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

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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.

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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

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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

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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.

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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

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Figure 4 Zone layout of the ground floor (left) and the remaining floors (right) for the cell-

office building in “DesignBuilder”.

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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”.

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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.


(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.


(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

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Table 10 Roof construction details in cold climate from exterior to interior side.


(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

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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.

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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

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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


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.


1 Building



4 District heating


6 Absorption chiller




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



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


refrigeration system based on district cooling for each assessed climate and location.


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.


1 Building



4 District heating


6 District cooling


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



charged, meaning that the bottom temperature reaches 6 °C.

21

2.4.2.4 Solar thermal assisted absorption chiller


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.


1 Building



4 District heating


6 District 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


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.


1 Building



4 District heating


6 Vapor compression chiller



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%


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.

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)


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


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


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


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


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


sources in Tampere.


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)


* = flat** = steep

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

Pu

rch

ased

en

ergy

(kW

h)


37


sources in Berlin.


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)


0

100,000

200,000

300,000

400,000

500,000

600,000

Pu

rch

ased

en

ergy

(kW

h)


38


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)


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, 50coll., steep



Sola

r fr

acti

on

(%

)


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


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.


investigated cooling systems in Tampere.

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Sorption, 50 collectors Sorption, 100 collectors Sorption , 150 collectors

PV, 2m spacing PV, 1.5m spacing

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investigated cooling systems in London.


investigated cooling systems in Berlin.

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District cooling Sorption, 50 collectors

Sorption, 100 collectors Sorption , 150 collectors


45


investigated cooling systems in Athens.


investigated cooling systems in Zaragoza.

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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.


Tampere.

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London.


Berlin.

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Athens.


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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.


Tampere.

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London.


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Athens.


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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.

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Tampere.


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Berlin.


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Zaragoza.

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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

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NP

V (

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*10

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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.

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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.

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Figure 59 Overview of the final NPVs after 25 years in each scenario in Zaragoza.

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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.

69

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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

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Figure 62 District cooling

Figure 63 Solar thermal assisted absorption chiller with 50 collector

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Figure 64 Solar thermal assisted absorption chiller with 100 collectors

Figure 65 Solar thermal assisted absorption chiller with 150 collectors

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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

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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

LCC-OPTIMISED COOLING SYSTEMS - Energy and Building Design

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