Energy optimization without affecting comfort

Transcription

1 Energy optimization without affecting comfort Minimizing the operational costs with an optimized indoor comfort climate Adriaan Woonink Date:

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3 TITLE PAGE Student The Hague University for Applied Sciences Faculty : Technology, Innovation & Society Name & student no. : Adriaan Woonink adriaanwoonink@gmail.com University The Hague University for applied sciences Faculty : Technology, Innovation & Society Supervisor : Ing. Arie van Kampen A.vanKampen@hhs.nl Company Swegon AB Company Supervisor Co-supervisor 1 Co-supervisor 2 Swegon AB : Ing. Petra Vladykova, Ph.D. : Petra.Vladykova@swegon.se : Arch. Markus Kalo, M.Sc. : Markus.Kalo@swegon.se : John Woollett, CEng : John.Woollett@swegon.se Project Energy optimization without affecting comfort Title : Energy optimization without affecting comfort Thesis : Bachelor thesis Location : Kvänum, Sweden Website : / 3

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5 ABSTRACT Despite the fact that the office building in Kvänum is recently build, there are still a lot of possible improvements to optimize the use of the building. With more in-depth research about the consumption and indoor climate a lot of could be saved whilst still maintaining the best possible indoor climate. This means that an evaluation of a building can still be worthwhile even though the building is recently build. The following results have been calculated with dynamic simulation software. A total of 3 different ventilation methods where investigated. These included the combination of constant and demand controlled ventilation systems that are in the current building, a constant ventilation system and a demand controlled ventilation system. A total of 7 simulations were run, to investigate the effect of the different ventilation systems and adaptations to the building. The multifunctional unit proved to have the highest efficiency and lowest annual operating cost. Compared to a common production method in Sweden, (air handling unit with district heating and a chiller) 19-26% of the annual use and 13-18% of the annual operating cost can be saved. When compared to a more similar production method, (air handling unit with a heat pump and a chiller) 1-2,4% of the annual use and operating cost can be saved. The newly build office building already as the best possible indoor climate with a PPD below 6%, but it is not yet optimized from an use perspective. Optimizing the temperature set points and introducing night time ventilation (simulation 1a) can save a total of kwh which is equal to or SEK respectively in operating costs each year. This adaptation could save 7,5% of the annual consumption compared to the starting simulation based on the current situation of the building and settings in the building management system (simulation 1). Adapting the building with demand controlled lighting (simulations 2, 4 and 5) could save kwh which is equal to 510 or SEK respectively in operating costs each year. This adaptation saves 3,4% of the annual consumption compared to the simulation with optimized temperature set points and a minimum of night time ventilation (simulation 1a). Adapting the demand controlled ventilation set points in the building management system (simulations 3 and 4), will save kwh which is equal to 758 or SEK respectively each year. This adaptation saves 5% of the annual consumption compared to the simulation with optimized temperature set points and a minimum of night time ventilation (simulation 1a). With the adaptations to the temperature and airflow set points in the building management system and by installing demand controlled lighting, a total of kwh which is equal to or SEK respectively could be saved annually, compared to the building in its current use, whilst maintaining the best indoor climate. This means that 15,9% of the annual consumption can be saved with all of these adaptations combined. The investigation of the newly build office building in Kvänum showed that for every project it is worthwhile to further investigate the temperature set points both for the occupied periods and the unoccupied periods, the airflow set points, (both for optimized night time ventilation and optimized indoor climate) and investigating the possibility of demand controlled lighting. Investigating the possibility for demand controlled ventilation can downsize the air handling unit by at least one size, which can save on investment cost. Installing the multifunctional unit in cases where there is a need for both heating and cooling at the same time can be more cost effective for the operating costs, compared to when other production methods are used, whilst still guaranteeing the best possible indoor climate. 5

