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In this paper, dynamic simulation was used to compare the energy performance of three innovative HVAC systems: (A) mechanical ventilation with heat recovery (MVHR) and micro heat pump, (B) exhaust ventilation with exhaust air-to-water heat pump and ventilation radiators, and (C) exhaust ventilation with air-to-water heat pump and ventilation radiators, to a reference system: (D) exhaust ventilation with air-to-water heat pump and panel radiators. System A was modelled in MATLAB Simulink and systems B and C in TRNSYS 17. The reference system was modelled in both tools, for comparison between the two. All systems were tested with a model of a renovated single family house for varying U-values, climates, infiltration and ventilation rates. It was found that A was the best system for lower heating demand, while for higher heating demand system B would be preferable. System C was better than the reference system, but not as good as A or B. The difference in energy consumption of the reference system was less than 2 kWh/(m2 a) between Simulink and TRNSYS. This could be explained by the different ways of handling solar gains, but also by the fact that the TRNSYS systems supplied slightly more than the ideal heating demand.
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Energy performance comparison of three innovative HVAC
systems for renovation through dynamic simulation
Marcus Gustafsson1, 5, Georgios Dermentzis2, Jonn Are Myhren3, Chris Bales4, Fabian Ochs2, Sture Holmberg5,
Wolfgang Feist2, 6
1, 4Energy and Environmental Technology, 3Building technology, Högskolan Dalarna, 791 88 Falun, Sweden
2Unit for Energy Efficient Buildings, University of Innsbruck, Technikerstraße 13, A-6020 Innsbruck, Austria
5Fluid and Climate Technology, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology,
School of Architecture and the Built Environment, Brinellvägen 23, 100 44 Stockholm, Sweden
6Passive House Institute Rheinstr. 44/46, D-64283 Darmstadt, Germany
Abstract
In this paper, dynamic simulation was used to compare the energy performance of three
innovative HVAC systems: A) mechanical ventilation with heat recovery (MVHR) and micro
heat pump, B) exhaust ventilation with exhaust air-to-water heat pump and ventilation
radiators, and C) exhaust ventilation with air-to-water heat pump and ventilation radiators,
to a reference system: D) exhaust ventilation with air-to-water heat pump and panel
radiators. System A was modelled in MATLAB Simulink and systems B and C in TRNSYS 17.
The reference system was modelled in both tools, for comparison between the two. All systems
were tested with a model of a renovated single family house for varying U-values, climates,
infiltration and ventilation rates.
It was found that A was the best system for lower heating demand, while for higher heating
demand system B would be preferable. System C was better than the reference system, but not
as good as A or B.
The difference in energy consumption of the reference system was less than 2 kWh/( a)
between Simulink and TRNSYS. This could be explained by the different ways of handling
solar gains, but also by the fact that the TRNSYS systems supplied slightly more than the ideal
heating demand.
Keywords: Energy performance, Dynamic simulation, HVAC, Micro heat pump, Ventilation
radiator, TRNSYS, MATLAB Simulink, Renovation
1Corresponding author. Tel.: +46 23778563. E-mail address: mgu@du.se.
Nomenclature
COP coefficient of performance
HD annual heating demand of building (kWh/(m2·a))
HP heat pump
HVAC heating, ventilation and air conditioning
MVHR mechanical ventilation with heat recovery
U heat transfer coefficient for building parts (W/(m2K))
Greek letters
η air change rate (h-1)
Subscripts
inf infiltration
vent ventilation
1. Introduction
About 40 % of the total energy use in the EU-27 is accounted for by the building sector. Thus,
the building stock plays an important part in the work towards the international goals of lower
energy use [1]. 2/3 of the energy used in households in the EU-15 goes to space heating [2],
and the largest potential for saving energy in this sector lies in renovation and upgrading of
old buildings to modern energy standards [3]. Such renovation measures include changing
windows, insulating roofs and external walls and changing HVAC systems. The latter of these
was the objective of this study.
Many studies have previously been conducted within the field of HVAC systems and
energy use of buildings, both residential and commercial buildings. Bojić et. al [4] compared
three HVAC systems for heating and cooling of an office building. Wang et al. [5] made a
comparison of three HVAC systems for a hypothetical apartment building. The study included
17 climate zones with various temperature and humidity conditions, and the systems
compared were a direct expansion split system, a split air-source heat pump system and a
closed-loop water-source heat pump with boiler an evaporative fluid cooler.
