LCC-OPTIMISED COOLING SYSTEMS - Energy and Building Design
Transcript of LCC-OPTIMISED COOLING SYSTEMS - Energy and Building Design
LCC-OPTIMISED COOLING SYSTEMS - A Study on Office Buildings in Different European Climates and Energy Markets
Roman Lechner
Master Thesis in Energy-efficient and Environmental BuildingsFaculty of Engineering | Lund University
Lund UniversityLund University, with eight faculties and a number of research centers and specialized in-stitutes, is the largest establishment for research and higher education in Scandinavia. The main part of the University is situated in the small city of Lund which has about 112 000 inhabitants. A number of departments for research and education are, however, located in Malmö and Helsingborg. Lund University was founded in 1666 and has today a total staff of 6 000 employees and 47 000 students attending 280 degree programs and 2 300 subject courses offered by 63 departments.
Master Program in Energy-efficient and Environmental Building DesignThis international program provides knowledge, skills and competencies within the area of energy-efficient and environmental building design in cold climates. The goal is to train highly skilled professionals, who will significantly contribute to and influence the design, building or renovation of energy-efficient buildings, taking into consideration the architec-ture and environment, the inhabitants’ behavior and needs, their health and comfort as well as the overall economy.
The degree project is the final part of the master program leading to a Master of Science (120 credits) in Energy-efficient and Environmental Buildings.
Examiner: Dennis Johansson (HVAC)Supervisor: Saqib Javed (HVAC)
Keywords: Office building, Cooling systems, LCC, Energy markets, Solar cooling
Thesis: EEBD–15/11
Abstract
Even with increasing energy performances and stricter building regulations throughout the
European Union, the use of active cooling systems in office building is still inevitable. It is
therefore essential to draw on efficient and economically reasonable system types and energy
sources. This thesis evaluates the life-cycle costs of various cooling systems and energy
sources in altering European countries, climates and energy markets.
In the beginning of this project, representative European climates are chosen in which the
building performance of a validated reference office building is simulated. After designing
the cooling systems, chiller capacities and other components for each location, the energy
performances of these systems are analyzed. In the end, market specific data in terms of a
country’s economic situation and development, energy prices as well as component costs are
gathered. Using this data, the life-cycle costs of each cooling system is calculated for a life
span of 25 years, using the net present value method. Besides this, a sensitivity analysis is
carried out to determine the impact of different development scenarios of European markets.
It has been shown that the net present value is mostly influenced by the initial energy prices
for the chiller supply energy and the corresponding development of the energy prices
throughout the years. Besides this, it has been found that the investment costs account for
40 % up to 75 % of the total net present value, depending on the location and the size of the
installed system. Alternative forms of cooling supply such as district cooling or solar
energy-assisted cooling systems can be cost-efficient under certain circumstances. It is also
noted that due to the absence of clauses that obligate energy supply companies to publish
energy prices and other relevant financial information, it is rather difficult to obtain conclusive
and valid information in terms of the cost-efficiency of the cooling systems.
Acknowledgements
First, I would like to address special thanks to my thesis supervisor Saqib Javed for his
invaluable input and guidance, as well as his useful critiques and in general his professional
and supportive attitude towards students. Additionally, he offered continuous mental and
subject-specific support, particularly during stressful times of my research project.
Furthermore, I would like to thank all my colleagues and fellow students, professors, lectures
and staff who are involved in LTH’s master program in “Energy-efficient and Environmental
Building Design”. Due to this program, I have gained a lot valuable experience and feel
prepared to actively contribute to increasing the energy-efficiency and sustainability in the
building industry. In this sense, I would also like to give thanks to the Eliasson Foundation
for funding my master studies.
Finally, I would like to express my big gratitude to my friends and family in Austria and
Sweden, whom continuously showed me their support in many different ways. Especially, I
would like to mention my parents, my brother Martin, my wife Monica as well as my close
friends Vaia and Yiota, who made my life in Sweden much more fun and pleasant.
Date: 12/23/2015
Location: Portland, USA
List of abbreviations
3D 3-dimensional
A Annual payment / Annuity
A0 Price at present time / time 0
A1 Compounded price after one year
ACH Air-changes per hour
AHU Air handling unit
ASHRAE American society of heating, refrigerating, and air-conditioning
engineers
BIM Building information modeling
CHP Combined heat and power
DHC District heating and cooling
EPBD European performance of buildings directive
EU European Union
F/V Building compactness factor in area per volume
g Growth rate
i Interest rate
HVAC Heating, ventilation and air-conditioning
LCC Life-cycle costs
n50 Infiltration rate at a pressure difference of 50 Pascal
N Number of years
NPV Net present value
PV Photovoltaic
SEK Swedish crowns
SHGC Solar heat gain coefficient
SVEBY Swedish energy-efficiency measures in buildings
U-value Heat transfer coefficient in W/(m²-K)
Table of content
1 Introduction ................................................................................................................ 1 1.1 Background and motivation 1 1.2 Aims, goals and scope 1
2 Methodology ............................................................................................................... 3
2.1 Climates and locations 3 2.2 The building 4
2.2.1 Geometry 4 2.2.2 Solar access analysis 5
2.3 Energy simulations 6 2.3.1 General simulation input data 6
2.3.1.1 Cell-office layout 8 2.3.1.2 Open-office layout 10
2.3.2 Location-dependent simulation input data 11 2.3.2.1 Cold climate 11 2.3.2.2 Moderate climate 13 2.3.2.3 Hot climate 14
2.4 Cooling systems 15 2.4.1 Limitations and assumptions 15 2.4.2 Cooling system layout and input data 16
2.4.2.1 Vapor compression chiller 16 2.4.2.2 District heating driven absorption chiller 18 2.4.2.3 District cooling 19 2.4.2.4 Solar thermal assisted absorption chiller 21 2.4.2.5 Photovoltaic assisted vapor compression chiller 22
2.5 LCC analysis 23 2.5.1 LCC analysis based on recent market developments and energy policies 25 2.5.2 Sensitivity analysis 26
2.5.2.1 Scenario I 27 2.5.2.2 Scenario II 27 2.5.2.3 Scenario III 27
3 Results ....................................................................................................................... 29
3.1 Climates and locations 29 3.2 Solar access analysis 30 3.3 Energy simulations 32 3.4 Cooling systems 34
3.4.1 System- and location-dependent solar fraction 38 3.5 LCC analysis 40
3.5.1 LCC analysis based on recent market developments and energy policies 40 3.5.2 Sensitivity analysis 46
3.5.2.1 Scenario I 46 3.5.2.2 Scenario II 50 3.5.2.3 Scenario III 54
4 Discussion ................................................................................................................. 59
5 Conclusions ............................................................................................................... 67
References ......................................................................................................................... 69
Appendix 1 – Floor plans, sections and elevations of the assessed reference building ... A1-1 Appendix 2 – PV layout for 2-m and 1.5-m spacing ...................................................... A2-1 Appendix 3 – Monthly energy performance of cooling systems in Berlin ...................... A3-1 Appendix 4 – Material costs of the different components used in the LCC analysis ...... A4-1
1
1 Introduction
1.1 Background and motivation
Today, buildings account for approximately 40 percent of the total energy demand in the
European Union, leaving a great potential for energy efficiency measures. Recent
developments and political guidelines introduced by the European Union, for instance the
EPBD or the EU 20-20-20 goals, aim at reducing this share by setting ambitious measures to
reduce the energy intensity of buildings, as well as to increase the efficiency of the system
components. Due to the characteristics of the European climate, most of these regulations
mainly affect insulation properties and therefore result in lowering building heating demands.
In general, increasing the thickness of thermal insulation or improving the airtightness of a
building comes along with overheating issues and an increased demand for cooling energy.
In residential buildings, the overheating issue can generally be avoided by following a smart
building design strategy or by implementing effective shading devices. This is because
residential buildings are mostly unoccupied during the day and therefore have low internal
gains during times that follow the same occupancy patterns, as hours in this period represent
the most critical ones in terms of cooling and overheating issues. In contrast to that,
commercial office buildings do not show these characteristics, as they mostly display high
occupancies with high internal loads during the most critical hours of the day. Besides that,
office buildings usually tend to have a higher window-to-wall ratio. Therefore, heat can
accumulate easily and the use of active cooling or refrigeration systems that come together
with increased energy demand becomes rather inevitable. Hence, it is necessary to ensure
that these active cooling systems operate in optimal conditions so that the amount of
consumed energy is as low as possible. In addition to that, environmentally-friendly
technologies and renewable forms of energy can be used to further reduce the primary energy
demand of such active cooling systems. Nevertheless, besides having energy-efficient and
innovative cooling concepts, it has to be ensured that these cooling systems are also
competitive and feasible in from an economic point of view.
1.2 Aims, goals and scope
The aim of this master thesis is to investigate various conventional and innovative
refrigeration technologies and concepts in different European locations and climate zones,
using different energy sources in regards to their life-cycle costs. It is desired to have a
detailed description on the behavior and performance of the assessed refrigeration concepts
in altering European climate zones. However, it has to be mentioned that the project also
underlies certain limitations, some of which may include assumptions due to data
unavailability or software limitations. With the obtained data, it is feasible to perform an
LCC analysis on each of the system, using accurate data from the country specific energy
markets. In the very end it is desirable to establish a roadmap or guideline, which should
assist designers or project engineers in assessing the most cost-effective solution in a certain
climate and energy market.
2
3
2 Methodology
This chapter provides a detailed description of the methodology used for the research project
as well as the tools that were used in order to obtain data and results. The following sections
discuss the various aspects of this project in detail.
2.1 Climates and locations
In the beginning of this project, a parametric study on different climates was carried out to
choose representative locations that will be used later for the simulations on the detailed
model of the building. This parametric study was performed on a simple box building in
“DesignBuilder” (DesignBuilder Software Ltd, 2015), a dynamic building simulation
program based on “EnergyPlus” (U.S. Department of Energy, 2015). The studied box
building has a length of 20 meters and a width of 10 meters. It only consists of one single
zone. The simulation input data such as construction types, schedules, loads, etc. followed
the default “DesignBuilder” templates for a generic office building.
The investigated locations were categorized into three main climate zones:
Cold climate
Moderate climate
Hot climate
For each of these climate zones, several locations were analyzed using the related weather
data (ASHRAE, 2001), while also considering coastal and continental influences. The
temperature differences between seasons vary a lot in a more continental location compared
to a coastal location, as the temperature buffer effect of a large water area is non-existent.
This phenomenon might lead to varying energy figures and systems sizes for similar
latitudes. In the end of the study, it was desired to have a pool of six different locations that
match these geographic criteria while simultaneously featuring local district energy
networks.
A map of the European climate zones according to the ASHRAE standard 169-2006 can be
seen in Figure 1 (ASHRAE, 2012). A list of the studied locations is provided in Table 1.
Table 1 Analyzed locations in the parametric study on representative climates.
Coastal, Country, (ASHRAE
climate no)
Continental, Country, (ASHRAE
climate no.)
Cold Reykjavik, ISL, (7)
Stockholm, SWE, (6A)
Kiruna, SWE, (8)
Tampere, FIN, (7)
Moderate
Copenhagen, DNK, (5C)
Amsterdam, NLD, (4A)
London, GBR, (4A)
Berlin, DEU, (5C)
Vienna, AUT, (5A)
Kiev, UKR, (5A)
Hot
Lisbon, PRT, (3C)
Rome, ITA, (3C)
Athens, GRC, (3A)
Ankara, TUR, (5A)
Seville, ESP, (3A)
Zaragoza, ESP, (3C)
4
Figure 1 European climate zones according to ASHRAE standard 169-2006. (ASHRAE,
2012)
2.2 The building
This section provides relevant information on the building, including building geometry,
construction, window properties and floor layout that were used for the preliminary building
performance simulations in each climate zone.
2.2.1 Geometry
The building is a six-story office building with two different floor layouts, a cell-office type
and an open-office type. It was chosen to be the representative building for this study.
Previously, the function of this building as an appropriate reference building has been
validated by researchers and scientists (Poirazis, 2005)
In this project, the building was modelled in “Autodesk Revit” (Autodesk Inc., 2015), a BIM
software for designers and engineers. A 3D image of the “Autodesk Revit” model can be
seen in Figure 2. Detailed information of the building dimensions and floor plans as well as
a number of sections and elevations can be found in Appendix 1.
The building has an occupied floor area of approximately 5900 m², depending on the floor
layout of the building, as the exterior dimensions are the same for both the cell-office and the
open-office types. The original building has two different façade constructions with an
5
average window to wall ratio of approximately 40 %. The windows of the short façade are
2.7 meters high and 1.6 meters wide and the windows of the long façade are 1.3 meters high
and 1.0 meters wide. The frame has a total width of 0.1 meters. The rooftop has an
unoccupied space for installation of technical components and air handling units.
Figure 2 3D views of the building from south-west (left) and north-east (right).
