mass flows in the four diffuser levels

in the TES as well as the temperatures of the mass

flows. The Type also determines the correct diffusor

level for the mass flows from the network and from

the collector planes. Furthermore, it determines the

operating condition of the storage tank and the HTST

and calculates the heat flows required for evaluation.

The boundary conditions of the simulation (weather

data and heat demand) are also considered by the

Control Unit Type.

Table 3: Evaluation of the TRNSYS models on the basis of the most important parameters, e.g. model for solar collectors.

Type

Efficiency

curve

Matched

flow

control

Collector

inter-

connection

Mutli node

model

Incident

angle

modifier

Heat

capacity

001: Flat-plate

collector

Yes

301: Matched

flow collector

model

Yes

539: Flat plate

collector with

capacitance

effects

Yes

832: Dynamic

collector model

Yes

SIMULTECH 2019 - 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

226

Figure 3: Schematic representation of the Brühl system in

as TM in TRNSYS with the central Type to connect and

control the individual model components.

The main part is to determine the respective operating

modes based on iteration methods. Thus the type

represents the core of the CRM (Figure 3).

Figure 4 compares the actual output of the

collector arrays with that calculated by the CRM for

three days. The correlation coefficient amounts 0.93

and an average deviation of -3.14 % is calculated for

this period. Deviation between measurement and

CRM for the whole year 2018 is about +4.4 %, which

demonstrates that the CRM is sufficient accruable.

By this approach the models of all system

components are developed and tested. Analogously,

all other model components were tested and

positively validated.

Using an intel®Core

i7, one year in calculation

steps of three minutes can be simulated with the CRM

in less than 4.5 minutes. This allows various tests

such as parameter variation, algorithm verification

and error detection.

Figure 4: Comparison of the measured (





, orange) and

simulated ( 





, dashed black) thermal power of the

collector fields. From 19. to 21. July 2018. The time

resolution is 15 min.

2.3 The Heating Network Navigator

The HN-Navi is intended to replace the control and

must therefore specify the optimum volume flows and

temperatures of the individual components (Figure 2)

for a defined time step. Therefore the HN-Navi

contains weather (radiation and temperature),

electricity price and load (supply temperature and

flow rate) forecasts based on artificial neural

networks. For each optimization run, are also the

current state values from the CRM (later measured

values from the real system) are used for the initial

values On the basis of the forecasts and the initial

values, the determined numerical optimization is

carried out in the main part of the HN-Navi. Like the

CRM, the main part contains models for the

respective system components.

Table 4: Classification of the parameters into “absolutely

necessary”, “necessary”, “expense-dependent” and

“unnecessary”, e.g. solar thermal plants.

Criteria

Parameter

absolutely

necessary

- field size

- collector efficiency

- collector orientation

- collector tilt

necessary

- field shadowing

- angular influence

- sky model

- heat loss at frost

protection

- soiling

expense-

dependent

- heat capacity (collector)

- separate consideration

south/ north field

unnecessary

- heat loss field

connection

In order to keep the numerical effort low and the

solvability within the framework of an at most

quadratic optimization problem, the model

components are abstracted in comparison to the

CRM. For the abstraction of the individual elements

an investigation with variation of all parameters and

correlations was conducted, using the models from

the SiL environment. The classification is based on

the resulting deviation of important parameters (yield,

heat quantities, operating hours, etc.) from the real

system in four categories:

 “absolutely necessary”: Parameter or correlation

should be considered in the same way as in the

SiL environment.

 “necessary”: Parameter or correlation should be

considered, but can be simplified, e.g. in a black

box model. Abstraction must be justified.

 “expense-dependent”: Depending on the

computing effort to be taken into account or not.

 “unnecessary”: No consideration required.

Software-in-the-Loop-simulation of a District Heating System as Test Environment for a Sophisticated Operating Software

227

Figure 5: Test procedure for the SiL Simulation; for details of the Heating Network Navigator see Figure 1.

New models were created for each system

component, which was simplified on the basis of the

criteria.

New models were created for each system

component, which was simplified on the basis of the

criteria.

Table 4 shows the classification of the

parameters using the example of solar thermal

collector arrays. New models were created for each

system component, which was simplified on the basis

of the criteria.