A study carried out by Gustafsson et al. [6], treating two HVAC systems similar to systems
A and B of this study, indicated that these systems may indeed be potential alternatives to
other, more established, systems. The results of this and the study by Wang et al. [5] also
confirm the necessity to vary the climatic conditions when comparing HVAC systems.
A complete building retrofit includes many more steps and aspects than those covered in
this study. Ma et al. [7] proposes a systemic approach, going all the way from planning to
post-evaluation. The present study focuses on the choice of HVAC systems after a renovation
of the building envelope.
There is a wide range of tools for simulation of building energy performance. In a study by
Ochs et al. [8], the simulation tools MATLAB Simulink [9] and TRNSYS 17 [10] are used to
model a renovated multi-family house. According to this study, there are major differences
between the tools regarding the modelling of walls, zone nodes, windows and shading, and
the time step of the solver (fixed in TRNSYS, adaptive in MATLAB Simulink). However, the
study also shows good agreement in results between the two tools.
In this study, the energy performance of three innovative heating and ventilation systems
was investigated through dynamic simulation and set in relation to a reference system, based
on a common air-to-water heat pump. The choice of systems A, B and C was based on their
potential suitability for building renovation and on the need to fill a gap in the research, while
D is an established type of system, thus suitable as reference. All of the tested systems were
implemented in a model of a generic single family house and tested for two renovation levels
in seven different climates.
The second objective of this study was to contribute to the comparison of different
simulation tools. The reference system was modelled in both MATLAB Simulink and
TRNSYS 17, to enable detection of systematic differences.
2. Methodology
2.1. Building model and boundary conditions
The building modelled in this study is a semi-detached single family house, with a tempered
floor area of 78 and a volume of the tempered zone of 187 m³. It was defined within the
FP7 project iNSPiRe [11] as a typical European single family house construction. The actual
building is located in London, UK, and consists of two floors and an unheated attic, with an
insulated ceiling between the top floor and the attic. In the model, the attic was excluded, and
the ceiling of the top floor was taken to be the upper limit of the building envelope. Solar
gains of the roof were thus disregarded and the ceiling was assumed to exchange heat directly
to the ambient air. The western wall, adjacent to the neighboring house, was taken to be
adiabatic. The whole tempered area was modelled as one zone, with stairs and intermediate
floor as internal walls. Simulations in TRNSYS 17 comparing the single zone model to a
model with one zone per floor and one zone for the attic showed a difference in heating
demand and heat load of less than 3 % for the climate of London.
For open window ventilation and shading, the boundary conditions used in this study were
the same as those used within [11], and to a large extent also within IEA SHC Task 44 [12].
Internal gains from occupants and electrical equipment were based on the same schedule as in
[11] and [12], but since the living area for the building used in this study was only 78 m2,
compared to 140 m2 in [12], the number of occupants was reduced from four to two and the
gains from electrical equipment and lighting were scaled down by 50 %. The ventilation rate
was taken to be 0.4 h-1 and the infiltration rate was calculated from a simplified model of the
building envelope to be 0.1 h-1. For two of the studied climates, the influence of air change
rates on the HVAC systems was tested. The infiltration rate was increased by steps of 0.1 to
0.2 and 0.3 h-1. The ventilation rate was both decreased and increased by the same amount to
0.3 h-1 to 0.5 h-1. While varying one these parameters, the other one was kept at its default
value.
The desired indoor temperature, which was used to control the heating systems, was set to
20 °C. Transmission losses to the ground were modelled by setting the disturbed ground
temperature as boundary temperature for the ground floor. The disturbed ground temperature
was approximated as a sine, which was calculated according to standard ISO 13370 [13].
Beside ventilation and infiltration rates, the sensitivity analysis comprised climatic
conditions and heating demand. Climate data for seven different European locations were
used, as listed in Table 1. The chosen locations, the same as used in [11], represent
continental and coastal climates as well as a range of average ambient temperature and
relative humidity. Data files from Meteonorm [14], based on long-term measurements, were
used to generate weather data for the simulations.
