Modelling and Simulation of the Temperature Control System in the

Heating Installations from Nonresidential Buildings

Daniel Popescu

and Ioan Borza

Department of Electrical Engineering in Civil Engineering and Building Services,

Technical University of Civil Engineering, Bd. Pache Protopopescu 66, Bucharest, Romania

Department of Civil Engineering and Building Services, Politehnica University,

Str. Traian Lalescu No. 2, Timisoara, Romania

Keywords: Temperature Control, Nonlinear Control Systems, Modelling, Simulation, Building Automation,

Civil Engineering.

Abstract: The article addresses specific issues of the automated heating systems for non-residential buildings, which

aim to ensure thermal comfort with low energy consumption. The specialized automatic system maintains

constant the indoor temperature when the heat input in building equals the heat loss through the building

envelope. The specialized automatic system consists of several subsystems. The model for each subsystem is

obtained considering the particularities of the heating processes from buildings and requirements for the

thermal comfort. By simulating the operation of the specialized automatic system is obtained the time

behavior for the main physical values that characterizes the system, relevant to the quality of the heating

temperature control in the building. The operation of the automatic controller and the control valve are

analyzed by simulation, in a comparable time interval with transient regime of the automatic heating system

of the real building. The validation of the model is done by comparing the results obtained by simulation with

results of experimental measurements in the real automatic system, implemented in the building chosen for

study.

1 ENSURING THE THERMAL

COMFORT IN

NONRESIDENTIAL BUILDINGS

The automation of heating systems in buildings can

be made differently from one building to another,

depending on the size of the building, the thermal

comfort imposed, the rooms destination in the

building, the number of persons in the building, the

heat source used, the building materials used, etc.

(Popescu and Ciufudean, 2012; Popescu, 2004;

Clements-Croome, 1996; Castilia et al., 2014;

Arguello and Velez, 2002; Balan, Stan and Lapusan,

2009; Balan et al., 2009; Chmielnicki, 2011; Liao and

Dexter, 2004; Ma et al., 2011; Kim and Ahn, 2013).

In an individual dwelling are easly to impose the

requirements for indoor thermal comfort: is chosen a

room "witness" (reference) for imposed thermal

comfort and, into the room, is placed the transducer

that measure the indoor temperature adjusted

(Popescu, 2014; Castilia et al., 2014). Choosing a

room as being the reference for indoor thermal

comfort is not recommended for non-residential

buildings because: the number of building occupants

is high and the thermal comfort exigencies differ from

one person to another, even if performing the same

task (Clements-Croome, 2011; Wagner and Schakib,

2011); also, heated spaces in the building may have

different destinations and a good labor productivity

impose adequate thermal comfort for the activity

carried (Oancea and Caluianu, 2012; Clements-

Croome and Li, 2000; Seppanen et al., 2006;

Clements-Croome, 2006; Wargocki, 2006).

Heating systems in non-residential buildings have a

heat source and contain multiple independent thermal-

hydraulic circuits, in which the water temperature is

adjusted to the corresponding values. The desired water

temperature in a heating circuit is established using the

selected heating curve for that circuit (Mira et al., 2010;

Ilina et al., 2010); flow temperature changes correlated

with outdoor temperature values.

Ensuring the thermal comfort in a zone of building

that is heated with an own heating circuit, depends on

the correct choice of heating curve for that zone. The

graph must lead to a heat input in building that is

454

Popescu, D. and Borza, I.

Modelling and Simulation of the Temperature Control System in the Heating Installations from Nonresidential Buildings.

In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2016), pages 454-461

ISBN: 978-989-758-184-7

Figure 1: Model of the automatic system that adjusts the water temperature in a heating circuit.

able to compensate the heat loss through the building

envelope in the heated zone; indoor temperature in

the building is maintained constant.

Heating automation in a non-residential building

involves:

- an automated system that adjusts the temperature of the

heat source (boiler) to a constant value, usually 80

- distinct automatic systems that independently adjust

the temperature of the water in each heating circuit.

2 MODELLING OF THE

AUTOMATIC SYSTEM FOR

ADJUSTING THE WATER

TEMPERATURE IN A HEATING

CIRCUIT

The model of the automatic system was developed in

Simulink from Matlab and is composed of several

subsystems, interconnected as shown in Figure 1.

Automatic adjustment of water temperature in the

heating circuit of the building is done using a

combined control loop, i.e. a control that supervises

the value of deviation (error), simultaneously with a

control that supervises the dominant disturbance.