The HN-Navi optimizes the entire system

considering all underlying physics. Various

optimisation strategies can be considered (minimum

operating costs 



, minimum CO

emission 



The time resolution is arbitrary. The software

generates optimal control suggestions (mass flows  ,

temperatures ) for all models and elements.

3 SOFTWARE IN THE LOOP

To test the HN-Navi, communication between it and

the CRM is necessary. A separate type was created

for this process. It checks every 10 seconds a defined

exchange folder for the existing file containing the

next schedule. A maximum number of queries can be

specified to prevent hanging in the loop and must be

adjusted to the optimization time.

The procedure is shown in Figure 5.

Before the first optimization time step, the CRM

provides the optimization parameters (start time,

simulation time step, optimization time step and end

time) as well as the current system data (temperatures,

mass flows, etc.). The HN-Navi starts the

optimization, meanwhile the CRM is in a sleep mode

until the necessary values for the system operation

(temperatures, mass flows) are returned.

The state values of the simulation are written to

the same exchange folder parallel to the simulation.

This allows the optimizer to perform a continual

comparison with its forecasts, just as it would later do

in the real system.

The development of the SiL environment is

already finished (status: May 2019) and first tests are

still ongoing. Quantitative results will be presented in

future works.

4 OUTLOOK

The next steps are an iterative process, in which the

HN-Navi will be improved. The test purposes are the

solution of different operating scenarios, the

examination of the solutions and the increase of the

performance.

Therefore, there will be four stages of testing:

1. Forecasting models:

Comparing the forecasted heat demand and

weather data in their daily forecast to the real

data;

2. System control:

Checking the control mechanisms (appropriate

specifications and control parameters),

Solvability of different operating scenarios;

3. Optimal operation:

Software training to find the optimal solution,

while considering the lowest costs or lowest

emission;

4. Error detection:

Implementation from error detection algorithms

to find acute and creeping errors and secure the

system operation.

After this last step the software will be tested in the

real Brühl System. As soon as the tests have been

completed to the satisfaction of all project partners,

the software will be brought to market by LEM

Complex Reference Model

Heating Network Navigator

Optimization parameters:

- start time

- simulation time step

- optimization time step

- end time

Optimization time table:

- temperatures,

- mass flows,

- etc.

Current system values:

- temperatures,

- mass flows,

- etc.

bevor first

optimization time step

SIMULTECH 2019 - 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

228

GmbH. The experiences of the project shall be used

to adapt the software to other district heating supply

systems.

5 CONCLUSIONS

SiL simulations are an important instrument to

develop and test software solutions. The development

of simulation and optimization tools for complex

systems is necessary because these systems can no

longer be calculated manually. In this case TRNSYS

is used to simulate a complex district heating system

with solar thermal plants and a short-term thermal

energy storage (Brühl system).

To warranty the supply safety, it is not possible to

test the software solution Heating Network Navigator

in the real system. This is the reason to combine

simulation and optimization to test the software in

advance. The example shows that TRNSYS as

modular and flexible simulation software is able to

fulfil such complex requests. Especially since own

models can be easily created and implemented.

In the context of this article, the creation of the

CRM and the Heating Network Navigator as well as

the linking of the two in the Software-in-the-Loop test

were presented. In the next step, the software tests can

begin.

ACKNOWLEDGEMENTS

The project underlying this paper is funded by the

German Federal Ministry for Economic Affairs and

Energy under the codes ZF4389101ST7/

ZF4147602ST6 following a decision by the German

parliament. Special thanks also go to the AiF Projekt

GmbH for supporting the project. The sole

responsibility for the content of the report lies with

the authors.

NOMENCLATURE

ANN

artificial neural network

charging

CHP

combined heat and power

CRM

complex reference model

discharging

frost protection

heat maintenance

HTST

heat transfer station

heat exchanger

inlet

out

outlet

prh

preheating

prim

primary

poh

postheating

return line

sec

secondary

SiL

software in the loop

supply line

TES

thermal energy storage





[€]

operating cost

 [kg/s]

mass flow





[kg]

mass of CO

 [°C]

temperature





/s]

flow rate

REFERENCES

SDH - solar district heating: Ranking List of European

Large Scale Solar Heating Plants. https://www.solar-

district-heating.eu/en/plant-database/. checked:

14.05.19

Urbaneck, T.; Oppelt, T.; Platzer, B.; Frey, H.; Uhlig, U.;

Göschel, T.; Zimmermann, D.; Rabe, D.: Solar District

Heating in East Germany – Transformation in a

Cogeneration Dominated City. Energy Procedia, Vol.