For each climate, two renovation levels were defined. EnerPHit standard (HD25) [15] and
Passive House standard (HD15) [16] were used to define houses with heating demands of 25
kWh/(m²·a) and 15 kWh/(m²·a), respectively, assuming an air MVHR efficiency of 85 % and
disregarding cooling demand. For the tested systems which did not include MVHR, the actual
heating demand was higher. The difference in heating demand with or without MVHR was
larger for the colder climates, where the MVHR has a larger impact. Insulation thicknesses
and related U-values were calculated using the passive house calculation tool PHPP [17]. The
applied U-values for each climate and renovation level are listed in Table 1.
Table 1 - Locations for climatic data and corresponding U-values used in simulations.
U-values [W/m² K]
HD25
HD15
Both
Location
Walls
Floor
Roof
Walls
Floor
Roof
Windows
Doors
Stockholm
0.126
0.128
0.126
0.057
0.057
0.057
0.90
0.80
Gdansk
0.150
0.153
0.150
0.074
0.075
0.075
0.90
0.80
Stuttgart
0.235
0.244
0.237
0.143
0.146
0.144
0.90
0.80
London
0.277
0.290
0.279
0.175
0.180
0.176
0.90
0.80
Lyon
0.320
0.337
0.323
0.198
0.204
0.199
0.90
0.80
Madrid
0.500
0.544
0.509
0.361
0.383
0.365
0.90
0.80
Rome
0.621
0.689
0.634
0.456
0.492
0.463
0.90
0.80
2.2. Investigated systems
All of the tested systems were set to provide space heating and ventilation, while domestic hot
water use was left out of the study. The cooling demand was evaluated by measuring the
number of hours with indoor temperature above 26 °C. The comparison of the systems did not
include an economic analysis, and practical details on installation were not considered. Total
energy consumption included heat pump compressor, auxiliary heater, pump for the space
heating circuit and ventilation fans. All energy consumed was thus electricity.
The layouts of the investigated HVAC systems are described in Figure 1.
Figure 1 - Schematic layout of studied HVAC systems: A) ventilation with heat recovery (MVHR), micro heat pump and
electric radiators, B) exhaust ventilation with exhaust air-to-water heat pump and ventilation radiators, C) exhaust ventilation
with air-to-water heat pump and ventilation radiators, D) exhaust ventilation with air-to-water heat pump and panel radiators.
2.2.1 System A
System A is based on a micro heat pump, in combination with mechanical ventilation with
heat recovery (MVHR), with electric radiators as backup for peak heat loads. The heat pump
uses the exhaust air of the heat recovery unit as source and provides heat to the supply air of
the ventilation system. Thus, one compact unit can be used for combined ventilation and
heating or cooling (reverse operation for cooling). Fresh outdoor air flows into the MVHR
unit, where it is heated with a recovery efficiency of up to 95 %. It is then further heated by
the micro heat pump up to maximum 52 °C, as higher temperatures may cause odor problems,
to supply space heating.
In comparison to an air source heat pump, the evaporator uses the benefit of slightly higher
source side temperature and of latent heat. The evaporator extracts heat from the air using the
latent heat of condensation, and the higher source side temperature improves the coefficient of
performance (COP) of the heat pump. However, the air volume flow rate in the evaporator,
which is equal to the flow rate in the condenser, is limited to the hygienic flow rate (too high
flow rate leads to dry indoor air). Thus, the source power is limited. The heating capacity of
the micro heat pump is in the range of 1 kW. Therefore, this system can only be implemented
in flats or small houses with very low energy demand such as Passive Houses. The advantages
of the micro heat pump are the compactness, giving the possibility of integration into the
façade, and cost reduction [18].
In order to model system A in MATLAB Simulink, the EFKOS model [19] was used. The
EFKOS model was originally developed for air-to-water heat pumps, but the micro heat pump
is an exhaust air-to-air heat pump. Therefore, the input data for the model were chosen so that
the output data would fit to the heating test points of Passive House Component Certificate of
the compact unit Aerosmart m Drexel & Weiss [20]. A mean volume flow rate of 160 m3/h
was taken for the measured test points of the certificate. In the studied building with a default
ventilation rate of 0.4 h-1 and a volume of 187 m3, the volume flow rate is 74.8 m3/h. To adapt
to this, the heating capacity was scaled down while keeping the ratio of heating capacity and
volume flow rate constant, assuming the COP to be independent of the volume flow rate.