Heating curve of the building establishes the required

flow temperature in the heating circuit; the flow

temperature increases (decreases) at the decrease

(increase) of the outdoor temperature, which

represents the dominant disturbance. Heat input in the

building is automatically adjusted and, therefore, the

indoor temperature is maintained constant.

3 MODEL OF THE HEATING

SYSTEM

The building chosen for modeling the automatic

system for temperature control of the thermal agent in

the heating installation, belongs to the Faculty of

Building Services Engineering from Bucharest. In

this building were conducted experimental research,

which had the purpose of ensuring the thermal

comfort by automatically controlling the quantity of

heat that is lost through building envelope (Popescu,

2008; Popescu and Ciufudean, 2008; Popescu,

Ciufudean and Ionescu, 2009; Popescu and

Ciufudean, 2012). One of the three independent

heating circuits with which it is equipped the building

was experimentally identified (Popescu, Ciufudean

and Ghiaus, 2009) and the transfer function of the

heating installation for this circuit is

1s6,53

e586,0

)s(H

s7,19

⋅

−

(1)

The dead time

7,19=

and the inertial time

constant

6,53=

are expressed in minutes.

The HEATING SYSTEM model, in Simulink, is

shown in Figure 2.

Figure 2: Model of the HEATING SYSTEM.

4 MODEL OF THE OUTDOOR

TEMPERATURE SUBSYSTEM

OUTDOOR TEMPERATURE subsystem generates

outdoor temperature values (dominant disturbance),

which changes similar to the outdoor temperature.

The subsystem is designed to provide a sinusoidal

signal with a period of 24 hours. Sinusoidal signal is

centered on an average outdoor temperature of -10

Modelling and Simulation of the Temperature Control System in the Heating Installations from Nonresidential Buildings

455

and the outdoor temperature extremes variations in 24

hours range between 0

C (day) and -20

C (night).

Values for the outdoor temperature have been chosen

particularly lower, similar to those actually recorded

in Romania at the beginning of the year 2015,

temperatures that pose particular problems in

maintaining thermal comfort in the building.

OUTDOOR TEMPERATURE model is shown in

Figure 3.

Figure 3: Model of the OUTDOOR TEMPERATURE.

5 MODEL OF THE HEATING

CURVE SUBSYSTEM

HEATING CURVE subsystem generates the flow

temperature setpoint in the heating circuit of the

building. Water temperature dependence on the

outdoor temperature is set by heating curve, which is

a line with a slope of 1.5. Slope value was chosen

adequate for the studied zone in the heated building.

Automation equipments used for heating

buildings allow choosing the slope of the heating

curve within the range 0.5 ... 4.0, as shown in Figure

4. Heating curves are taken from the technical

documentation of automation equipments and the

temperatures are given in Celsius degrees.

Temperatures in the HEATING CURVE

subsystem are expressed in Kelvin degrees.

The heating curve used in model was designed

based on the heating curve, in Celsius degrees, with a

slope of 1.5, from the set of heating curves shown in

the Figure 4. The ranges of temperatures are equal,

regardless of unit Kelvin or Celsius chosen for

temperatures, so we can write

)K(T)C(

Δ=θΔ

(2)

Therefore, the variation of flow temperature in the

heating installation is

0000

( ) 80 20 60

CCCC

Δ=−=

(

() 60

TK KΔ=

)

and the outdoor temperature variation

0000

( ) 20 20 40

CCCC

Δ=−−=−

(

() 40

TK KΔ=−

)

Figure 4: Heating curves for a three-way mixing valve.

Figure 5: Heating curve used in the model.

The heating curve used in the model is the straight

segment noted AC (figure 5), which has the general

equation

y +⋅=

(3)

With the values written on the graph axes is

calculated the slope

5,1

)(

−=

−

Using the resemblance of triangles ABC and ADE,

we can write

353,15 293,15 293,15 253,15

293,15 293,15 0

KK KK

nK KK

−−

, from

where shall be determined the value

Kn 87,732=

Heating curve has the equation

[ ] 1, 5 [ ] 732,87

ft ot

TK TK K=− ⋅ +

(4)

Equation (4) represents the basis for HEATING

CURVE subsystem from Figure 6.

(K)

353,15

293

293,15

253,15

MoMa-GreenSys 2016 - Special Session on Modelling Practical Paradigms of Green Manufacturing Systems

456

Figure 6: Model of the HEATING CURVE.