2.2.2 Solar access analysis
The solar access analyses on various building facades in each climate zone were performed
using a simple “SketchUp” (Trimble Navigation Limited, 2013) model of the building, which
was then imported into “Rhinoceros 5.0” (Robert McNeel & Associates, 2014) and analyzed
using the “Rhinoceros” plugins “Grasshopper” (Davidson, 2015) and “DIVAforRhino”
(Lagios, 2015). “SketchUp” is a simple 3D modeling tool. “Rhinoceros 5.0” is an advanced
3D modeling tool with a vast number of extensions and plugins such as “Grasshopper”, a
graphical algorithm editor and “DIVAforRhino”, an environmental analysis tool.
The same tools were also used to create shading masks and radiation images for the rooftop
of the building, which are essential for determining the energy output of solar energy systems
in the later system performance simulations.
It has to be mentioned that the building was assumed to be in an unshaded environment for
all simulations. In reality, the solar irradiation on the facades might be slightly lower due to
shading of surrounding objects such as adjacent buildings or trees. However, the results of
the shading masks on the roof are likely to not be influenced by any surrounding objects as
the building consists of six stories and is therefore rather high. Mutual shading of the small
technical area on the roof or the railing might therefore be much more crucial.
N N
6
2.3 Energy simulations
This section details the essential input values used for the dynamic energy simulations of
each climate zone in order to gain relevant data for the design process of the cooling systems.
All the detailed simulations were carried out in “DesignBuilder”. It has to be mentioned that
all the simulations were simplified by assessing only three different floor types, the ground
floor, the top floor and one intermediate floor with an adiabatic ceiling and slab. The energy
results of this particular intermediate floor were then multiplied with a factor of 4. These
simplifications allowed to shorten the excessive simulation time and can be justified by the
fact that the building has only a representative character. A 3D image of the “DesignBuilder”
model can be seen in Figure 3.
Figure 3 3D view of the building as modeled in "DesignBuilder".
2.3.1 General simulation input data
Most of the data used for the simulations, such as floor layout, occupancy profile, operating
schedules, internal load density or HVAC-related data remained unchanged for all simulation
cases and is explained in this section. Data that was modified in the course of the simulation
process will be discussed later.
A list of all the zones with relevant input data can be seen in Table 3. The data for the internal
loads was derived from SVEBY (2013) and is briefly described in Table 2.
7
Table 2 Recommended input values for energy simulations by SVEBY.
Inputs Values
Lighting (W/m²) Office areas: 7 - 10
Remaining areas: 4
Laptop (W) 65
Charger (W) 10
Printer (W) 160
Copy machine (W) 400
Catering (W/m²) 2
Table 3 Zone data for the simulations used in "DesignBuilder".
Zone Area (m²) Occupants
Lighting
density
(W/m²)
Equipment
Single office 10.8 1 8
1 Laptop
1 Charger
1 Printer
Double office 16.2 2 8
2 Laptops
2 Charger
1 Printer
Corner office 18.5 1 8
1 Laptop
1 Charger
1 Printer
Open office 869 48 8
48 Laptops
48 Charger
24 Printer
Meeting big 27.0 10 4
1 Laptop
1 Charger
1 Printer
Meeting small 21.5 5 4
1 Laptop
1 Charger
1 Printer
Storage 14.0 - 4 1 Laptop
Copy room 14.0 - 4 1 Copy
machine
Lavatory 3.4 - 4 -
Pantry 18.47 - 4 Catering
Corridor 358.5 - 4 -
8
Each office zone was assumed to be occupied for 70 % of the time according to SVEBY
(2013) recommendations (SVEBY, 2013). The occupancy density in all other zones was
assumed to be 30 % of the amount of people on each floor, except the meeting rooms, which
were assumed to be fully occupied from 09:00 to 09:30 and 12:00 to 13:30 each weekday.
The ventilation shaft was assumed to be both unoccupied and unconditioned.
The building was assumed to be occupied during workdays from 09:00 until 17:00. The
operating schedules of the equipment as well as lighting were following the occupancy
schedule. The schedule for mechanical ventilation as well as heating and cooling was set to
be “ON” for normal workdays between 06:00 and 18:00.
The hygienic airflow rate and the people-dependent airflow rates were set to be 0.35 l/(s-m²)
and 7.0 l/(s-m²), respectively. The heat recovery efficiency was assumed to be 70 %. The set
point temperatures for heating and cooling were set to be 21 °C and 25 °C.
2.3.1.1 Cell-office layout
The cell-office building contains 348 rooms in total. Figure 4 displays the rooms per floor as
simulated in “DesignBuilder”. A list of all the rooms per floor can be seen in Table 4.
Table 4 List of zones per floor in the cell-office building
Zone type Ground floor Floors 2 to 6
Corner office 4 4
Single office 16 28
Double office 11 14
Meeting small 1 0
Meeting big 3 0
Copy room 2 2
Storage 7 2
Lavatory 6 6
Pantry 2 2
Corridor 1 1
9
Figure 4 Zone layout of the ground floor (left) and the remaining floors (right) for the cell-
office building in “DesignBuilder”.
10
2.3.1.2 Open-office layout
The open-office building contains 107 rooms in total. Figure 5 displays the rooms per floor
as simulated in “DesignBuilder”. A list of all the rooms per floor can be seen in Table 5.
Figure 5 Zone layout of the ground floor (left) and the remaining floors (right) for the open-
office building in “DesignBuilder”.
11
Table 5 List of zones per floor in the open-office building
Zone type Ground floor Floors 2 to 6
Corner office 4 4
Open office 1 1
Copy room 2 2
Storage 7 2
Lavatory 6 6
Pantry 2 2
2.3.2 Location-dependent simulation input data
In order to achieve a more realistic simulation scenario for each location, some exterior
building elements like facades or windows were modified. When making these
modifications, it was ensured that the building meets the requirements for climate-specific
building codes. However, it has to be mentioned that only one building code was applied for
each simulated climate zone. The used building codes were the Swedish building code for
the cold climate zone (Stockholm, Tampere) , the British building code for the moderate
climate zone (London, Berlin) and the Greek building code for the hot climate zone (Athens,
Zaragoza), respectively.
2.3.2.1 Cold climate
The most relevant input data for the locations in the cold climate zones can be seen from
Table 7 to Table 11. The applied building code for the buildings in Stockholm and Tampere
is the Swedish building code for the local climate zone “III” and can be seen in Table 6
(Concerted Action, 2013). The constructions for the cold climate were used from the office
building studied by Poirazis (Poirazis, 2005), which was originally studied in Malmö,
Sweden. Since both Malmö and Stockholm are located in the Swedish climate zone “III”, it
was assumed that the original constructions can be used without any further modifications.
Table 6 Comparison of energy data used for simulations and as required by Swedish
building regulations.
Unit
Maximum according
to Swedish building
code
Stockholm
Open / Cell
Tampere
Open / Cell
U-value W/(m²-K) 0.60 0.54 0.54
Allowed purchased
energy kWh/m² 80 48 / 52 56 / 62
12
Table 6 shows the compliance of the studied building cases in the cold climate zone with the
current Swedish building code for the local climate zone “III” and the values used for the
simulations.
Table 7 External wall construction details of the long facade in cold climate from exterior to
interior side.
Material Thickness (m) Conductivity
(W/(m-K))
Specific heat
capacity
(J/(kg-K))
Density
(kg/m³)
Brick 0.12 0.58 840 1500
Air gap 0.04
Gypsum board 0.009 0.22 1090 970
Mineral wool
90 % - wood
studs 10 %
0.1068 0.036 – 0.14 754 – 2300 16 – 500
Gypsum board 0.013 0.22 1090 970
Table 8 External wall construction details of the short facade in cold climate from exterior to
interior side.
Material Thickness (m) Conductivity
(W/(m-K))
Specific heat
capacity
(J/(kg-K))
Density
(kg/m³)
Brick 0.12 0.58 840 1500
Air gap 0.04
Mineral wool 0.145 0.036 754 16
Concrete 0.20 1.4 840 2100
Table 9 Floor to ground construction details in cold climate from exterior to interior side.
Material Thickness (m) Conductivity
(W/(m-K))
Specific heat
capacity
(J/(kg-K))
Density
(kg/m³)
EPS 0.100 0.0336 1700 1000
Concrete 0.100 1.4 1.4 840
Linoleum 0.0025 0.156 1260 1200
13
Table 10 Roof construction details in cold climate from exterior to interior side.
Material Thickness (m) Conductivity
(W/(m-K))
Specific heat
capacity
(J/(kg-K))
Density
(kg/m³)
Roof felt 0.003 0.13 1300 930
Wood 0.02 0.14 2300 500
Mineral wool 0.20 0.036 754 16
Concrete 0.30 1.4 840 2100
Ceiling tiles 0.0125 0.057 837 720
Table 11 Construction of the window in cold climate from exterior to interior side.
Glazing U-value
(W/(m²-K))
SHGC
(%)
Light transmission
(%)
Triple pane
coated glass
13 mm air
1.21 36 54
Frame, 100
mm width Thickness (m)
Conductivity
(W/(m-K))
Specific heat
capacity
(J/(kg-K))
Density
(kg/m³)
Aluminum 0.005 160 880 2800
Wood 0.06 0.19 2390 700
2.3.2.2 Moderate climate
The most relevant input data for the locations in the moderate climate zones can be seen in
Table 13 and Table 14. The applied building code for the buildings in London and Berlin is
the British building code and can be seen in Table 12 (Planning Portal, 2013). The
constructions and materials used for the energy simulations of the moderate climate are the
same as the ones in Section 2.3.2.1, but with a modified thickness of the exterior insulation
layers or window panes. The changes can be seen in Table 13 and Table 14.
Table 12 shows the compliance of the studied building cases in the moderate climate zone
with the current British building code and the values used for the simulations.
Table 12 Comparison of energy data used for simulations and as required by British building
regulations.
Unit Maximum according to
British building code
Value used for
simulations
Roof U-value W/(m²-K) 0.25 0.23
External wall U-value W/(m²-K) 0.35 0.33
Ground floor U-value W/(m²-K) 0.25 0.22
Window U-value W/(m²-K) 2.20 1.82
External door U-value W/(m²-K) 3.50 2.82
n50 value m³/(h-m²) 10 2.7
14
Table 13 Modified construction insulation thicknesses in moderate climate.
Construction element Insulation thickness
(m)
External wall, long façade 0.1068
External wall, short façade 0.10
Floor to the ground 0.10
Roof 0.13
Table 14 Modified construction of the window in moderate climate.
Glazing U-value
(W/(m²-K))
SHGC
(%)
Light
transmission (%)
Triple pane clear glass
13 mm air 1.76 69 0.74
2.3.2.3 Hot climate
The constructions and materials used in the energy simulations for the hot climate are the
same as the ones described in in Section 2.3.2.1, but with a modified thickness of the exterior
insulation layers or window panes. The most relevant input data for the locations in the hot
climate zones can be seen in Table 16 and Table 17. The applied building code for the
buildings in Athens and Zaragoza is the Greek building code for the local climate zone “A”
and can be seen in Table 15 (Concerted Action, 2013).
Table 15 Comparison of energy data used for simulations and as required by Greek building
regulations.
Unit Maximum according
to Greek building
code
Value used
for
simulations
Roof U-value W/(m²-K) 0.50 0.42
External wall U-value W/(m²-K) 0.60 0.47
Ground floor U-value W/(m²-K) 0.50 0.44
Window U-value W/(m²-K) 2.20 1.82
Average U-value for F/V < 0.4 W/(m²-K) 1.15 0.82
Table 15 shows the compliance of the studied building cases in the hot climate zone with the
current Greek building code and the values used for the simulations.
15
Table 16 Modified construction insulation thicknesses in hot climate.
Construction element Insulation thickness
(m)
External wall, long façade 0.05
External wall, short façade 0.05
Floor to the ground 0.07
Roof 0.06
Table 17 Modified construction of the window in hot climate.
Glazing U-value
(W/(m²-K))
SHGC
(%)
Light transmission
(%)
Triple pane clear glass
13 mm air 1.76 69 0.74
2.4 Cooling systems
Based on the data obtained from the detailed energy simulations in “DesignBuilder”, several
refrigeration plants operating on different concepts and using varying secondary energy
sources had to be determined. A list of the investigated refrigeration principles can be seen
below:
- Vapor compression refrigeration system powered by the electricity grid.
- Absorption refrigeration system powered by district heating.
- District cooling system.
- Absorption refrigeration system powered by solar thermal collectors with district
heating as backup.
- Vapor compression refrigeration system powered by the electricity grid and assisted
by photovoltaic modules.