Table 2 shows nominal performance data for the micro heat pump for inlet air temperatures to
the heat recovery unit, calculated for 78 % heat recovery efficiency.
Table 2 - Rated performance of micro heat pump for inlet air temperatures to the heat recovery unit.
Air temperature [°C]
-2
2
7
Heating
output [kW]
1.03
1.18
1.34
COP [-]
2.22
2.73
3.07
2.2.2 System B
In system B, the mechanical exhaust ventilation provides an air-to-water heat pump with air
from the living zone, while at the same time creating the low pressure needed to drive the air
flow through the ventilation radiators into the building. The heat pump extracts heat from the
air and delivers heated water to the radiators. The number of ventilation radiators was chosen
based on the desired ventilation rate and the ideal air flow and pressure drop for one
ventilation radiator [21]. The radiators were then sized to cover the heat load of the building at
a distribution and return temperatures of 35/30 °C. The heat pump model was based on
performance data for an existing air-to-water heat pump for exhaust air, as presented in Table
3 [22]. The same heating capacity, plus an auxiliary heater of 1.5 kW, was used for all
locations and renovation levels. The water flow rate was held constant at the nominal level
according to test standards [23].
Table 3 - Rated performance of the exhaust air-to-water heat pump of system B.
Water
temperature
[°C]
Air flow rate [l/s]
30
40
50
60
70
Heating
output [kW]
35
1.14
1.30
1.42
1.46
1.50
45
1.15
1.24
1.30
1.35
1.37
COP [-]
35
4.46
4.76
5.12
5.24
5.43
45
3.34
3.49
3.72
3.86
3.91
In the ventilation radiators, outdoor air flows in through a duct in the wall and is heated by the
radiator panels before entering the room. The heat output of a radiator, either of traditional or
ventilation type, is proportional to the mean temperature difference between the radiator
surface and the air in contact with the heated radiator surfaces. Because of the lower
surrounding air temperature of a ventilation radiator, it can work with a lower supply water
temperature than a traditional radiator. The direct contact with outdoor air gives the system
the quality of fast thermal response, as the heat output is automatically adjusted with any
change of ambient air temperature. Ventilation radiators have also been proven to perform
well in terms of thermal comfort, giving a stable and uniform indoor climate [24], and the low
water temperature is beneficial for the performance of the heat pump. From a renovation
perspective, ventilation radiators in combination with mechanical exhaust ventilation can be a
competitive solution, given that there is already a water heating system in the house.
2.2.3 System C
System C has the same configuration as system B, but with a regular air-to-water heat pump
without heat recovery from exhaust air. The heat pump model was based on manufacturer
performance data for an existing air-to-water heat pump, as presented in Table 4, with a
nominal capacity of 3 kW and a nominal COP of 3.27 at A2/W35 [25].
Table 4 - Rated performance of the air-to-water heat pump of systems C and D.
Water
temperature
[°C]
Air temperature [°C]
-15
-7
2
7
10
12
20
30
Heating
output [kW]
35
1.70
2.60
3.00*
4.50
4.60
4.80
5.00
5.50
45
1.50
2.30
2.80
4.00
4.20
4.40
4.60
5.00
55
1.30
2.00
2.70
3.70
3.80
4.00
4.30
4.70
COP [-]
35
1.90
2.85
3.27**
4.64
4.83
5.00
5.27
5.70
45
1.60
2.20
2.65
3.55
3.67
3.75
4.04
4.41
55
1.16
1.70
2.12
2.74
2.87
3.10
3.30
3.45
* = nominal heating output; ** = nominal COP.
Assuming the COP to be independent of size, the nominal heating capacity was scaled down to
cover the average heat load over 24 hours during the whole year. The nominal water flow rate,
as given by test standards [23], was scaled accordingly, to allow using the same performance
data. An auxiliary heater of 1 kW was employed when necessary. In Table 5, the nominal
capacity and flow rate for each location and renovation level are listed.
Table 5 - Nominal capacity and flow rate of down scaled air-to-water heat pump.