70 (2015) pp. 587–594. DOI:

10.1016/j.egypro.2015.02.090

Urbaneck, T.; Oppelt, T.; Shrestha, N. Lal; Platzer, B.;

Göschel T.; Uhlig, U.; Frey, H.: Technische Umsetzung

der solaren Fernwärme Brühl. EuroHeat&Power,

VWEW Energieverlag 46. Jg. (2017) 11 pp. 20-23. –

ISSN 0949-166X

Shrestha, N. Lal; Urbaneck, T.; Oppelt, T.; Platzer, B.;

Göschel T.; Uhlig, U.; Frey, H.: Implementation of

large solar thermal system into district heating network

in Chemnitz (Germany) In: International Solar Energy

Society (Hrsg.): ISES Solar World Conference 2017

and the IEA SHC Solar Heating and Cooling. Freiburg,

2018, pp. 322-332. - ISBN 978-3-9814659-7-6

DOI:10.18086/swc.2017.06.08

Urbaneck, T.; Oppelt, T.; Shrestha, N. Lal; Platzer, B.;

Göschel T.; Uhlig, U.; Frey, H.: Technische Umsetzung

der solaren Fernwärme Brühl. EuroHeat&Power,

VWEW Energieverlag 46. Jg. (2017) 11 pp. 20-23. –

ISSN 0949-166X

Urbaneck, T.; Fürbaß, G.; Stillger, G.: Energetische

Stadtsanierung in Chemnitz – auf dem Weg zur grünen

Fernwärme. In: Klimaschutz & erneuerbare Wärme –

Beispiele, Aktivitäten und Potenziale für die

kommunale Wärmewende. Köln: Deutsches Institut für

Urbanistik (Hrsg.) p. 54-61 2017. – ISBN 978-3-88118-

583-7

Kuboth, S.; Heberle, F.; König-Haagen, A.; Brüggemann,

D.: Economic model predictive control of combined

Software-in-the-Loop-simulation of a District Heating System as Test Environment for a Sophisticated Operating Software

229

thermal and electric residential building energy systems.

Applied Energy, Vol. 240 (2019) p. 372-385,

www.elsevier.com/locate/apenergy

Schweiger, G.; Gomes, C.; Hafner, I.; Engel, G.; Nouidui,

T. S.; Popper, N.: Co-Simulation: Laveraging the

Potential of Urban Energy System Simulation.

EuroHeat&Power English Edition VWEW

Energieverlag, Vol. 15, I-II/2018, pp. 13 - 16

Oppelt, T.; Urbaneck, T.; Platzer, B.; Otto, S.; Heinrich, I.;

Schmidt, A.; Göschel T.; Uhlig, U.: Wärmenetz-

Navigator optimiert den Betrieb von Wärmenetzen.

EuroHeat&Power, VWEW Energieverlag 47. Jg.

(2018) 6 pp. 42-45. – ISSN 0949-166X

Oppelt, T.; Urbaneck, T.; Otto, S.; Heinrich, I.; Schmidt,

A.; Göschel, T.; Uhlig, U.; Frey, H.: Development of a

software system for optimal operation of heating

networks with central solar plant. In: EuroSun 2018:

12th International Conference on Solar Energy and

Buildings. Rapperswil (Schweiz), 2018. – ISBN 978-3

-9820408-0-6 DOI:

https://doi.org/10.18086/eurosun2018.05.05

Shrestha, N. Lal; Urbaneck, T.; Oppelt, T.; Göschel T.;

Uhlig, U.; Frey, H.: Special Storage Management and

System Concept - Large-scale Solar District Heating

System Operates as Expected. EuroHeat&Power,

English Edition VWEW Energieverlag Vol. 15 (2018)

3 pp. 19-27. – ISSN 1613-0200

Solar Energy Laboratory, University of Wisconsin-

Madison: TRNSYS 18 – a Transient System Simulation

program, 2017, http://www.trnsys.com/

SIMULTECH 2019 - 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

230