Each of these refrigeration plants were modified for each investigated location in terms of
system size, refrigeration capacities and supplied energy. The simulation software used for
this step was “Polysun” (Vela Solaris AG, 2015), a design tool for photovoltaic and solar
thermal systems as well as geothermal and generic system design. The cooling was provided
to the rooms via standard cooling coils in the building’s AHUs. In order to decrease the
required system size, a cold water storage tank was placed between the chiller and the cooling
coils of the AHU.
2.4.1 Limitations and assumptions
During the course of this study, several limitations for using “Polysun” for this study were
found, the most important of which are listed below:
- The data which has been obtained from the detailed energy simulations in
“DesignBuilder” cannot be entirely imported to “Polysun”, which only offers a
16
limited choice of energy-relevant input data to perform its own internal energy
simulations. Furthermore, it is not possible to enter the building geometry and floor
layout as they were described in Section 2.3.1. Instead, the specific heating and
cooling demands, the specific heating and cooling loads as well as manually
calculated thermal storage properties of the buildings were used for each location.
The differences of the energy simulations are apparent when comparing the location
dependent annual cooling demands per m² in Section 3.3, particularly when
comparing the graphs in Figure 20.
- The building is originally assumed to have one AHU per occupied floor. However,
the maximum cooling coil capacity of an AHU in “Polysun” is limited to 30 kW,
hence, leading to a higher number of simulated AHU than needed, particularly in the
locations London, Berlin, Athens and Zaragoza. Due to this limitation, the obtained
electricity demands for the fans inside the AHU are likely to be higher than they
would appear in reality with one AHU per floor. On the other hand it can be said that
a higher number of installed AHUs is sometimes desirable and more beneficial in
terms of flexibility, which is particularly important if the building is rented by more
than one tenant. In addition, the specific fan powers and therefore the electricity
demands can be lowered, since the relation between electric power demand and air
flow rate is increasing with bigger AHUs.
- Due to the rather large system sizes that occur in this research project, “Polysun”
reached its calculation capacities, particularly when implementing cooling towers to
the system diagrams. Instead of using cooling tower templates as they are available
in the software, a constant heat sink in terms of capacity, primary temperatures and
flow rates was assumed. In order to make the results more realistic, the electricity
that is needed to operate cooling towers was calculated manually for each hour the
heat sink was in operation and added to the simulated energy demand.
2.4.2 Cooling system layout and input data
This section describes the functionality and relevant input data of different refrigeration
plants as they were calculated and designed in “Polysun”. The theoretical background of the
functional principle of these refrigeration concept can be found in any HVAC text book and
will not be explained in this thesis. The buildings were modeled according to the correlating
data from “DesignBuilder”, however the limitations that were mentioned in section 2.4.1
have to be kept in mind.
2.4.2.1 Vapor compression chiller
This section provides information on simulation input data and the functionality of the
refrigeration system based on a conventional vapor compression chiller for each of the
assessed climate and location.
The system consists of two different hydronic cycles, one each for heating and cooling, which
are mechanically separated. The heating demand is met by radiators (2) that are fed by a
17
district heating system (4). In order to decrease the required system size, a hot water buffer
tank (3) is installed between the radiators and the energy source. However, it has to be
mentioned that all the parameters connected to heat supply in terms of space heating will not
be considered later in the LCC analysis, as it is not relevant for the purpose of this study. The
cooling system consists of the main chiller unit (6), an outdoor cooling tower (8) unit and a
cold water storage tank (7) to reduce the required system size. The cooling demand is met by
the cooling coils of the building’s AHUs (5).
Table 18 List of components in the system layout of the vapor compression chiller of Figure
6.
Component Description
1 Building
2 Radiators for heat supply
3 Hot water storage tank
4 District heating
5 AHU with cooling coil
6 Vapor compression chiller
7 Cold water storage tank
8 Heat sink for re-cooling
Figure 6 System layout of the vapor compression chiller.
The vapor compression chillers that were used for this study have a nominal cooling capacity
and a COP of respectively 185 kW and 4.5 for Stockholm and Tampere, 222 kW and 4.17
for London and Berlin and 306 kW and 4.58 for Athens and Zaragoza. It has to be mentioned
that the COP of the chillers was assumed to be constant for the respective locations, which
is not reflected in reality as it changes dynamically with different system temperatures. The
heating capacity of the district heating transfer station was set 400 kW for Stockholm and
Tampere, 300 kW for London and Berlin and 200 kW for Athens and Zaragoza. The storage
tanks for hot and cold water have a water capacity of 10.4 m³. The used cooling towers have
18
a nominal re-cooling capacity of 306 kW, with a total number of one tower for Stockholm,
Tampere, London and Berlin and two cooling towers for Athens and Zaragoza. However, the
last limitation described in chapter 2.4.1 has to be considered at this stage.
The pump between components 5 and 7 is activated if the indoor air temperature exceeds the
set point temperature for cooling by 0.1 K. The chiller and all the other connected
components that are required to supply, start to operate if the temperature of the top layer in
the cold water tank exceeds 10 °C. The system stops operating if the required indoor
temperature is equal to the cooling set point temperature and the cold water tank is fully
charged, meaning that the bottom temperature reaches 3.5 °C.
2.4.2.2 District heating driven absorption chiller
This section provides information on simulation input data and the functionality of the
refrigeration system based on an absorption chiller for each of the assessed climate and
location.
Table 19 List of components in the system layout of the absorption chiller of Figure 7.
Component Description
1 Building
2 Radiators for heat supply
3 Hot water storage tank
4 District heating
5 AHU with cooling coil
6 Absorption chiller
7 Cold water storage tank
8 Heat sink for re-cooling
The system consists of two different hydronic cycles, one each for heating and cooling, which
are mechanically separated. However, the hot water tank (3) is indirectly connected to the
absorption chiller (6) through the generator heat exchanger in the chiller. The heating demand
is met by radiators (2) that are fed by a district heating system (4). In order to decrease the
required system size, a hot water buffer tank (3) is installed between the radiators and the
energy source. Again, it has to be mentioned that all the parameters connected to heat supply
in terms of space heating will not be considered later in the LCC analysis, as it is not relevant
for the purpose of this study. The cooling system consists of the main absorption chiller unit
(6), an outdoor cooling tower (8) and a cold water storage tank (7) to reduce the required
system size. The cooling demand is met by the cooling coils of the building’s AHUs (5).
The absorption chillers used for different locations are all single-staged Lithium-Bromide
chillers. They have an average COP and a cooling capacity of respectively 0.75 and 175 kW
for Stockholm and Tampere, 0.75 and 281 kW for London and Berlin, and 0.75 and 351 kW
for Athens and Zaragoza, respectively. However, it has to be noted that the COP was assumed
to be constant. The heating capacity of the district heating transfer station was set to be 200
kW for Stockholm and Tampere, 300 kW for London and Berlin and 400 kW for Athens and
Zaragoza. The storage tanks for hot and cold water have a water capacity of 10.4 m³. The
19
used cooling towers have a nominal re-cooling capacity of 306 kW, with a total number of
one tower for Stockholm, Tampere, London and Berlin and two cooling towers for Athens
and Zaragoza. Again, the last limitation described in chapter 2.4.1 has to be considered at
this stage.
Figure 7 System layout of the district heating driven absorption chiller.
The pump between components 5 and 7 is activated if the indoor air temperature exceeds the
set point temperature for cooling by 0.1 K. The chiller and all the other connected
components that are required to supply start to operate if the temperature of the top layer in
the cold water tank exceeds 10 °C. The system stops operating if the required indoor
temperature is equal to the cooling set point temperature and the cold water tank is fully
charged, meaning that the bottom temperature reaches 3.5 °C. The district heating starts
operating if the bottom temperature of the hot water tank is less than 90 °C and stops
operating if the tank is fully charged, meaning that the top temperature of the hot water tank
reaches 95 °C.
2.4.2.3 District cooling
This section provides information on simulation input data and the functionality of the
refrigeration system based on district cooling for each assessed climate and location.
The system consists of two different hydronic cycles, one each for heating and cooling, which
are mechanically separated. The heating demand is met by radiators (2) that are fed by a
district heating system (4). In order to decrease the required system size, a hot water buffer
tank (3) is installed between the radiators and the energy source. All the parameters
connected to heat supply in terms of space heating will not be considered later in the LCC
analysis, as it is not relevant for the purpose of this study. The cooling system consists of a
20
district cooling heat exchanger (6) and a cold water storage tank (7) to reduce the required
system size. The cooling demand is met by the cooling coils of the building’s AHUs (5).
Table 20 List of components in the system layout of the district cooling system of Figure 8.
Component Description
1 Building
2 Radiators for heat supply
3 Hot water storage tank
4 District heating
5 AHU with cooling coil
6 District cooling
7 Cold water storage tank
Figure 8 System layout of the district cooling system.
The cooling capacity of the district cooling transfer station was assumed to be 200 kW for
Stockholm and Tampere, 250 kW for London and Berlin and 300 kW for Athens and
Zaragoza. The heating capacity of the district heating transfer station was set to be 400 kW
for Stockholm and Tampere, 300 kW for London and Berlin and 200 kW for Athens and
Zaragoza. The storage tanks for hot and cold water have a water capacity of 10.4 m³.
The pump between components 5 and 7 is activated if the indoor air temperature exceed the
set point temperature for cooling by 0.1 K. The district cooling and all the other connected
components that are required to supply start to operate if the temperature of the top layer in
the cold water tank exceeds 10 °C. The system stops operating if the required indoor
temperature is equal to the cooling set point temperature and the cold water tank is fully
charged, meaning that the bottom temperature reaches 6 °C.
21
2.4.2.4 Solar thermal assisted absorption chiller
This section provides information on simulation input data and the functionality of the
refrigeration system based on the solar thermal assisted absorption chiller for each of the
assessed climate and location.
The system consists of three different hydronic cycles, one each for heating and cooling and
solar thermal collectors, which are separated. However, the heating tank (3) is indirectly
connected to the chiller (6). The solar thermal collectors (9) are connected to a solar energy
buffer tank (10) by a heat exchanger. The buffer tank is then directly connected to the central
hot water tank (3). The heating demand is met by radiators (2) that are fed by a district heating
system (4). In order to decrease the required system size, a hot water tank (3) is installed
between the radiators and the energy source. All the parameters connected to heat supply in
terms of space heating will not be considered later in the LCC analysis, as it is not relevant
for the purpose of this study. The cooling system consists of the main absorption chiller unit
(6), an outdoor cooling tower (8) and a cold water storage tank (7) to reduce the required
system size. The cooling demand is covered by the cooling coils of the building’s AHUs (5).
Table 21 List of components in the system layout of the solar thermal assisted absorption
chiller of Figure 9.
Component Description
1 Building
2 Radiators for heat supply
3 Hot water storage tank
4 District heating
5 AHU with cooling coil
6 District cooling
7 Cold water storage tank
8 Heat sink for re-cooling
9 Solar collector field
10 Solar energy storage tank
The main components are the same as mentioned in Section 2.4.2.2. The used solar collector
field consists of evacuated tube collectors with a specific aperture area of 2.1 m² per collector
and a total number of 50, 100 or 150 collectors, depending on the simulated case. The used
solar energy storage tank has a volume of 5.65 m³ for 50 collectors and 8.5 m³ for 100 and
150 collectors. The solar collectors are investigated with two different tilt-angles in order to
ensure a close-to-optimum solar fraction for the cooling systems. It has to be pointed out
again that the solar fraction does not include the energy that could potentially be used for
additional space heating purposes in the winter, therefore only the useful energy for cooling
is addressed and used in the LCC calculations in Section 2.5. The investigated tilt-angles are
60 and 45 degrees for Stockholm and Tampere, 50 and 35 degrees for London and Berlin
and 22 and 37 degrees for Athens and Zaragoza. The azimuth angle of the collector field was
180 degrees for each location. The steeper angles are chosen, since the angle for the
maximum solar output of a system equals the degree of latitude of a certain location. The
22
lower angles are chosen, since the investigated systems are only assessed during summer
months when the sun has higher solar angles.
Figure 9 System layout of the solar thermal assisted absorption chiller.
The basic functionality is the same as described in Section 2.4.2.2. The pump between
components 9 and 10 starts operating if the collector temperature exceeds the temperature at
the top of the heat exchanger in component 10 by 6 K and stops operating if the temperature
has reached equilibrium. The pump connecting the components 10 and 3 starts operating
when the top layer temperature in tank 10 exceeds the tank temperature in the corresponding
height of component 3 by 2 K and stops if the temperatures reached equilibrium.
2.4.2.5 Photovoltaic assisted vapor compression chiller
This section provides information on simulation input data and the functionality of the
refrigeration system based on the photovoltaic assisted vapor compression chiller for each of
the assessed climate and location.