HP capacity [kW]
HP water flow rate [kg/s]
Location
HD25
HD15
HD25
HD15
Stockholm
1.90
1.70
0.121
0.108
Gdansk
1.70
1.50
0.108
0.095
Stuttgart
1.90
1.60
0.121
0.102
London
1.60
1.40
0.102
0.089
Lyon
1.70
1.40
0.108
0.089
Madrid
1.90
1.60
0.121
0.102
Rome
1.70
1.40
0.108
0.089
For the sensitivity analysis on ventilation and infiltration, the heat pump was sized to fit the
new loads, as shown in Table 6.
Table 6 - Nominal capacity and water flow rate of heat pump for varying ventilation and infiltration rates.
Location
Parametric
variation
HP capacity [kW]
HP water flow rate [kg/s]
HD25
HD15
HD25
HD15
Stockholm
ηvent = 0.3
1.70
1.40
0.108
0.089
ηvent = 0.5
2.20
1.90
0.140
0.121
ηinf = 0.2
2.20
1.90
0.140
0.121
ηinf = 0.3
2.40
2.10
0.153
0.134
Rome
ηvent = 0.3
1.60
1.30
0.102
0.083
ηvent = 0.5
1.80
1.50
0.115
0.095
ηinf = 0.2
1.80
1.50
0.115
0.095
ηinf = 0.3
1.90
1.60
0.121
0.102
2.2.4 System D
The heat pump of the reference system D is the same as the one used in system C, and was
sized the same way. The traditional panel radiators were assumed to be in place before the
renovation and sized to cover the heat load of the building without the extra insulation applied
for HD25 or HD15. Design distribution and return temperatures were taken to be 90/70 °C,
but in the renovated houses studied, the actual radiator water temperatures would be lower,
due to the lower heat load.
2.3. Simulation tools
System A was modelled in MATLAB Simulink and systems B and C were modelled in
TRNSYS 17, while the reference system D was modelled in both tools, to enable comparison
between this and the other systems while reducing the risk of systematic errors. This also
allowed for a comparison between the two simulation tools. A time step of five minutes was
used in the TRNSYS simulations, while MATLAB Simulink uses an adaptive time step.
In MATLAB Simulink the complex building model of the Carnot Blockset was used. The
heat pump model in system D was based on performance map data. The heating capacity was
approximated linearly depending on the source inlet air temperature and the sink outlet water
temperature. The COP was based on Carnot COP and the Carnot performance factor. In the
initialization of the model (pre-processing) the Carnot performance factor and the linear
coefficients for the heating capacity were calculated in order to achieve the best possible
agreement.
In TRNSYS, the heat pump was modelled using a performance map with data on heating
capacity and compressor power for a range of testing points. The heat output and COP of the
heat pump were calculated in the model through interpolation between these points.
The ventilation radiator model of systems B and C was based on an Excel model provided
by a radiator manufacturer, which in turn was based on measurements on their own products
[26]. A link embedded in TRNSYS was used to connect the Excel model to the rest of the
system.
2.4. Controls
All heating systems and auxiliary heaters were controlled by on/off differential controllers
with hysteresis. The governing temperature was the indoor air temperature. The set point for
the primary heating systems was 20 °C, with upper and lower dead bands of 0.25 K.
Similarly, the auxiliary heaters had a set point of 19.75 °C and allowed the temperature to
vary between 19.5 °C and 20 °C. The set point for the auxiliary heater was set to a lower
value to avoid operation during hours when the primary system could manage the heating.
The ventilation was running independently of the heating control signals, but in systems A
and B the heat pumps were bypassed when no heating was needed.
3. Results
Figure 2 shows the annual heating supply by heat pump and compressor of the reference
system and Figure 3 the electrical energy consumption of the reference system, comparing
MATLAB Simulink and TRNSYS for all locations and renovation levels. In Figure 2, the
solid and dashed lines mark the heating demand with heat recovery for the HD25 and the
HD15 houses, respectively. The difference between the two tools exceeded 5 % only for
Madrid and Rome, where the difference was 7 % and 6 % respectively for supplied heating
and 11 % and 8 % respectively for electrical energy consumption. The trends were similar for
both energy standards of the house. In TRNSYS, all systems overshot the ideal heating
demand, which was defined as the heating required to keep the indoor air temperature at or
above 20 °C at all times, by 1 kWh/(m2 a) to 2 kWh/(m2 a). In Simulink, system D followed
the ideal heating demand more closely. The ideal heating demand simulated in Simulink was
higher than in TRNSYS for all climates except for Madrid and Rome, where it was lower.