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7 ACKNOWLEDGMENTS I would like to thank everyone for helping and supporting me all the way so that I could make this thesis to what it is today. First off all I want to thank my parents for supporting me in every step before and during my stay in Sweden. Without their love, attention and the candy that they have send me it would have been very difficult for me to complete my work. I would also like to thank Ing. Petra Vladykova, Ph.D., Arch. Markus Kalo, M.Sc., John Woollett, CEng and Ir. Arie van Kampen for all their supportive criticism, ideas and support during the making of this thesis. It is because of their support and patience that I have come where I am today. I am incredibly grateful to them for making it possible for me to go to Sweden. Furthermore I would like to thank all the staff at Swegon for all the advice and information that they have given me, but also all the fun talks during fika, which greatly helped with getting to know the Swedish country and culture. I also want to thank all the new friends I made in Gothenburg and Stockholm, for their fun and support. Without them life in Sweden would have been hard and dark, but because of them it was enjoyable, full activities and with plenty of new experiences. 7

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9 Table of contents 1 Introduction Bachelor thesis objective Main questions model data in ida ice The building data IDA ICE Installation data Internal load data The Excel model Energy production in the model Cost of production Methods The building IDA ICE The Excel model Analysis The building IDA ICE The Excel model Results and discussion The building Settings for the baseline model Results of each simulation and adaptation IDA ICE & the Excel model Conclusion and recommendations Further work The building IDA ICE The Excel model Symbols and abbreviations Appendix

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11 1 INTRODUCTION Comfort and use The indoor environmental quality is the summation of several indoor quality factors [1]. Figure 1-1 below shows these factors. One of these is the indoor air quality, henceforth defined as IAQ. On average, people spent 90% of their time indoors [2]. Therefore it is of the utmost importance that the indoor environmental quality is good, if unhealthy living conditions are to be avoided. Figure 1-1 The indoor environmental quality defined The oil crisis of the 1970 s was one of the main events that has diverted more focus on use, but also in the last decade it has become a large focus point in the building industry in Europe. Over time, it became more important to build efficient buildings, this meant that certain design choices for the building and its installations were made to decrease the use of a building. In order to save, buildings where made more airtight and better insulated. This had a positive effect on the consumption, but one of the consequences was that the natural ventilation in these buildings was also put to a halt and mechanical installations were not always installed, properly dimensioned and/or properly managed for a healthy indoor environment. Because of this, buildings were not ventilated well enough. Thus the sick building syndrome became into existence [3]. This meant that people could become temporarily and sometimes even permanently sick by staying in a certain building, or part of a building with an unhealthy indoor environmental climate. Both for existing and new buildings there is a challenge to find the optimization of the indoor air quality in the most efficient way. 1.1 Bachelor thesis objective The main focus of this thesis is to optimize the performance of the newly build office building in Kvänum, Sweden, without compromising on the IAQ. The focus is also on where there could be made some adaptations to the settings of the building management system without compromising on the IAQ and recommendations on the use of external solar shading and demand 11

12 controlled lighting. Whenever adaptations to the system will be researched, the IAQ must never become worse within the present parameters, which is why all the other researched adaptations will work from a baseline model, where the set points of the building management system are optimized. The IAQ can be defined into 4 different categories: best (I), good (II), acceptable (III) and unacceptable (IV). These definitions can be found in the IDA ICE software and are based on the EN standard [4] [5]. Table 1-1 below shows the set points of these 4 different categories. These categories will be used to define the IAQ of the building. Category I is the best category and that is the one that will be aimed for in this thesis. However, if the percentage of people dissatisfied (PPD) of category I can be achieved with parameter settings from category II or III, these parameters will be used. Class Comfort Indices Table 1-1 Comfort category set points Operative Temperatures (⁰C) PPD (%) PMV Minimum Maximum Airflow Per person (l/s) Per m 2 (l/s/m 2 ) CO 2 levels (ppm) Above outdoors Maximum indoors I < 6-0,2 / +0, ,5 10 0, II < 10-0,5 / +0, , III < 15-0,7 / +0, , IV > 15 < -0,7 / +0,7 > N.A. N.A. < 4 N.A. < 800 < The set points for IAQ in the building are being managed by the building management system made by Swegon. This is a server that controls the different components connected to the server. In this case this is the air handling unit, the different damper components, valves and the comfort modules. The building management system communicates the information measured and generated by the components to each other, in order to keep the IAQ within the set points that have been put in the control software. This can be controlled on the building level, zone level and the room level, so that each part of the building can have its own desired indoor climate. The results of the simulations will be used to calculate the use and operating costs of different types of production methods and distribution methods. All of the simulations will have the same indoor comfort level, but the way the is produced and distributed will be different with each simulation. This is done to show the effect on the performance of delivering the right amount of at the right time and the right place provided by demand controlled ventilation (DCV), which is a variable air volume system (VAV), compared to the same amount of everywhere provided by constant air volume (CAV), or a combination of the two at any given time. The differences in production will be researched to show what type of production is the most efficient way and the cheapest way. The investment cost of these different installations types will not be researched since the focus of the research is on the operating costs. 1.2 Main questions Which parameters in the building management system, in the building design and in the choice of installations have influence on the indoor air quality, the delivered and produced, how can these be optimized and what is the effect on the operating costs? 12