The main components are the same as mentioned in chapter 2.4.2.1. The used PV modules
(9) have a nominal efficiency of 15.6 % and a specific cell area of 1.63 m² per module. It was
simulated with a varying row-spacing of 1.5 m and 2 m, resulting in a total number of 135 or
162 modules, respectively. Besides this, each location was simulated with two different tilt-
angles, in order to ensure a close-to-optimum situation for the assessed systems. The azimuth
and tilt-angles of the PV modules are identical to the ones described in Section 2.4.2.4. The
simulated roof layout and the placement of the PV modules can be seen in Appendix 2.
23
Table 22 List of components in the system layout of the photovoltaic assisted vapor
compression chiller of Figure 10.
Component Description
1 Building
2 Radiators for heat supply
3 Hot water storage tank
4 District heating
5 AHU with cooling coil
6 Vapor compression chiller
7 Cold water storage tank
8 Heat sink for re-cooling
9 PV module field
10 Electricity grid
11 Internal electric appliances
The internal electric appliances (11) are required to run the simulation and measure only the
energy required for cooling related appliances. Therefore, the electric energy required for
lighting and other office supply is not included in the energy simulations. The functionality
of the system is identical to the one described in Section 2.4.2.1.
Figure 10 System layout of the photovoltaic assisted vapor compression chiller.
2.5 LCC analysis
Based on the energy results from different cooling systems, a detailed life-cycle cost (LCC)
analysis was performed, also considering energy-market specific parameters. This section
provides detailed information on all the relevant parameters that were used in the comparison,
as well as in a following sensitivity analysis. The whole LCC analysis was carried out in
24
“Microsoft Excel” (Microsoft, 2015), using hand calculations based on the net present value
method.
The projected lifetime for each single cooling system was assumed to be 25 years. The
formulas that were used in the LCC analysis are listed in Equations 1-3.
NPV = 𝐴 [
(1 + 𝑖)𝑁 − 1
𝑖(1 + 𝑖)𝑁]
(1)
The NPV formula for single equal payments (Eq. 1) was used for all annual payments that
are not associated with a certain growth rate. These payments consist of annual connection
fees to energy supply companies as well as material and labor costs for maintenance.
NPV = 𝐴1 [1 − (1 + 𝑔)𝑁(1 + 𝑖)−𝑁
𝑖 − 𝑔]
(2)
The NPV formula for gradient series (Eq. 2) was used for annual payments that are associated
with a certain growth rate. These payments consist of the annual costs for electricity, district
heating and district cooling as well as the operating costs for electrical components such as
cooling towers or pumps.
𝐴1 = 𝐴0(1 + 𝑖) (3)
The formula for a single compounded payment (Eq. 3) was used for determining the energy
costs after one year in order to calculate the NPV for each system in Eq.2, as it was assumed
that the energy costs occur at the end of each month.
Information on local energy prices, energy regulations and market developments were either
obtained from the local energy supply companies or statistical data from the European
Commission. However, it has to be considered that the collected data underlies certain
limitations, which might have a great impact on the final outcome of the LCC analysis. A list
of the most important limitations and assumptions can be seen below:
- Some of the data used for determining the annual energy costs or development rates
was outdated and from times prior to the global financial crisis in 2008. However,
this factor will partly be considered in the sensitivity analysis in Section 2.5.2.
- Currently, there is no infrastructure for district heating in the city of Athens.
Therefore, the energy prices from the district heating network in the city of
Ptolemaida (D.H.C.P., 2011) in the northern part of Greece were used instead.
- Due to local laws and regulations in Germany, Greece and United Kingdom, energy
supply companies are not required to publish information on their energy prices and
price policies. Therefore, data that could not have been collected from the local
25
suppliers was created by analyzing statistical data and weighing it with existing data
from the other energy markets, where data was available. (European Commission,
2015; Jan-Olof Dalenbäck, 2012).
A data sheet with the relevant material costs and specific installation time per unit can be
found in Appendix 4. The annual maintenance hours of the systems were assumed to be 32
man hours per year. The annual material costs for maintenance were assumed to be 1 % of
the initial system costs.
2.5.1 LCC analysis based on recent market developments and energy policies
This section provides important information on the input data for the LCC analysis based on
recent market developments and energy policies. Figure 11 shows the average prices for
electricity, district heating and district cooling as well as the country specific PV feed-in
tariffs for each location. The energy prices were either obtained from local energy supply
companies or from statistical data collected by the European Commission.
Table 23 describes the energy price relations between the main energy sources electricity,
district heating and district cooling in each location. Figure 12 displays the trend and the
projected development of the most important parameters for an energy related LCC analysis
in the investigated energy markets. The used price growth and interest rates are real rates,
including the effect of inflation.
Table 23 Price relations between the main energy sources for the investigated locations.
Electricity District heating District cooling
Stockholm 1 0.52 0.31
Tampere 1 0.51 0.26
London 1 0.11 0.07
Berlin 1 0.29 0.18
Athens 1 0.24 0.18
Zaragoza 1 0.19 0.14
The average labor costs for each country and location was obtained from the European
Commission (European Commission, Eurostats, 2015). The considered costs are 246 SEK/h
for Stockholm, 298 SEK/h for Tampere, 206 SEK/h for London, 291 SEK/h for Berlin, 135
SEK/h for Athens and 197 SEK/h for Zaragoza, respectively. The material costs for technical
components such as AHU, piping, pumps, chillers, etc. was assumed to be constant
throughout the European Union. This was confirmed by communication with several
contacts in the relevant industry. The used purchasing prices as well as the installation costs
can be seen in Appendix A4-1.
26
Figure 11 PV feed-in tariffs and average annual prices for electricity, district heating and district
cooling for the investigated locations.
Figure 12 Real development of inflation rate, interest rate and electricity and district energy
prices in the investigated European energy markets.
2.5.2 Sensitivity analysis
The purpose of the sensitivity analysis in this section is to investigate the impact of changing
energy markets, energy policies as well as financial and economic situation on the NPVs of
the different systems. Therefore, three different scenarios have been assessed and compared
to the initial NPVs of the different systems.
Looking at Figure 12, it appears that the European growth rates for energy purchasing prices
for electricity and district energy range respectively between -6 % and +8 % and -5 % and
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Stockholm Tampere London Berlin Athens Zaragoza
Ener
gy c
ost
s (S
EK/k
Wh
)
Electricity District heating District cooling PV feed-in tariff
-6%
-4%
-2%
0%
2%
4%
6%
8%
Stockholm Tampere London Berlin Athens Zaragoza
Rat
es (
%)
Inflation Electricity growth rate District energy growth rate Interests
27
+4 % per year, respectively. Simultaneously, the interest rates, as well as labor costs vary
significantly in different European countries, mainly due to the latest development of the
European economy and the financial crises.
2.5.2.1 Scenario I
In the first sensitivity analysis, the price growth rates for electricity, district heating and
district cooling were standardized in each location, with a growth rate of +2.5 % for
electricity and +0 % for district energy, respectively. This particular scenario might occur
with an increased level of financial stability and an increased amount of available CHP and
DHC facilities and network sizes, which allow cheaper operation conditions for the energy
supply companies.
2.5.2.2 Scenario II
In the second sensitivity analysis the interest rates in each country were standardized,
additionally to the parameters in the first sensitivity analysis. The interest rate was set to be
+2 %. This scenario might occur after an extended period of higher economic stability and
an increased level of trust in the European financial market.
2.5.2.3 Scenario III
In the third sensitivity analysis, the PV feed-in tariffs and labor costs were modified in
addition to the parameters in scenario I and II. The PV feed-in tariffs were assumed to
represent a lower subsidized PV market, as it is already the case in Germany. Therefore the
ratio between the electricity purchasing price and the feed-in tariffs for Berlin was
determined and applied to the other locations. The resulting feed-in tariffs are 0.79 SEK/kWh
for Stockholm, 0.86 SEK/kWh for Tampere, 1.03 SEK/kWh for London, 1.01 SEK/kWh for
Athens and 0.96 SEK/kWh for Zaragoza, while the tariff for Berlin remains the same as
before. Besides the change in feed-in tariffs, the average labor costs were set to be at least
200 SEK/h for each location. This scenario might occur with a long term level of financial
stability in the European Union, in addition to an increased level of economic wealth as well
as a higher saturated PV market. However, this parameter only affects the locations Athens
and Zaragoza.
28
29
3 Results
3.1 Climates and locations
The simulated cooling loads for the different locations can be seen in Table 24. The climatic
diagram of the mean outdoor dry-bulb temperatures on a monthly basis for the chosen
locations can be seen in Figure 13.
Looking at the results in Table 24 and Figure 13, the temperature buffer effect of a coastal
influence is apparent, also indicated on average lower cooling loads in each climate zone.
The chosen representative locations for each climate zone that are used in the upcoming
chapters are highlighted in Table 24.
Table 24 Cooling loads for the locations analyzed in the parametric study on representative
climates.
Coastal Continental
Climate zone Location Cooling load
(kW) Location
Cooling load
(kW)
Cold Reykjavik
Stockholm
28.19
37.42
Kiruna
Tampere
30.14
36.90
Moderate
Copenhagen
Amsterdam
London
40.45
44.43
43.63
Berlin
Vienna
Kiev
44.63
50.41
47.01
Hot
Lisbon
Rome
Athens
49.38
49.51
54.22
Ankara
Seville
Zaragoza
55.91
58.68
52.91
Figure 13 Monthly mean outdoor dry-bulb temperatures for each chosen location.
-10
-5
0
5
10
15
20
25
30
Tem
per
atu
re (
°C)
Stockholm Tampere London Berlin Athens Zaragoza
30
A decisive factor that influenced the choice of the final representative climates was the
availability of the required infrastructure, such as district heating and district cooling systems
at the studied locations. This factor would have a significant impact on the accuracy of this
research project, as the actual energy prices from the local energy supply companies will be
used later for the final LCC analysis. However, it has to be mentioned that there is not district
heating available in Athens. The solution to this problem is mentioned in the limitation in
Section 2.5
3.2 Solar access analysis
Figure 14 displays the annual solar irradiation and therefore the potential for implementing
solar energy systems on the roof as well as on the south and east façade of the building for
each climate zone. Looking at Figure 14 it can be said that the rooftop is more or less
unshaded. However, for areas close to the building’s railing and the AHU room in the center
of the roof, this assumption is not valid. Yet, in case of an installation of solar energy systems
on the roof, a certain walking and maintenance area is required which is partly assumed to
be located in these temporarily shaded areas. Placing elements of solar energy systems on
the surrounding vertical facades is less profitable, as the average incident solar radiation is
lower compared to the roof. The façade elements also contain a great amount of window
area, possibly making the implementation more complex and expensive. Therefore, the
façade is not considered in further investigations.
A diagram of the annual incident radiation on a horizontal surface for each chosen location
can be seen in Figure 15. Looking at Figure 15 and Figure 16, it can be seen that the annual
irradiation on a horizontal surface increases with a more southern latitude. However, the
locations in moderate climates do not show a significant difference in annual radiation in
relation to the cold climates.
Figure 14 Annual solar radiation on the building facades in the cold (left), moderate (center)
and hot (right) climate zone.
The irradiation levels range from approximately 1,250 kWh/(m²-year) in the northern
locations to approximately 2,200 kWh/(m²-year) in the Mediterranean climate zones. This
fact suggests the assumption that refrigeration principles assisted by solar energy might be
more profitable in the south compared to the north as there is a greater solar potential.
31
Figure 15 Annual radiation on a horizontal surface for each location.
Figure 16 European map of annual horizontal solar irradiation per area. (JRC European
Commission, 2006)
0
500
1000
1500
2000
2500
Stockholm Tampere London Berlin Athens Zaragoza
An
nu
al r
adia
tio
n
(kW
h/m
²-a)
32
3.3 Energy simulations
Table 25 and Figure 17 present an overview of the main energy key figures for the open-
office layout, obtained from the annual energy simulations.
Table 25 Simulated energy key figures for the open-office layout in “DesignBuilder”.
Location Heating demand
(kWh/m²-a)
Peak heating
load (W/m²)
Cooling demand
(kWh/m²-a)
Peak cooling
load (W/m²)
Stockholm 23.7 51.0 6.7 27.8
Tampere 31.8 65.1 3.7 27.6
London 32.9 39.7 6.9 32.7
Berlin 42.0 52.3 10.8 35.3
Athens 11.3 32.5 44.6 42.6
Zaragoza 20.0 39.4 21.9 43.3
Figure 17 Energy demand and peak loads for the open-office layout as simulated in
“DesignBuilder”.
Table 26 and Figure 18 display an overview of the main energy key figures for the cell-office
layout, obtained from the annual energy simulations in “DesignBuilder”.
Table 26 Simulated energy key figures for the cell-office layout in ”DesignBuilder”.