The seasonal performance factor of the heat pump was around 0.1 higher in Simulink than in
TRNSYS. In terms of gains and losses of the house, some differences were noted in absorbed
solar energy. The solar gains in MATLAB Simulink were around 3 kWh/(m2·a) higher than in
TRNSYS for the climates of Madrid and Rome, while for other climates the solar gains were
2.5 kWh/(m2 a) to 5 kWh/(m2 a) lower in MATLAB Simulink than in TRNSYS.
Figure 2 Annual heating supplied by system D in MATLAB Simulink and in TRNSYS. Solid line marks heating demand of
HD25 with heat recovery; dashed line marks heating demand of HD15 with heat recovery.
0
10
20
30
40
50
60
Specific heating suuply [kWh/(m² a)]
HD25 MATLAB Simulink
HD25 TRNSYS
HD15 MATLAB Simulink
HD15 TRNSYS
Figure 3 - Electrical energy consumption of system D in MATLAB Simulink and in TRNSYS.
The relative energy consumption of systems A, B and C compared to the reference system D
is shown in Figure 4. System A is set in relation to the performance of system D in MATLAB
Simulink, while B and C are set in relation to the TRNSYS model of system D.
System A had the lowest energy consumption for both renovation levels in all climates. The
largest savings compared to system D were seen for the HD15 in cold climates, with a
maximum of 36 % for the climates of Stockholm and Gdansk.
System B showed a similar trend, but with less difference between the coldest and the
warmest climates, and also less difference between the two renovation levels. For the HD25
house it was close to system A in energy consumption in all climates. The maximum energy
saving compared to system D was 23 % for the HD15 house in Stockholm.
For system C, the energy use was consistently lower than the reference, with only small
variations with the climates. It was the best system, together with A and B, for the HD25
house in Rome. The energy savings compared to system D ranged from 3 % for the HD25
house in Madrid and Rome to 8 % for the HD15 house in Stockholm.
0
5
10
15
20
25
Specific energy consumtpion
[kWh/(m²a)]
HD25 MATLAB Simulink
HD25 TRNSYS
HD15 MATLAB Simulink
HD15 TRNSYS
Figure 4 Energy consumption of tested systems compared to the reference system for varying climate and heating demand.
The influence of ventilation rate on the energy performance is shown in Figure 5 and the
influence of infiltration rate in Figure 6, both for the HD25 house. System A was affected in a
positive direction relative to system D when the ventilation rate was increased and in a
negative way when the infiltration rate was increased. With a ventilation rate of 0.5 h-1, the
energy performance of system A was better than the reference for the climate of Rome. For
system B, both ways of increasing the air change rate were favorable compared to system D.
With an infiltration rate of 0.2 h-1, system B had the best energy performance for Stockholm,
and with an infiltration rate of 0.3 h-1 it was the best system also for Rome. System C was not
significantly influenced in any way in relation to the reference system by either of these
parameters.
Figure 5 - Energy consumption of tested systems (HD25) compared to the reference system for varying ventilation rate.
0.50
0.60
0.70
0.80
0.90
1.00
1.10
Stockholm
Gdansk
Stuttgart
London
Lyon
Madrid
Rome
Stockholm
Gdansk
Stuttgart
London
Lyon
Madrid
Rome
HD25 HD15
System A
System B
System C
System D
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
0.3 0.4 0.5
Ventilation rate [h-1]
Stockholm System A
Stockholm System B
Stockholm System C
Rome System A
Rome System B
Rome System C
System D
Figure 6 - Energy consumption of tested systems (HD25) compared to the reference system for varying infiltration rate.
Figure 7 shows the number of hours with room temperature above 26 °C for the reference
system. In Lyon, Madrid and Rome, the room temperature reached above 26 °C for 1000 h to
2000 h per year, with slightly higher figures for the HD15 house. All systems met the criteria
to keep the temperature above 19.5 °C at all times.
Figure 7 - Number of hours with room temperature above 26 °C for the reference system in MATLAB Simulink and in
TRNSYS.