Choosing a heating curve with slope value greater

than 1.5 will lead to overheating of the building; a

value of the slope less than 1.5 will lead to insufficient

heating of the building.

If the outdoor temperature reaches extreme

values, -20...-30

C, the set temperature at the boiler

must be fixed at values higher than 80

C, in order to

not negatively affect the indoor temperature in the

building. Practical experience in the heating of

buildings has shown that a set temperature at the

boiler higher than 80

C is rarely needed and for small

time intervals. The boiler automation equipment

allows to establish the working temperature at

maximum 95

6 MODEL OF THE NONLINEAR

REGULATOR SUBSYSTEM

NONLINEAR REGULATOR subsystem is a three-

point regulator to which the switching thresholds and

the dead zone were established in the static

characteristic of the regulator. The model of the

regulator was realised by authors and this regulator

ensures a good precision in operation.

This type of nonlinear regulators can be

successfully used for the automation of the heating

installations, due to the high thermal inertia for

buildings (Arguello and Velez, 2002).

7 MODEL OF THE THREE-WAY

MIXING VALVE SUBSYSTEM

The boiler has its own automatic control loop that

maintains the temperature of boiler at the constant

value 80

The three-way mixing valve send the thermal

agent in the heating installation at a temperature

obtained by mixing the thermal agent taken over from

the boiler with the thermal agent taken over from the

return of the heating installation. The angular position

of the three-way mixing valve is variable between -

and +45

. The temperature of the thermal agent at

the output of the control valve is comprised between

the temperature in the heating installation return

(minimum value for the angular position -45

) and the

boiler temperature (maximum value for the angular

position +45

). Temperature regulated with mixing

valve depends linearly on the angular position of the

valve; for angular position 0 degrees, the valve takes

over thermal agent in equal proportions from the

boiler and from the heating installation return.

Model of three-way control valve was realised by

authors in Simulink.

8 SIMULATION OF THE

AUTOMATIC CONTROL

SYSTEM

The simulation was performed during 50 hours

(180,000 seconds), which is relevant for thermal

comfort in the building studied. The results obtained

by simulation are shown graphically in Figure 7.

The first graph is for the outdoor temperature. The

evolutions in time for the next graphs must be

analyzed in correlation with the graph for the outdoor

temperature.

Flow temperature values imposed for the heating

installation (ranging between 50

C and 80

C) are in

accordance with the values of the outside temperature

(ranging between 0

C şi -20

C) and with the heating

curve with slope 1,5.

The values of angular position for three-way

control valve indicate a greater amount for thermal

agent taken from the boiler, compared to the amount

of thermal agent taken from the heating return. For

the angular position of 40

, the flow temperature

reaches 77 ... 78

C; for the angular position of 45

, the

flow temperature should reach a maximum value of

C. The error comes from the nonlinear regulator.

The temperature in the heating installation return

varies due to the changes of the flow temperature and

through the exchange of heat between the installation

and building. The difference between flow

temperature and return temperature of the heating

installation is maintained approximately in the range

20 ... 30

C, which indicates that the installation heats

efficiently the building (Ilina et al., 2010).

Modelling and Simulation of the Temperature Control System in the Heating Installations from Nonresidential Buildings

457

Figure 7: Results obtained by simulation of the automatic control system.

Correct operation of the automatic regulator and

the control valve can be evaluated using the graphs

from Figure 8, during the transitional regime.

The 300 seconds simulation time is relevant to

analyze the transitory regime of the automatic heating

system used in non-residential buildings.

The error adjusting decreases to the value 2,5K,

which is very good if we take into account that relates

to temperature in heating installation and not to the

indoor temperature of the building.

The regulator commands, for adjusting the

angular position of the control valve during the

transitory regime, are generated at time intervals from

10 to 100 seconds. These values are large enough to

find that the actuator of the control valve is not

overloaded by repeated orders during transitory

regimes. Furthermore, in the operation of the heating

installation of a building, transitory regimes follow

each other at intervals of tens of minutes or even

larger, usually when the outdoor temperature

changes.

9 VALIDATION OF THE MODEL

FOR AUTOMATIC CONTROL

SYSTEM

Faculty of Building Services Engineering from

Bucharest is the non-residential building equipped

MoMa-GreenSys 2016 - Special Session on Modelling Practical Paradigms of Green Manufacturing Systems

458

Figure 8: Results obtained by simulation automatic control system in transitional regime.

with automatic heating system which formed the

basics for the model presented this article. It was

monitored the operation of the automatic heating

system of the building during two days, in the first

part of January from 2015, when outdoor

temperatures were extremely lower. Were measured

and were recorded hourly the values for outdoor

temperature, indoor temperature in the building and

flow temperature in the heating installation. The

graphs for the three temperatures are plotted in the

Figure 9.