Location Heating demand
(kWh/m²-a)
Heating load
(W/m²)
Cooling demand
(kWh/m²-a)
Cooling load
(W/m²)
Stockholm 60.9 65.7 5.6 32.9
Tampere 74.8 78.6 3.3 32.2
London 40.4 47.6 11.8 44.4
Berlin 49.9 61.5 16.0 47.8
Athens 15.0 38.7 56.6 56.1
Zaragoza 26.3 46.9 30.9 57.9
0
50
100
150
200
250
300
350
400
450
500
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
Stockholm Tampere London Berlin Athens ZaragozaP
eak
load
(kW
)
Ener
gy d
eman
d (
kWh
)
Heating Demand Cooling Demand Heating load Cooling load
33
Figure 18 Energy demands and peak loads for the cell-office layout as simulated in
“DesignBuilder”.
Figure 19 shows the difference factor between the assessed energy figures between the cell-
and the open-office building as simulated in “DesignBuilder”. In this graph, a factor of 1.00
represents no difference in the simulated energy values between the two office layouts. In
terms of annual heating energy, the open-office building has a lower demand. One possible
explanation could be that the cell-office building contains more internal thermal mass.
Despite the fact that thermal mass usually benefits a lower heating demand, this effect could
be reversed if the building is unoccupied during nights and weekends when the heating set
point temperature is lowered. This hypothesis is also supported by the presence of lower
heating loads. When looking at the cooling energy key figures, it can be seen that the energy
demand is higher for the open-office building, particularly for the moderate and hot climate
locations. The reason can again be explained with the difference in thermal masses where the
above mentioned effect is reversed due to an accumulation and storage of heat.
In general it can be said that the cooling energy key figures, which are the most important
ones in this particular project, are not significantly different when comparing the open- and
cell-office layout. Therefore it was chosen to only proceed with the data for the open-office
building in this thesis, as the results can be assumed to be rather similar.
0
50
100
150
200
250
300
350
400
450
500
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
Stockholm Tampere London Berlin Athens Zaragoza
Pea
k lo
ad (
kW)
Ener
gy d
eman
d (
kWh
)Heating Demand Cooling Demand Heating load Cooling load
34
Figure 19 Difference of energy key figures between open- and cell-office layout as simulated
in “DesignBuilder”.
3.4 Cooling systems
Figure 20 shows the difference in annual cooling demand for each location as they were
simulated in “DesignBuilder” and “Polysun”. It is apparent that the simulations results vary
between the different tools, however the difference is within a reasonable margin. An
explanation of the occurring differences might be the use of different algorithms, climate
files as well as different and limited building input data. Also, it has to be considered that the
simulations in “DesignBuilder” are based on ideal systems, where Polysun uses more
complex and realistic systems.
Figure 21 to Figure 26 show the simulation results of different systems in the selected
locations. It can be observed that all the different locations indicate the same relative trends
in terms of energy intensity. The vapor compression systems have the lowest annual
consumed energy demands in all the locations. The district cooling systems show the second
lowest consumed energy demand, followed by the absorption based cooling systems. This
trend can be easily explained by the difference in COPs, with 4.5 for the vapor compression
system, 1.0 for the district cooling and 0.75 for the absorption based cooling systems.
Then main difference between the chosen locations is the total secondary energy demand per
year. As it was expected, the locations in the cold climate zones indicate the lowest energy
demand, followed by the locations in the moderate and hot climate zones, where the demand
is increased by a factor of two and four, respectively. This effect can be explained with the
difference in maximum outdoor temperatures and duration of the cooling season per year
between the locations.
Regarding the solar assisted cooling systems, it can be said that the increase of gross aperture
area results in a higher solar fraction, regardless of the installation tilt. However, it can be
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
Stockholm Tampere London Berlin Athens Zaragoza
Dif
fere
nce
fac
tor
Heating demand Cooling demand Heating load Cooling load
35
observed that the optimum inclination type – i.e. flat or steep – is dependent on the location
and solar system type. A more detailed analysis will be presented later in this section.
Figure 20 Annual cooling demands as simulated in “DesignBuilder” and “Polysun”.
Figure 21 Annual energy performance of the investigated refrigeration systems and energy
sources in Stockholm.
0
50,000
100,000
150,000
200,000
250,000
300,000
Stockholm Tampere London Berlin Athens Zaragoza
An
nu
al c
oo
ling
dem
and
(k
Wh
)
DesignBuilder Polysun
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
Pu
rch
ased
en
ergy
(kW
h)
Electricity District cooling District heating Solar collectors PV
* = flat ** = steep
36
Figure 22 Annual energy performance of the investigated refrigeration systems and energy
sources in Tampere.
Figure 23 Annual energy performance of the investigated refrigeration systems and energy
sources in London.
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
Pu
rch
ased
en
ergy
(kW
h)
Electricity District cooling District heating Solar collectors PV
* = flat** = steep
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
Pu
rch
ased
en
ergy
(kW
h)
Electricity District cooling District heating Solar collectors PV
37
Figure 24 Annual energy performance of the investigated refrigeration systems and energy
sources in Berlin.
Figure 25 Annual energy performance of the investigated refrigeration systems and energy
sources in Athens. The scale of the y-axis is different compared to the previous
locations.
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
Pu
rch
ased
en
ergy
(kW
h)
Electricity District cooling District heating Solar collectors PV
0
100,000
200,000
300,000
400,000
500,000
600,000
Pu
rch
ased
en
ergy
(kW
h)
Electricity District cooling District heating Solar collectors PV
38
Figure 26 Annual energy performance of the investigated refrigeration systems and energy
sources in Zaragoza. The scale of the y-axis is different compared to the previous
locations.
3.4.1 System- and location-dependent solar fraction
This section describes the optimum installation in terms of solar fraction, depending on
system type and location. Figure 27 and Figure 28 show the solar fractions obtained from
“Polysun” for the systems described in Section 2.4.2.4 and 2.4.2.5 for each considered
location. Looking at the results in Figure 27 it is obvious that the solar fraction increases with
an increasing collector field area. However, it has to be mentioned that the increase does not
follow a linear trend, as the solar fractions with systems consisting of 150 collectors is
considerably smaller than three times of the systems consisting only of 50 collectors.
By taking a closer look at the graphs, it can also be observed that the systems with a flat
installation tilt show a higher solar fraction in cold climates, while systems with a steep tilt
have a slightly higher solar fraction in hot climates. One possible explanation could lie in the
solar paths of the different locations. In northern locations, the solar height is much lower,
but the range of solar azimuth angles is much wider. Hence, a flat installation might allow
more solar radiation in time throughout summer months, since the collector does not cause
mutual shading on its own aperture area. In contrast to that, in the southern locations where
the solar paths show opposite characteristics, a steeper installation might be more beneficial
with a smaller incident angle for a relatively shorter amount of time during summer months.
From Figure 28, it is also noticeable that the solar fractions for the solar thermal assisted
systems are higher for colder climate zones that for warmer ones. This effect can be easily
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
Pu
rch
ased
en
ergy
(kW
h)
Electricity District cooling District heating Solar collectors PV
39
explained with the data obtained in Chapter 3, particularly Figure 15 and Table 24. When the
solar radiation in the southern locations is increased by a factor of approximately two, the
annual cooling demand increases by a factor of approximately four, resulting in higher solar
fractions in the north compared to the south.
Figure 27 Solar thermal fractions for different system layouts in each location.
Looking at the results in Figure 28, it is obvious that the solar fraction is higher with a reduced
row-spacing of the modules in each location, as more modules can be installed on the roof.
The difference in installed PV modules between flat and steep installation and the used layout
of the PV systems can be seen in Appendix 2. The graph in Figure 28 also indicates that,
unlike solar thermal collectors, it is more beneficial to install the PV modules with a steeper
tilt in the colder climates. A more beneficial steeper tilt for the PV can be explained with the
fact that the PV cell temperature is lowered. It is known that PV modules show a lower output
with higher cell temperature, due to a higher induced electrical resistance inside the cells.
The solar fraction for the PV modules is also higher for colder climates than for warmer
climates, due to same reasons as for solar thermal collectors. Generally, it can be observed
that in cold climates, the solar fraction reaches a value of more than 200 % in cold climates
when only used during for cooling during months where cooling demand occurs.
Only the solar energy systems that proved to be the most beneficial in terms of energy output
for each location will be investigated further in the LCC calculations. These systems are
listed in Table 27.
Table 27 Optimum installation layout for each solar energy system depending on location.
Location 50 collectors 100
collectors
150
collectors
PV, 2 m
spacing
PV, 1.5 m
spacing
Stockholm flat flat flat steep steep
Tampere flat flat flat steep steep
London flat flat flat steep steep
Berlin flat flat flat steep steep
Athens steep steep steep flat flat
Zaragoza steep steep steep flat Flat
0%
10%
20%
30%
40%
50%
60%
Sorption, 50coll., flat
Sorption, 100coll., flat
Sorption, 150coll., flat
Sorption, 50coll., steep
Sorption, 100coll., steep
Sorption, 150coll., steep
Sola
r fr
acti
on
(%
)
Stockholm Tampere London Berlin Athens Zaragoza
40
Figure 28 Solar fraction of PV modules for different system layouts based on each location.
3.5 LCC analysis
This section provides LCC analysis results, focusing on NPVs of all the systems after 25
years and recent energy market development data. Besides this, this section also presents
results from various sensitivity analyses that were carried out.
3.5.1 LCC analysis based on recent market developments and energy policies
Looking at the graph of Figure 29, it is apparent that the energy costs for PV assisted vapor
compression systems are the lowest for each location, followed by the district heating driven
absorption system. A cooling system based on district cooling is on average the most
expensive in terms of energy costs according to this graph. However, it has to be considered
that the building is assumed to already have an existing connection to the electricity grid and
district heating, as they are required even for purposes other than cooling. Therefore no
annual connection fees are considered for these systems. This, however, does not apply for
the case of a connection to a district cooling network. Also, it is obvious that the energy costs
for solar assisted technologies are lower, since less additional energy has to be bought from
the electricity or district heating grid. Worth mentioning is also the fact that solar thermal
systems do not reduce the energy costs significantly in any case, where on the other hand PV
assisted systems allow a greater saving potential in any of the assessed locations. In the
locations Stockholm, Tampere and London, these systems even allow a negative energy bill
if the system is only used for cooling purposes.
0%
50%
100%
150%
200%
250%
PV, 2m spacing, flat PV, 2m spacing, steep PV, 1.5m spacing, flat PV, 1.5m spacing,steep
Sola
r fr
acti
on
(%
)Stockholm Tampere London Berlin Athens Zaragoza
41
Figure 29 Annual costs for each assessed cooling system in each location based on recent
market developments and energy policies.
Figure 30 to Figure 35 show the accumulated life-cycle costs for 25 years of each considered
system in the selected locations.
The graph of Figure 30 shows that the vapor compression cooling system has by far the
lowest costs after 25 years for Stockholm. This is mainly due to the low electricity prices and
the negative growth rate of electricity in Sweden, but also due to the low demand of cooling
energy and the low initial system costs. The second cheapest option appears to be the district
heating driven absorption systems. What is interesting to see is that solar assisted cooling
systems do not break even in Sweden, since the energy savings do not make up for the high
installation costs of either the solar thermal collectors or PV modules. For solar thermal
collectors it can be said that the district heating prices are rather low in Sweden, particularly
during the summer months when most of the cooling demand occurs. Looking at the graphs,
it is also noticeable that the district cooling curve shows the steepest gradient and results with
the third highest NPV after 25 years, even though the initial installation cost is the cheapest
and the location specific cooling demand is rather low. However, this effect can be explained
by the fact that the annual costs for district cooling energy account for only about 25 % of
the total costs, while the biggest share comes from the annual connection fee.
Looking at the graph of Figure 31, it can be seen that for Tampere, the vapor compression
system has the lowest NPV after the projected lifetime. As for Stockholm, this can be
explained with low prices and negative growth rate for electricity prices in Finland. However,
this effect is less developed compared to Sweden, thus resulting in a smaller difference
between the vapor compression system and the second cheapest option, which in this case is
district cooling. The district cooling system shows the lowest initial installation costs again,
but because of lower growth rates, the vapor compression system starts to break even after
the sixteenth year. Again, the solar assisted cooling systems do not break even due to the
high installation costs compared to the small amount of annual cooling demand.
-25,000
25,000
75,000
125,000
175,000
225,000
275,000
325,000
Stockholm Tampere London Berlin Athens Zaragoza
Ener
gy c
ost
s (S
EK/y
ear)
Vapor compression Sorption District cooling 50 collectors
100 collectors 150 collectors PV 2m spacing PV 1.5m spacing
42
For London, unlike previous locations, a different trend is observed when looking at Figure
32. This can be explained based on a completely different market situation. Additionally, the
annual cooling energy is higher, leading to a more significant impact of the annual energy
costs throughout a system’s life cycle. It can be observed that the PV assisted vapor
compression chiller system with 1.5 meter row-spacing proofs to be the cheapest after 25
years, followed by district cooling, the district heating driven absorption chiller system and
the conventional vapor compression system. However, all of the systems only show minor
differences in their net present value. It is interesting to see that the trend of the PV assisted
vapor compression systems, as they show decreasing accumulated costs after the assessed
life-span. This can be explained through the rather high electricity purchasing prices in
London and a negative electricity bill at the end of each year. Another interesting thing to
see for this location is that the district heating driven absorption system is relatively cheap.