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
0.1 0.2 0.3
Infiltration rate [h-1]
Stockholm System A
Stockholm System B
Stockholm System C
Rome System A
Rome System B
Rome System C
System D
0
500
1000
1500
2000
2500
Hours with room temperature > 26 °C
[h]
HD25 MATLAB Simulink
HD25 TRNSYS
HD15 MATLAB Simulink
HD15 TRNSYS
4. Discussion
In the comparison between the two simulation tools, some deviations were observed for the
performance of system D. The relatively high differences in percentage for Rome and Madrid
could partly be explained by the low heating demand for these locations. Also, in TRNSYS all
the tested systems provided 1 kWh/(m2 a) to 2 kWh/(m2 a) more than the ideal heating
demand, notably with a mutual difference of less than 1 kWh/(m2 a) between them. There also
seemed to be a difference in how the two tools handle solar gains of a house. This showed in
the number of hours with overheating, where the simulations in MATLAB Simulink gave a
higher number in most cases. It could also have influenced the difference in annual heating
demand.
The house was modelled as a single zone, disregarding solar gains to the roof. For the
heating demand, particularly for London and colder climates, this approach makes little or no
difference to the results compared to a model including roof and attic, since the solar gains are
relatively small during the heating season. In warmer climates the difference could be more
significant, and if the cooling demand is to be determined all solar gains should be taken into
account.
Heating systems that are based on heat recovery of ventilation air are always limited by the
ventilation rate. For both systems A and B in this study, the relatively low ventilation rate
limited the heating capacity of the respective heat pumps and increased the need for auxiliary
heating. Varying the ventilation rate, it was shown that the performance of these systems
system relative to the reference system improved with a higher ventilation rate, and vice
versa. When it comes to varying the infiltration rate, A and B are affected in opposite ways.
In system B, the exhaust fan enables the exhaust air heat pump to utilize both the ventilation
and infiltration air to deliver energy to the ventilation radiators. In system A, the MVHR unit
can only make use of the ventilation part, while the infiltrated air just adds to the heat losses.
All systems were compared for the same infiltration rate. However, the infiltration rate of a
house is dependent on the pressure difference between indoor and outdoor, which in turn
depends on the type of ventilation system installed [27]. System A, using balanced
ventilation, would have a lower infiltration rate than the other systems for the same house.
In the present study, the use of mechanical ventilation was accounted for only during the
months when the house required heating. In Sweden, building regulations [28] do not allow
replacing mechanical ventilation with opening windows. Extending the ventilation period
would strike the hardest on system A, since the MVHR unit consumes more energy than a
simple exhaust fan. For the HD15 house in Stockholm, applying mechanical ventilation all
year would increase the total energy consumption of system A by 8 %, whereas the increase
for systems B, C and D would be 2-3 % for the same case. However, bypassing the heat
recovery unit during summer would reduce the impact on energy consumption for system A.
For system C, some savings were seen due to the lower water temperature enabled by the
use of ventilation radiators. However, the water temperature in the reference system was
already low, since the existing radiators were sized for a higher heat load. The largest
reduction in energy consumption was seen for system A, where the air heat recovery cut down
the heating demand significantly compared to that of other systems. System B consumed less
energy than system C due to the higher source side temperature of the exhaust air heat pump.
System A was the system that benefitted the most from a higher renovation standard. It had
the lowest energy consumption for both renovation level and all climates, but for the HD25
house it consumed almost as much energy as system B, despite the advantage of MVHR. This
confirms the premise that the micro heat pump is best applied in very low energy building
such as Passive Houses and suggests that a system like B would be preferable in houses with
higher heating demand.
In a complete building retrofit, it may not always be feasible from the economic point of
view to achieve Passive House standard. For the climates of Gdansk and Stockholm 200-300
mm of extra insulation is required to go from HD25 to HD15 level. This will of course
increase the investment costs significantly, even though the total insulation thickness could be
reduced by choosing better insulating windows in such cold climates. On the other hand,
insulation of the floor may not always be feasible, thus increasing the need for improvements
on other parts of the building envelope.
The level of insulation can also be important for the choice of heating system in terms of
thermal comfort. If ventilation radiators are used in heavily insulated houses, as in systems B
and C, there could be problems with cold draft when the outdoor temperature is at or near the
balance temperature of the house. As the heating system will not be active above the balance
temperature, a lower balance temperature will allow colder air to be supplied through the
radiators.