Outdoor temperature variation experimentally

measured is approximately sinusoidal; the deviation

from sinusoidal form in the model is due to the

particular weather conditions existing in Bucharest in

period chosen for experimental measurements.

Experimentally measured flow temperature on the

heating installation has evolved over time by

following outdoor temperature values, according to

the heating curve with slope 1.5, selected in the

control cabinet of the boiler.

The experimental measurements have also

included indoor temperature in an office of the

building. Indoor temperature variations were between

18,1

C and the 19,9

C; these values are acceptable for

activities in an office of the building in cold winter

days.

Figure 9: Graphs for experimentally measured

temperatures.

The comparative analysis of values and graphs for

-40.00

-20.00

0.00

20.00

40.00

60.00

80.00

100.00

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

Outdoor temperature

Indoor temperature

Flow temperature

[hours]

[Celsius]

Modelling and Simulation of the Temperature Control System in the Heating Installations from Nonresidential Buildings

459

significant temperatures, obtained by simulation and

experimental measurements in the building, show that

the model of automatic system was done correctly

and accurately.

10 CONCLUSIONS

The finite duration of the transitory regime show the

stability of the automatic system modeled and a large

reserve of stability.

The accuracies for temperature control of the

thermal agent have close values in the case of the

simulation and the case of the operating for real

system in building.

The nonlinear regulator and the three-way mixing

valve are suited for the purpose.

There are no overloads for the three-way mixing

valve caused by the transitory regimes of the

automatic system.

The change of the angular position during

operation at the three-way mixing valve takes place

within the domain of variation thereof, from -45

+45

. Consequently, are not producing saturations of

the regulator commands which would reduce the

adjusting performances.

Slope value for heating curve must be adapted to

the particularities from the building heated zone.

The model for the automatic system can be used

as an auxiliary tool in design of automatic heating

systems for non-residential buildings; it is necessary

to know prior the mathematical model of the heating

process.

The model of the automatic heating system is

validated by comparing the significant temperatures

obtained by simulation and experimental

measurements in the studied building.

The article presents how the temperature of the

thermal agent is controlled in the heating installation

from a non-residential building. Thermal comfort

depends on the indoor temperature of the building,

which in turn depends on the temperature of the

thermal agent in the heating system. Adding a

subsystem called the heated space to the automatic

system model, provides a better solution to ensure the

thermal comfort inside the building.

REFERENCES

Arguello-Serrano, B., Velez-Reyes, M., 2002. Nonlinear

control of a heating, ventilating, and air conditioning

system with thermal load estimation”. Control Systems

Technology, IEEE Transactions 7(1).

Balan, R., Stan, S.D., Lapusan, C., 2009. A Model Based

Predictive Control Algorithm for Building Temperature

Control. IEEE International Conference on Digital

Ecosystems and Technologies: 541-546.

Balan, R., Hancu, O., Stan, S., Lapusan, C., Donca, R.,

2009. Application of a Model Based Predictive Control

Algorithm for Building Temperature Control. Book

Series: Energy and Environmental Engineering Series:

97-101.

Castilia, M.M., Alvarez, J.D., Rodriguez, F., 2004.

Berenguel, M., Comfort Control in Buildings. Springer,

ISBN 978-1-4471-6347-3 (e-book).

Castilia, M.M., Alvarez, J.D., Rodriguez, F., Berenguel,

M., 2014. Comfort Control in Buildings. Springer,

ISBN 978-1-4471-6347-3 (e-book).

Chmielnicki, W.J., 2011. Impact of the indoor temperature

control algorithm in the building on the consumption of

the heat. Rynek Energii 6: 66-73.

Clements-Croome, D.J., 1996. Freshness, ventilation and

temperature in offices. BSERT, 17 (11), 21-27.

Clements-Croome, D.J., 2011. The interaction between the

physical environment and people. In: S.A. Abdul-

Wahab, ed. Sick building syndrome in public buildings

and workplaces. Berlin Heidelberg: Springer-Verlag,

239-261.

Clements-Croome, D.J., Li, B., 2000. Productivity and

Indoor Environment, BSERT, 1, pp. 629-634.