This is probably due the relatively low purchasing price of district heating energy in
combination with a negative price growth rate for this particular energy source. The solar
thermal systems, however, do not break even again when they are directly compared to the
district heating driven absorption system.
The NPV results for the different system types in Berlin show a rather simple trend according
to Figure 33, with district cooling being the most economical solution under the assessed
circumstances. The second most economical option after 25 years can be identified as the
conventional vapor compression system. The district heating driven absorption system is the
third most economical solution. Looking at the curves, it is also obvious that neither of the
investigated solar energy assisted systems are economically reasonable, mainly due to the
higher initial investment costs. However, it can be observed that from the two different types
of solar assisted cooling technologies, the PV modules seem to be more economical than the
thermal collectors.
When looking at the results from Athens in Figure 34, it can be observed that district cooling
proves to be the most economical throughout the whole lifespan of the systems. This can be
explained both with low initial investment costs and favorable market developments for
thermal forms of energy. However, district heating driven and solar thermal assisted
absorption systems prove to be not cost-efficient due to rather high initial costs of the
systems. Additionally to this, the solar fraction of solar assisted cooling systems is rather low
in hot climates due to a constant demand of cooling energy throughout the summer. This is
also the case for PV assisted vapor compression chillers, however the gradient of the
accumulated life-cycle costs is less steep. The reason for this probably lies in the comparably
higher purchasing prices for electricity.
The graphs of Figure 35 for Zaragoza show that the vapor compression system becomes the
most economical option after 9 years. For the projected lifetime of 25 years, district cooling
and the PV assisted vapor compression systems show similar NPVs, with the PVs showing
a less steep gradient and becoming more economical after approximately 22 years. The
reason can be found in the rather high growth rate for district energy prices. Similarly, the
PV assisted systems also become more economical than the absorption system, even though
the installation cost is high. Likewise to the other investigated energy markets, solar thermal
technologies proved to be not cost efficient in terms of cooling.
43
Figure 30 Net present values based on recent market developments and energy policies for the
investigated cooling systems in Stockholm.
Figure 31 Net present values based on recent market developments and energy policies for the
investigated cooling systems in Tampere.
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
44
Figure 32 Net present values based on recent market developments and energy policies for the
investigated cooling systems in London.
Figure 33 Net present values based on recent market developments and energy policies for the
investigated cooling systems in Berlin.
4
5
6
7
8
9
10
11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
4
5
6
7
8
9
10
11
12
13
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption
District cooling Sorption, 50 collectors
Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
45
Figure 34 Net present values based on recent market developments and energy policies for the
investigated cooling systems in Athens.
Figure 35 Net present values based on recent market developments and energy policies for the
investigated cooling systems in Zaragoza.
6
7
8
9
10
11
12
13
14
15
16
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
6
7
8
9
10
11
12
13
14
15
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
46
3.5.2 Sensitivity analysis
In this section, the results from various sensitivity analyses are presented. Different scenarios
and the relevant input data for each analysis have been previously discussed in Section 2.5.2.
3.5.2.1 Scenario I
As mentioned in Section 2.5.2.1, in this scenario the price growth rates for electricity, district
heating and district cooling have been standardized for each location. Figure 36 to Figure 41
show the accumulated life-cycle costs for scenario I of each considered system in the selected
locations.
By comparing Figure 30 with Figure 36 for Stockholm, no significant change in the net
present values after 25 years can be observed. The reason for this can easily be explained by
the low amount of annual cooling demand for the different systems.
By comparing Figure 31 with Figure 37 for Tampere, no significant difference can be
observed, likewise to the previous assessed location. One alteration that is apparent is that
the breakeven point for conventional vapor compression systems shifts from approximately
16 to 19 years, which can be explained by the different price growth rate for electricity. Again
the reason for the similar life cycle costs and the trends compared the first LCC analysis can
be found in the low amount of annual cooling demand in this type of climate.
By comparing Figure 32 with Figure 38 for London, the most obvious difference is the
general trend of the various systems which became more linear due to an average energy
price growth rate close to the interest rate. Besides this change of trend, the main difference
in this sensitivity analysis is the fact that the vapor compression system became most
economical option, followed by the district heating and cooling based systems. The reason
for this is the decrease of the electricity price growth rate from over +8 % to +2 %. This
effect is also responsible for the change of trends of the NPV curves for the PV modules.
Similar to the sensitivity analysis scenario I for London, the gradient of the NPV curves for
Berlin in Figure 39 becomes almost linear. When comparing Figure 33 and Figure 39, it can
be observed that the vapor compression system indicates a breakeven point of approximately
14 years compared to the district cooling network. All the solar systems in this particular
location remain not cost efficient with changing energy price growth rates, compared to the
non-solar assisted systems.
While comparing Figure 34 to Figure 40 for Athens, it is apparent that due to the change of
growth rates, all system show a lower NPV after 25 years for scenario I. However, no
breakeven point is reached when comparing the two most economical solutions, district
cooling and the conventional vapor compression system, even though they approximate each
other throughout the 25 years, showing no significant difference in the projected life cycle
costs after 25 years. Both the heat operated and solar assisted cooling systems remain vastly
cost-inefficient.
47
Comparing Figure 35 with Figure 41 for Zaragoza, it can be noticed that the differences
between the two scenarios do not vary significantly. The main difference is that the heat
operated system in this particular scenario has a lower NPV after the projected lifetime. This
can be attributed to the lower growth rates of the district energy prices compared to the
electricity prices. Yet, it can be said that the vapor compression system remains the cheapest.
Figure 36 Net present values based on scenario I for the investigated cooling systems in
Stockholm.
Figure 37 Net present values based on scenario I for the investigated cooling systems in
Tampere.
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
48
Figure 38 Net present values based on scenario I for the investigated cooling systems in
London.
Figure 39 Net present values based on scenario I for the investigated cooling systems in
Berlin.
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
4
5
6
7
8
9
10
11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
49
Figure 40 Net present values based on scenario I for the investigated cooling systems in
Athens.
Figure 41 Net present values based on scenario I for the investigated cooling systems in
Zaragoza.
6
7
8
9
10
11
12
13
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
6
7
8
9
10
11
12
13
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
50
3.5.2.2 Scenario II
As mentioned in Section 2.5.2.2, in this sensitivity analysis the interest rates for each
considered location were standardized, additionally to the parameters in the first sensitivity
analysis. Figure 42 to Figure 47 show the accumulated life-cycle costs for scenario II of each
considered system in the selected locations.
By comparing Figure 36 with Figure 42 for Stockholm, it is apparent that the change of
interest rates from 1.3 to 2.5 % causes no drastic change in the outcome of the results.
However, some minor details can be observed, such as the decrease of the maximum and
minimum NPVs or the trend of the district cooling curve, which shows a less steep incline
and becoming the third most economical solution.
By comparing Figure 37 with Figure 43 for Tampere, it is apparent that again the change of
interest rates from 1.0 to 2.5 % causes no drastic change in the outcome of the results.
However, some minor details can be observed, such as the general decrease of the maximum
and minimum NPVs or the trend of the absorption based system curves, which show a less
steep incline. Also, the breakeven point for the vapor compression system shifts from
approximately 18 years to 21 years.
By comparing Figure 38 with Figure 44 for London, it is apparent that the change of interest
rates from 1.9 to 2.5 % basically causes no change in the outcome of the results.
Unlike the other investigated locations in the second sensitivity analysis, Berlin shows a
greater difference in the NPVs for scenario II, which can be observed when comparing Figure
39 with Figure 45. This is due to the fact that the initial interest rates change rather drastically
from 0.8 to 2.5 %, causing on average lower NPVs after 25 years. Also, the breakeven point
for a conventional vapor compression system shifts from 14 years to 18 years, compared to
the district cooling system.
Among all locations, the biggest difference of scenario II can be spotted for Athens when
comparing Figure 40 with Figure 46. This is due to the fact that Athens is the only location
where the interest rate is lowered, from the initial 7.9 to 2.5 %, causing a drastic change in
the NPVs after 25 years. In this particular scenario, the NPVs rise in a range of roughly 3
million SEK. In addition to this, the vapor compression system now shows a breakeven time
of 13 years compared to district cooling. However, the final difference of NPVs between
these two systems after 25 years is rather insignificant.
By comparing Figure 41 with Figure 47 for Zaragoza, it can be seen that the results do not
indicate any major changes, which can be easily explained by the fact that the interest rate
increase from 2.1 to 2.5 % is rather insignificant.
51
Figure 42 Net present values based on scenario II for the investigated cooling systems in
Stockholm.
Figure 43 Net present values based on scenario II for the investigated cooling systems in
Tampere.
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
52
Figure 44 Net present values based on scenario II for the investigated cooling systems in
London.
Figure 45 Net present values based on scenario II for the investigated cooling systems in
Berlin.
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
4
5
6
7
8
9
10
11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
53
Figure 46 Net present values based on scenario II for the investigated cooling systems in
Athens.
Figure 47 Net present values based on scenario II for the investigated cooling systems in
Zaragoza.
6
8
10
12
14
16
18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
6
7
8
9
10
11
12
13
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*1
06)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
54
3.5.2.3 Scenario III
As mentioned in Section 2.5.2.3, in this scenario the PV feed-in tariffs and labor costs were
modified in addition to the parameters in scenario I and II. Figure 48 to Figure 53 show the
accumulated life-cycle costs for scenario III of each considered system in the selected
locations.
While comparing Figure 48 to Figure 53 for scenario III to the respective graphs of Figure
42 to Figure 47 for all selected locations, it can be concluded that neither feed-in tariffs for
photovoltaic systems nor the increase of labor costs have any significant impact on the NPVs
after 25 years of projected lifetime. This is despite the fact that PV-assisted vapor
compression systems become more expensive throughout the life-cycle when compared to
the other scenarios. However, this does not affect the results in a major way, as in neither of
the locations, solar assisted systems proof to be cost-efficient. In case of feed-in tariffs, it can
be analyzed that the times of supply are almost directly proportional to the times of demand
for cooling energy. This means that most of the energy that is generated by the PV modules,
is directly used to power the cooling appliances. Therefore, only a fraction of the generated
energy can be sold to the public grid. In terms of the labor costs, it can be concluded that the
percentage of the labor costs accounts only for a small share in both the installation costs and
the annual costs for maintenance.
Figure 48 Net present values based on scenario III for the investigated cooling systems in
Stockholm.
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
55
Figure 49 Net present values based on scenario III for the investigated cooling systems in
Tampere.
Figure 50 Net present values based on scenario III for the investigated cooling systems in
London.
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
56
Figure 51 Net present values based on scenario III for the investigated cooling systems in
Berlin.
Figure 52 Net present values based on scenario III for the investigated cooling systems in
Athens.
4
5
6
7
8
9
10
11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
6
8
10
12
14
16
18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
57
Figure 53 Net present values based on scenario III for the investigated cooling systems in
Zaragoza.
6
7
8
9
10
11
12
13
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Acc
um
ula
ted
co
sts
(SEK
*10
6)
Lifetime (years)
Vapor compression Sorption District cooling
Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors
PV, 2m spacing PV, 1.5m spacing
58
59
4 Discussion
It can be said that from an environmental and sustainability perspective, it is positive that in
half of investigated energy markets, cooling systems based on renewable and more
sustainable forms of energy represent the most cost-efficient cooling solution. These systems
are PV assisted vapor compression system in London and district cooling in Berlin and
Athens. However, even though the conventional vapor compression systems proves to be the
cheapest option in Stockholm, Tampere and Zaragoza, it can be considered environmentally
friendly under certain perspectives. This is due to the fact that particularly the Swedish and
Finnish electricity mix contains a big amount of green energy generated by biomass,
hydropower plants and wind turbines. Though, it has to be considered that both energy
markets also supplies some of its energy by nuclear power plants, which are considered being
harmful to the environment. Additionally, it has to be considered that building a hydro power
plant comes together with a major interference with nature, which in some aspects can also
be considered being not sustainable. Generally though, the economic reasonableness for the
predominant status of vapor compression chillers as the main cooling technology used in
buildings was confirmed. Additionally, the recent development and appearance of district
cooling networks in a lot of European cities was also shown to be economically reasonable.
One parameter that has not been investigated in this research project is the application of heat
sources other than district heating to power the absorption chiller. Alternatives include the
use of natural- or bio-gas, which can be burned locally in conventional gas vessels or a micro
CHP-plant, and allows the cogeneration of thermal and electrical energy. Further research is
needed in order to analyze these options in further detail.