In warmer climates, a thicker insulation leads to slightly higher indoor temperatures during
summer, thus occasionally increasing the cooling demand. The observed indoor temperatures
for Lyon, Madrid and Rome in this study indicate that the tested house would need a cooling
device in these climates; a service which could be provided by reversing the operation of the
heat pump.
A complete energy system for a house need also include domestic hot water. Air-to-water
heat pumps, like the ones used in systems B, C and D, are normally designed to handle both
space heating and hot water. System A, on the other hand, would require a complement to the
air-to-air micro heat pump to be able to provide this service. In heavily insulated houses,
where heat losses are minimized, the relative importance of hot water use will naturally
become larger.
The heat pump used in systems C and D was scaled down from 3.0 kW to heating capacities
ranging from 1.2 kW to 2.4 kW, assuming that the COP remained the same. In reality, the
Carnot efficiency, and thus the COP, might not be independent of the capacity of the heat
pump. For a scaling down of this relatively small magnitude, it may not have a great impact,
but it should be taken into consideration that it could affect the result of systems C and D,
especially for the warmer climates where the heat pump has been scaled down more.
The TRNSYS heat pump model used was not designed for variable speed. The exhaust air
heat pump of system B would, in reality, be able to vary the compressor speed to cope with
higher loads, and would therefore need to use less auxiliary heating than the model did. The
micro heat pump of system A also has the potential to perform slightly better with a speed
controlled compressor. The influence of control strategy could be a subject for future studies.
5. Conclusions
In dynamic simulation of building energy performance, the results are to some extent
dependent on the choice of simulation tool. The differences between MATLAB Simulink and
TRNSYS 17 were in this study found to be larger for warmer climates, possibly because of
differences in how solar gains are treated in the two tools. Also, the TRNSYS systems
supplied slightly more than the ideal heating demand. Still, the magnitudes of the deviations
were acceptable.
Both systems A and B were more favorable in colder climates; system A due to the heat
recovery and system B due to the higher source side temperature of the heat pump. According
to the results of this study, system A is the best option in well-insulated houses with low
infiltration and high ventilation rate. For a less insulated house with higher infiltration rate,
located in the same climate, system B would have the best energy performance. The
performance of system C shows that some energy can be saved by applying ventilation
radiators instead of traditional panel radiators, although in this case the panel radiators were
sized for a higher heat load and thus also enabled a low water temperature. System C was
better than the reference system, but not as good as A or B.
In future studies of retrofitted buildings, it is suggested to include the use of domestic hot
water, as this will make up a larger part of the total energy consumption when the space
heating demand is lowered through renovation of the building envelope. In warm climates,
cooling demand should also be considered.
Acknowledgment
This study was carried out in close connection to the European project iNSPiRe, which is
funded through the 7th Framework Program (Proposal number: 314461; Title: Development of
Systematic Packages for Deep Energy Renovation of Residential and Tertiary Buildings
including Envelope and Systems; Duration: 2012-10-01 2016-09-30).
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NIBE—Indata till TMF:s program ver 2.1 för NIBE F750
  • N—indata
N—Indata, NIBE—Indata till TMF:s program ver 2.1 för NIBE F750.(in Swedish).
TRNSYS 17—a transient sys-tems simulation program11] iNSPiRe, European Commission 7th Framework Programme project. Proposal number: 314461; Title: Development of Systematic Packages for Deep Energy Renovation of Residential and Tertiary Buildings including Envelope and Sys-tems
  • S A Klein
  • A Beckman
  • W Mitchell
  • A Duffie
S.A. Klein, A. Beckman, W. Mitchell, A. Duffie, TRNSYS 17—a transient sys-tems simulation program, in: Solar Energy Laboratory, University of Wisconsin, Madison, 2011. [11] iNSPiRe, European Commission 7th Framework Programme project. Proposal number: 314461; Title: Development of Systematic Packages for Deep Energy Renovation of Residential and Tertiary Buildings including Envelope and Sys-tems;
Purmo Air Simulator Vers. 05.11
  • M Ivonen
Ivonen, M. (2007). Purmo Air Simulator Vers. 05.11.2007.