Clements-Croome, D.J., Editor, 2006. Creating the

productive workplace. Second Edition, 468 pages,

ISBN 13: 978-0-415-35138-6, Taylor & Francis,

London and New York.

Ilina, M. (coordinator), 2010. Technical Encyclopedia of

Installations, vol. I, ISBN 978-973-85936-5-7,

Publishing House Artecno Bucharest.

Kim, B.-Y., Ahn, H.-S., 2013. Coordination and control for

building automation systems, International Conference

on Control, Automation and Systems, Pages 614-616.

Liao, Z., Dexter, A.L., 2004. A simplified physical model

for estimating the average air temperature in multi-zone

heating systems. Building and Environment, 39(9):

1013-1022.

Ma, Y.D., Anderson, G., Borrelli, F., 2011. A Distributed

Predictive Control Approach to Building Temperature

Regulation. Proceedings of the American Control

Conference.

Mira, N. (coordinator), 2010. Technical Encyclopedia of

Installations, vol. E, ISBN 978-973-85936-5-7,

Publishing House Artecno Bucharest.

Oancea, C., Caluianu, S., 2012. Analysis of non-residential

buildings in Romania from the labour productivity and

intelligent buildings concept point of view. Intelligent

Buildings International, Volume 4, Issue 4, pages 216-

227, Publisher Taylor & Francis Ltd., ISSN 1750-8975.

Popescu D., 2004. Régulation d’un système de chauffage

des bâtiments. Proceedings of the 7th International

Conference on Development and Application Systems.

pp. 6-9, ISBN 973-666-106-7.

Popescu, D., 2014. Specific problems on the operation of

the automatic control system of temperature into an

MoMa-GreenSys 2016 - Special Session on Modelling Practical Paradigms of Green Manufacturing Systems

460

individual dwelling. WSEAS Transactions on Systems,

Volume 13, 2014, pp. 482-491. E-ISSN: 2224-2678.

Popescu, D., 2008. A New Solution for Automatic Control

of Heating Systems in Buildings Based on Measuring

Heat Transfer Through Outer Surfaces. Proceedings of

the 10th WSEAS International Conference on

Automatic Control, Modeling and Simulation, pp. 206-

209, ISSN 1790-5117.

Popescu, D., Ciufudean, C., 2012. Indoor thermal comfort

by controlling heat transfer through building envelope

The 13th International Conference on Automation &

Information, pp. 150-155, ISBN 978-1-61804-099-2.

Popescu, D., Ciufudean, C., 2008. Automatic Control

System for Heating Systems in Buildings Based on

Measuring the Heat Exchange through Outer Surfaces.

Proceedings of the 8th WSEAS International

Conference on Simulation, Modelling and

Optimization, pp. 117-121, ISSN 1790-2769.

Popescu, D., Ciufudean, C., 2012. Indoor thermal comfort

by controlling heat transfer through building envelope.

The 13th International Conference on Automation &

Information, pp. 150-155, ISBN 978-1-61804-099-2.

Popescu, D., Ciufudean, C., Ionescu, D., 2009.

Experimental Analysis of the Automated System for

Heating Control based on Heat Losses through

Building’s Envelope. 9th WSEAS International

Conference on Simulation, Modelling and

Optimization. pp. 160 – 166, ISSN 1790-2769.

Popescu, D., Ciufudean, C., Ghiauş, A., 2009. Specific

Aspects of Design of the Automated System for

Heating Control that Accounts for Heat Losses Through

the Building’s Envelope. Proceedings of the 13th

WSEAS International Conference on Systems. pp. 352

– 356, ISSN 1790-2768.

Seppanen, O., Fisk, W.J., and Lei, Q.H., 2006. Room

temperature and productivity in office work. Berkeley:

Lawrence Berkeley National Laboratory. Available

http://escholarship.org/uc/item/9bw3n707.

Wagner A. and Schakib-Ekbatan K., 2011. User

satisfaction as a measure of workplace quality. Detail

Work Environments, Edited by Christian Schittlich, 54-

57.

Wargocki, P., Seppanen, O., Andersson, J., Boerstra, A.,

Clements-Croome, D., Fitzner, K., Hanssen, S.O.,

2006. Indoor Climate and Productivity in Offices.

REHVA Guidebook no 6. ISBN 2-9600468-5-4.

Modelling and Simulation of the Temperature Control System in the Heating Installations from Nonresidential Buildings

461