An interesting result of this research is the fact that among the thermally operated systems,
district cooling systems prove to be more cost efficient compared to the absorption chillers,
even though it is the only technology in this research, where rather high connection fees
apply to the energy supply companies in the LCC analysis. The only location that does not
show these characteristics is Stockholm, where the connection fees are much higher
compared to other locations. One possible explanation can be that the annual connection fee
for this location has been researched incorrectly, since the exact pricing policies of the energy
supply companies can be rather ambiguous. In the example of Tampere in Finland, it can be
seen that the magnitude of the seasonal variation of district energy prices is vital for an
absorption chiller to be economically competitive against other technologies. When
comparing the absorption NPV trends for the similar climates Stockholm and Tampere,
which also share the same average purchasing price relations, it can be observed that the
absorption system is significantly higher in Tampere. This is due to the fact that the
purchasing price for district heating is almost 0.20 SEK higher during the summer months in
Finland.
Another interesting finding is the fact that initial installation costs of different cooling system
arrangements account for approximately 40 to 60 % of the total NPV after 25 years.
However, in cold climates where system sizes are rather large compared to the total occurring
cooling demand, the installation costs may account for up to 75 % of the total NPV.
Therefore, it is demonstrated that installation costs play a vital role in determining the cost-
efficiency of a cooling system. It has also been shown that the country specific labor costs
60
do not affect the NPV on a big scale, since the share of these costs is rather small, both in the
initial installation as well as in the running costs.
An unexpected result of this project is that the solar fraction for solar thermal systems does
not have a great significance in the cost-efficiency of a solar thermal assisted cooling system.
In general it is valid to point out that solar thermal assisted cooling systems proved not to be
cost-efficient in any way. The two reasons that can be identified are the high installation costs
for a solar collector field and the fact that district heating is usually cheap during the summer
months. Particularly this factor lowers the impact of the energy savings on the operating costs
significantly. In the course of this project, it has also been shown that the solar fraction of
solar thermal assisted cooling system decreases with the increase of average outdoor
temperature. This finding is rather surprising, but can also be explained easily in this sense
that the useful solar radiation increases by a factor of two from the cold to the hot climate
zones, while the cooling demand increases by a factor of approximately three. Another result
that was not expected in relation to solar assisted cooling systems is that the additional
investment costs of installing more PV modules by allowing a smaller row spacing are easily
recovered within 25 years. As a result, the PV systems with 1.5 m row spacing prove to be
more cost-efficient than the ones with less modules and 2 m row spacing in each
investigation. Therefore it can also be assumed that mutual shading is not causing an issue
with the assessed system layouts. Further research could show that applying even a smaller
row spacing could break even for PV assisted vapor compression systems.
One factor that has to be kept in mind is that the geometry of the building plays an important
role on the energy and cost-efficiency of solar assisted cooling technologies. By replacing
the six-story building in this project by a building with the same floor plan but only three
stories, the solar fraction increases drastically. This leads to the conclusion that twice as much
energy for the installed cooling systems can be generated locally on-site with indicating equal
or less installation costs, due to smaller components.
In addition to row spacing of the PV modules, it has been found that in terms of PV assisted
vapor compression cooling, the quantity of the energy market specific feed-in tariffs account
only for a small share of the NPV. This can be easily explained by the fact that the curve of
the cooling demand follows the same trend as the supply curve from the PV modules.
Therefore, energy is not sold to the grid but directly used instead, making the feed-in tariffs
less influential for this purpose, particularly in locations with a higher cooling demand.
However, it has to be considered that only the useful energy for the cooling supply has been
taken into consideration for all solar assisted cooling technologies. Due to this, the NPV
results obtained in this study may differ from actual potential costs. Speaking in terms of
solar thermal collectors, some of the energy that is generated throughout the year can be
directly used to support the building’s heating and domestic hot water demand. This is
significant to the extent that the purchasing price of district heating is much higher during
winter months, which can then lower the heating bill. However, it also has to be considered
that the useful radiation is much lower during the winter months, which again has a limiting
effect on this particular scenario. The same applies to the NPV of the photovoltaic modules,
as they also generate electricity in times when no cooling is needed. However, electrical
appliances during normal office hours cause a constant electricity demand, which can then
be supplied by the electricity production from PV modules. In order to gain more detailed
results on this particular issue, further investigations that take a building’s energy costs on a
61
more holistic scope into account are required. Additionally it has to be mentioned that
electricity is mostly provided by fossil fuels in southern European countries. Besides this,
electrical powered air-conditioning is widely spread due to rather hot summer months.
Therefore, PV assisted cooling systems can reduce the grid loads significantly while
simultaneously reducing the ecological footprint of the country’s energy generation.
One interesting observation is that the prior mentioned influence of a more continental
climate on the energy demand does not necessarily lead to higher energy costs, as it is
strongly dependent on the current situation of the country’s energy market and prices.
Therefore it can actually be seen that the highest NPVs of all the investigated cooling systems
have been identified in Berlin, where the same cooling system technology is on average 20
% more expensive compared to the second most expensive location Athens. This is even
though the climate is more moderate and the system components are smaller and therefore
cheaper. However, it has to be mentioned that this situation only occurs in the initial LCC
analysis, not when the parameters from the various sensitivity analyses have been applied.
A big issue that this study has confronted is the data and price collection process from
external sources. Many manufacturers are reluctant in terms of publishing market prices for
components as they consider them highly sensitive information in terms of marketing and
sales strategy. This can cause certain problems in terms of determining the correct NPV of
certain systems, particularly since it has been already discovered earlier that the initial
investment costs account for a significant share of the final NPV. Another related issue is
that due to some country specific laws and regulations, energy supply companies are not
required to publish information on their price models for energy and energy transfer. This
issue makes it further complicated to obtain enough revealing data to conduct a valid LCC
analysis. Instead, assumptions based on old available statistical data have to be made, which
may cause a significant error margin in the results of the research, since operating costs have
been found to account for the biggest share of the final NPV of a system. A solution towards
more transparency and customer care can be the compulsive publication of data for the
energy supply companies through European laws. Laws like this would also not interfere
with the sales strategies of local energy suppliers, as they usually have a monopoly on the
energy infrastructure in a city, particularly for district energy. Yet, an interesting observation
is that a more stable economic situation and a higher level of trust in the European financial
market may go hand in hand with significantly lower NPVs for each system and location.
Yet, it is very essential to keep in mind that history has proven that these are highly sensible
economical and financial parameters that either cannot or should not be drastically modified
and influenced by political instruments and institutions.
One point that may have a significant influence on the total energy costs, particular in the hot
climates, is the cooling set point temperature. In this project, the cooling set point temperature
has been assumed to be 25 °C in each climate zone. However, it may be questionable if actual
office buildings in hot climates need to achieve an indoor temperature with these temperature
or if a higher temperature level is acceptable as well. Another point that may cause some
changes in the final results of the NPVs is the use of different software in this project,
particularly the used energy simulation software. Both “DesignBuilder” and “Polysun”
calculate a building’s energy demands based on different algorithms, due to the fact that they
have been programmed for different purposes. Therefore, they both underlie certain
simplifications and limitations as well as require different input data that eventually cannot
62
be obtained from the other software. However, since this thesis project was intended to serve
a more general investigation with the idea to initialize and promote further research on this
topic, a certain error margin based on different energy simulations was considered
acceptable. As it was found out during the energy simulations, the difference between having
a cell-office or open-office floor layout does not make a major difference. It can be expected
that due to the small difference in energy demand and system capacities, the NPVs are likely
not to differ a lot either. However, in order to make a more conclusive statement regarding
this topic, further investigations are necessary.
Figure 54 to Figure 59 present a final overview of all the final NPVs for each investigated
technology, scenario and location. It can be observed that the combination of energy price
growth rates and interest rates have a rather significant impact on the life-cycle costs of a
cooling system. Since electricity is necessary for each system type, the development of this
factor accounts for the biggest share, especially with the vapor compression based systems.
This effect can particularly be seen for the systems in London, Berlin and Zaragoza, where
the NPVs are lower in all scenarios compared to the base case. This is also due to the rather
moderate interest rates in these locations. In contrast to that, the systems in Athens, which
also has a high electricity price growth rate, show a NPV increase in scenario II and II. The
reason for that probably lies in the current situation of the national economy with rather high
interest rates. The northern locations Stockholm and Tampere even have an increase of the
NPV for vapor compression systems due to the negative electricity price growth rate in the
base cases. However, in scenario II and III, this increase is reversed again by increasing the
interest rates, even though the effect is rather insignificant.
Figure 54 Overview of the final NPVs after 25 years in each scenario in Stockholm.
0
2
4
6
8
Base case Scenario I Scenario II Scenario III
NP
V (
SEK
*10
6)
Vapor compression Sorption District cooling Sorption, 50 coll.
Sorption, 100 coll. Sorption, 150 coll. PV, 2m spacing PV 1.5m spacing
63
Figure 55 Overview of the final NPVs after 25 years in each scenario in Tampere.
Figure 56 Overview of the final NPVs after 25 years in each scenario in London.
0
1
2
3
4
5
6
7
8
Base case Scenario I Scenario II Scenario III
NP
V (
SEK
*10
6Vapor compression Sorption District cooling Sorption, 50 coll.
Sorption, 100 coll. Sorption, 150 coll. PV, 2m spacing PV 1.5m spacing
0
2
4
6
8
10
12
Base case Scenario I Scenario II Scenario III
NP
V (
SEK
*10
6)
Vapor compression Sorption District cooling Sorption, 50 coll.
Sorption, 100 coll. Sorption, 150 coll. PV, 2m spacing PV 1.5m spacing
64
Figure 57 Overview of the final NPVs after 25 years in each scenario in Berlin.
Figure 58 Overview of the final NPVs after 25 years in each scenario in Athens.
0
1
2
3
4
5
6
7
8
Base case Scenario I Scenario II Scenario III
NP
V (
SEK
*10
6)
Vapor compression Sorption District cooling Sorption, 50 coll.
Sorption, 100 coll. Sorption, 150 coll. PV, 2m spacing PV 1.5m spacing
0
2
4
6
8
10
12
Base case Scenario I Scenario II Scenario III
NP
V (
SEK
*10
6)
Vapor compression Sorption District cooling Sorption, 50 coll.
Sorption, 100 coll. Sorption, 150 coll. PV, 2m spacing PV 1.5m spacing
65
Figure 59 Overview of the final NPVs after 25 years in each scenario in Zaragoza.
0
2
4
6
8
10
12
14
Base case Scenario I Scenario II Scenario III
NP
V (
SEK
*10
6)
Vapor compression Sorption District cooling Sorption, 50 coll.
Sorption, 100 coll. Sorption, 150 coll. PV, 2m spacing PV 1.5m spacing
66
67
5 Conclusions
It was confirmed that the status of conventional vapor compression chillers as the
main cooling technology in buildings is economically justifiable. Additionally to
this, the fast growth of district cooling networks in European cities in the recent years
was found to be reasonable in terms of life-cycle costs for the consumer.
The correct assessment of a country’s energy market in terms of interest rates and
mainly price growth rates for the supplying energy sources are very important, as
these factors majorly determine the outcome of a LCC analysis, particularly in
climates with a high annual cooling demand.
The introduction of a comprehensive European law, which regulates the obligatory
publication of energy prices for energy supply companies will allow more detailed
research on the efficiencies of different cooling systems. Additionally, this may also
lead to a progressive development of more sustainable technologies or district energy
networks from which energy supply companies may also benefit from.
Operating costs can account for more than 50 % of a technology’s NPV, particularly
in warmer climates. Therefore, energy price relations between different cooling
technologies can be a good and powerful indicator for a preliminary LCC-assessment
of cooling systems without running detailed energy simulations. Labor and
maintenance costs, as well as feed-in tariffs for PV systems do not play a significant
role when determining the NPV of a cooling system.
District heating driven absorption chillers can be effective in countries with high
electricity purchasing prices. However, seasonal energy price variation is a vital
aspect for determining the competitive position of these particular systems.
With an increased level of economic and financial stability in an energy market,
district energy systems, particular district cooling systems tend to become more
financially reasonable.
The building geometry and the related roof-to-conditioned floor area is one of the
biggest influences on the final NPV of a solar assisted energy systems, particularly
for PV assisted vapor compression systems.
PV assisted cooling systems can be economically reasonable, particularly hot
climates. Additionally, adding more PV modules to support vapor compression
cooling systems is directly connected to a decrease of the NPV of a certain system
in each assessed climate zone.
Solar thermal absorption chillers are not economically reasonable in any case, as the
initial costs are too high.
68
69
References
ASHRAE. (2001). International Weather for Energy Calculations (IWEC Weather Files) Users
Manual and CD-ROM. Atlanta.
ASHRAE. (2012, 07). BSR/ASHRAE Addendum b to ANSI/ASHRAE Standard 196-2006. Retrieved
02 24, 2015, from Climatic Data for Building Design Standards:
https://osr.ashrae.org/Public%20Review%20Draft%20Standards%20Lib/169-PR-
draft_2012%2006%2019_v3_chair_approved.pdf
Autodesk Inc. (2015). Revit. Retrieved 05 26, 2015, from http://www.autodesk.com/products/revit-
family/overview
Concerted Action. (2013). Implementing the Energy Performance of Buildings Directive (EPBD) -
Featuring Country Reports 2012. Porto: ADENA.
D.H.C.P. (2011). DH Infrastructure. Retrieved 05 26, 2015, from
http://www.tpt.gr/index.php?option=com_content&view=article&id=57&Itemid=69
Davidson, S. (2015). Grasshopper . Retrieved 05 26, 2015, from http://www.grasshopper3d.com/
DesignBuilder Software Ltd. (2015). DesignBuilder. Retrieved 05 26, 2015, from
http://www.designbuilder.co.uk/
districlima Zaragoza. (2015). Tarifas oficiales Districlima Zaragoza. Retrieved 05 26, 2015, from
http://districlimazaragoza.com/districlimazaragoza/uploads/descargas/Tarifas-districlima-
zaragoza/Tarifas_Marzo_2015.pdf
EDP. (2013). Electricidad, Precios oferta Precio fijo EDP COR desde el 26/01/2015 hasta
25/02/2015. Retrieved 05 26, 2015, from http://www.edpenergia.es/es/negocios/gas-y-
electricidad/precios/mercado-regulado/?provincia=zaragoza
European Comission. (2015, 03 02). Inflationsrate - Jährliche Veränderungsrate (%). Retrieved 05
26, 2015, from
http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=de&pcode=tec00118
&plugin=1
European Commission. (2015). Eurostats. Retrieved 05 26, 2015, from
http://ec.europa.eu/eurostat/statistics-explained/index.php/Energy_price_statistics
European Commission, Eurostats. (2015, 04 21). Wages and labor costs. Retrieved 05 26, 2015,
from http://ec.europa.eu/eurostat/statistics-explained/index.php/Wages_and_labour_costs
Flodberg, K. (2012). Very Low Energy Office Buildings in Sweden - Simulations with low internal
heat gains. Lund: Faculty of Engineering LTH.
Fortum AB. (n.d.). Elpriser. Retrieved 05 25, 2015, from Historiska elpriser:
http://www.fortum.com/countries/se/privat/el/elmarknaden/historiska-
elpriser/pages/default.aspx
Fortum AB. (n.d.). Företag Elnät. Retrieved 05 25, 2015, from Elnätspriser för Stockholm:
http://www.fortum.com/countries/se/SiteCollectionDocuments/Sakr_Sth_150601_d.pdf
Fortum AB. (n.d.). Företag Fjärrkyla. Retrieved 05 25, 2015, from Prisavtal 2014 - Fjärrkyla
Komfort: http://www.fortum.com/countries/se/SiteCollectionDocuments/prisavtal-komfort-
odaterad-april-2014.pdf
Fortum AB. (n.d.). Företag Fjärrvärme. Retrieved 05 25, 2015, from Prisavtal 2015 - Fjärrvärme
Trygg: http://www.fortum.com/countries/se/SiteCollectionDocuments/prisavtal-trygg-
2015.pdf
International Energy Agency. (2009). Energy Policies of IEA Countries, Spain 2009 Review.
OECD/IEA.
International Energy Agency. (2011). Energy Polivies of IEA Countries, Greece 2011 Review.
OECD/IEA.
International Energy Agency. (2012). Energy Policies of IEA Countries, The United Kingdom 2012
Review. OECD/IEA.
International Energy Agency. (2013). Energy Policies of IEA Countries, Finland 2013 Review.
OECD/IEA.
70
International Energy Agency. (2013). Energy Policies of IEA Countries, Germany 2013 Review.
OECD/IEA.
International Energy Agency. (2013). Energy Policies of IEA Countries, Sweden 2013 Review.
OECD/IEA.
Jan-Olof Dalenbäck, S. W. (2012). Market for Solar District Heating. Göteborg: http://www.solar-
district-heating.eu/portals/0/sdh-wp2-d2-3-market-aug2012.pdf.
Javed, S. (2014, 09). Lecture slides: Master Program in Energy-efficient and Environmental
Building Design, Lund University. Life Cycle Costs, 2-3.
JRC European Commision. (2006). Photovoltaic Solar Electricity Potential in European Countries.
Retrieved from http://re.jrc.ec.europa.eu/pvgis/cmaps/eur.htm
Lagios, K. (2015). DIVAforRhino. Retrieved 05 26, 2015, from http://diva4rhino.com/
Microsoft. (2015). Microsoft Office - Excel. Retrieved 05 26, 2015, from
https://products.office.com/en-us/excel
Office of Gas and Electricity Markets. (2015). Feed-in Tariff Generation & Export Payment Rate
Table for Photovoltaic Installations - FIT Year 6 (2015/16). Retrieved 05 26, 2015, from
https://www.ofgem.gov.uk/ofgem-publications/92754/fitpvtarifftablefor1april2015-
amended-pdf
Planning Portal. (2013). Building regulations. Retrieved 02 18, 2015, from Approved document
L2A - Conservation of fuel and power in new buildings other than dwellings:
http://www.planningportal.gov.uk/uploads/br/BR_PDF_AD_L2A_2013.pdf
Poirazis, H. (2005). Office Buildings - Energy Use and Indoor Climate Simulations. Lund: Lund
Institute of Technology.
Public Power Corporation S.A.-Hellas. (n.d.). Κτίρια γραφείων, μεγάλα καταστήματα, μεσαίες
βιοτεχνίες, φούρνοι, κλπ. Retrieved 05 26, 2015, from
https://www.dei.gr/Documents2/TIMOLOGIA/TIMOL25072014/G22EPAGGE.pdf
Robert McNeel & Associates. (2014). Rhinoceros. Retrieved 05 26, 2015, from
https://www.rhino3d.com/en/
Shaper, J. (n.d.). www.absorptionsmaschine.de. Retrieved 05 24, 2015, from
Wirtschaftlichkeitsbetrachtung nach VDI 2067:
http://absorptionsmaschine.de/wirtschaftlichkeitsbetrachtung-der-
absorptionsmaschine/absorptionskaeltemaschine-zur-kaelteerzeugung-.html
SVEBY. (2013, 06 05). Rapporter. Retrieved 02 15, 2015, from Brukarindata Kontor 1.1:
http://www.sveby.org/wp-content/uploads/2013/06/Brukarindata-kontor-version-1.1.pdf
Tampereen Sähkölaitos Kaukolämpö OY. (2014). Kaukojaahdytys_hinnasto_2014_06_01. Tampere.
Retrieved from Kaukojäähdytyksen myyntihinnasto 1.6.2014 alkaen.
Tampereen Sähkölaitos Kaukolämpö OY. (2014, 01 03). SÄHKÖN VERKKOPALVELUHINNASTO.
Retrieved 05 26, 2015, from
https://www.tampereensahkolaitos.fi/sahkoverkkopalvelut/hinnastotjasopimusehdot/Docum
ents/S%C3%A4hk%C3%B6n%20siirtotariffit%2001-01-2014.pdf
Tampereen Sähkölaitos Kaukolämpö OY. (n.d.). Hinnastot ja sopimusehdot. Retrieved 05 25, 2015,
from Kaukolämmön myyntihinnat 1.1.2013 alkaen:
https://www.tampereensahkolaitos.fi/kaukolampojaahdytysjamaakaasu/kaukolampo/hinnast
otjasopimusehdot/Documents/Hinnat_20130101.pdf
Tampereen Sähkölaitos Kaukolämpö OY. (n.d.). Lähisähkö-tarjous yrityksille. Retrieved 05 26,
2015, from
https://www.tampereensahkolaitos.fi/sahkonmyynti/yritysasiakkaatyli63a/lahisahkotarjous/
Sivut/default.aspx#.VWTbyE_tlBd
The Commtech Group. (2003). Achieving the Desired Indoor Climate. Lund: Studentlitteratur.
Trimble Navigation Limited. (2013). SketchUp. Retrieved 05 26, 2015, from
http://www.sketchup.com/
U.S. Department of Energy. (2015, 04 10). EnergyPlus Energy Simulation Software. Retrieved 05
26, 2015, from http://apps1.eere.energy.gov/buildings/energyplus/
71
Vattenfall GmbH. (n.d.). Allgemeiner Preis der Grundversorgung. Retrieved 05 26, 2015, from
https://www.vattenfall.de/ma-vf_de-
apis_landingpage/Download.action?documentID=65ee24c6-9faa-4ebc-9d10-28397c787a75
Vattenfall GmbH. (n.d.). Profi24 Strom für Berlin. Retrieved 05 26, 2015, from
https://www.vattenfall.de/de/geschaeftskunden-strom-profi24.htm
Vela Solaris AG. (2015). Polysun Simulation Software. Retrieved 05 26, 2015, from
http://www.velasolaris.com/english/home.html
Wikells Byggberäkningar AB. (2013). Wikells Sektionsfakta - VVS. Växjo: Elanders.
Wilson, B. (1988). log p-h diagram for R134a. 94(2).
72
A1-1
Appendix 1 – Floor plans, sections and elevations of the assessed reference building
Figure A1-1 Elevation - East
A1-2
Figure A1-2 Elevation - South
Figure A1-3 Floor plan – Ground, open-office
Figure A1-4 Floor plan – Ground, open-office
A1-3
Figure A1-5 Floor plan – Ground, cell-office
Figure A1-6 Floor plan – 3rd floor, cell-office
A2-1
Appendix 2 – PV layout for 2-m and 1.5-m spacing
Figure A2-1 PV layout on the rooftop for 2-m (top) and 1.5-m (bottom) row-spacing
A3-1
Appendix 3 – Monthly energy performance of cooling
systems in Berlin
Figure 60 Vapor compression chiller
Figure 61 District heating driven absorption chiller
0
2000
4000
6000
8000
10000
12000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)
Electricity
0
5000
10000
15000
20000
25000
30000
35000
40000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)
Electricity District heating
A3-2
Figure 62 District cooling
Figure 63 Solar thermal assisted absorption chiller with 50 collector
0
5000
10000
15000
20000
25000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)Electricity District cooling
0
5000
10000
15000
20000
25000
30000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)
Electricity District heating Solar collectors
A3-3
Figure 64 Solar thermal assisted absorption chiller with 100 collectors
Figure 65 Solar thermal assisted absorption chiller with 150 collectors
0
5000
10000
15000
20000
25000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)Electricity District heating Solar collectors
0
5000
10000
15000
20000
25000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)
Electricity District heating Solar collectors
A3-4
Figure 66 Photovoltaic assisted vapor compression chiller with 2-m row-spacing
Figure 67 Photovoltaic assisted vapor compression chiller with 1.5-m row-spacing
0
2000
4000
6000
8000
10000
12000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)Electricity PV Production
0
2000
4000
6000
8000
10000
12000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ener
gy (
kWh
)
Electricity PV Production
A4-1
Appendix 4 – Material costs of the different components
used in the LCC analysis
Table 28 Material and installation costs of the different components used in the LCC analysis.
Climate Material costs incl. VAT Installation time
COMPONENT (SEK/unit) (h/unit)
Pump group all 31,250 8.50
Absorption chiller cold 750,000 50.00
Absorption chiller moderate 800,000 55.00
Absorption chiller hot 830,000 60.00
Vapor compression chiller cold 435,000 16.00
Vapor compression chiller moderate 442,400 18.00
Vapor compression chiller hot 459,200 20.00
District cooling station cold 300,000 100.00
District cooling station moderate 325,000 125.00
District cooling station hot 350,000 150.00
Tank 5.6 m³ all 103,125 10.00
Tank 8.5 m³ all 157,500 12.00
Tank 10.4 m³ all 193,125 14.00
Re-cooling tower all 218,750 16.00
AHU all 350,000 18.00
Evacuated tube collector all 10,000 0.50
PV module all 3,500 0.50
Inverter all 18,750 12.00
Control unit all 3,500 6.00
(SEK/m) (h/m)
Piping for district cooling components cold 699 1.98
Piping for district cooling components moderate 769 1.98
Piping for district cooling components hot 839 1.98
Piping for solar thermal collector piping cold 750 0.64
Piping for solar thermal collector piping moderate 825 0.64
Piping for solar thermal collector piping hot 900 0.64
other piping cold 988 0.70
other piping moderate 1087 0.70
other piping hot 1186 0.70
The data in Table 28 was obtained either directly from the component manufacturers or from
a cost and installation handbook (Wikells Byggberäkningar AB, 2013). This thesis was
written in a time when 1 SEK was equal to approximately 0.10 EUR and 0.12 USD,
respectively.
Dept of Architecture and Built Environment: Division of Energy and Building DesignDept of Building and Environmental Technology: Divisions of Building Physics and Building Services