13 Sub-questions 1. How do the adaptations to the set points in the building management system influence the indoor air quality and the performance? 2. How do the adaptations to the choices in the building design and distribution installations influence the performance in the different theoretical scenarios? 3. How does a different choice for production installations affect the performance, without the loss of an optimized indoor climate and what operating costs are involved in this? 4. How can the information generated by the investigation of the office building in Kvänum be used for other buildings? Description of structure of the bachelor thesis Figure 1-2 shows that the thesis consists of 3 main parts. The first part focuses on optimizing the set points in the building management system. The indoor temperatures, ventilation airflows and CO 2 set points will be investigated to get an optimized indoor air quality, with the least amount of heating, cooling and ventilation as possible. Figure 1-2 Structure of the thesis In the second part, the effect of adaptations to the building in the form of demand controlled lighting, external solar shading, a full demand controlled ventilation and constant air volume is analyzed. Demand controlled ventilation is a variant of a variable air volume system. A financial part is also involved in the second part where the payback time for the external solar shading is calculated, to show if this adaptation is financially feasible as well. The ventilation is controlled by temperature set points in the office landscape and CO 2 levels and temperature set points in the conference rooms within the zone. This means that when the sensors in the zone detect that the temperature or CO 2 levels rise above or drop below the set points in the building management system, the system will adjust its airflow for ventilation or water 13

14 flow for heating or cooling in order to restore the indoor air within the desired set points. Because these conditions are not always the same, this is defined as a VAV system, since these airflows will be variable throughout the day and night. In the current office building the office landscapes, which together take up a large section of the building, are ventilated with a CAV system. A constant air volume system has only one, pre-set air volume which will always be the same, no matter what indoor conditions apply. This means that often there is more ventilation in a room than is required. The adaptations to the demand controlled ventilation will give insight in the performance and IAQ when the entire building is controlled by demand controlled ventilation. In addition, there will be a study where the entire building is simulated with a CAV system, so that a good comparison can be made with the effect of DCV on the performance and IAQ. In the third part, the production of by different types of installations and the cost in production will be evaluated. The required distributed is different for every scenario, but the same per method of production. This will show how the different types of installations have a different use and with that a different operating cost, but with the best indoor air quality maintained. Only the operating cost and the efficiency of the supplied divided by the distributed will be calculated. This will be done by creating an Excel model in which all of these factors are calculated. The Excel model is set up in such a way that it can be used with different efficiencies in production and costs. 14

15 2 BUILDING MODEL DATA IN IDA ICE This chapter contains all the data that is required to set up the simulations in IDA ICE. 2.1 The building The building is built up according to the data and drawings shown in chapter 3.1. All the other settings below are settings in the IDA ICE software that need to be defined before the simulation can be run data The office building is described further in chapter 3.1, based on the survey described there. Table 2-1 shows the general building dimensions of the newly build office building in Kvänum. Table 2-1 The new office building dimensions dimensions [m] Depth 14,1 Length 42 Height 10 Table 2-2 shows the other building properties used to build the model with in IDA ICE. Table 2-2 properties of the new office building properties Floor area m 2 Floors 3 Height of floor 3,05 m structure Steel and concrete U-value Area insulation [W/(m 2.K)] [m 2 ] Sandwich panels 0, Concrete pre-fab walls 0, Ground floor 0, Roof 0, Windows 1, g-value windows 0,68 Weather data There is no weather station present in Kvänum, so it is not possible to use weather data of the actual location. There are 2 options for nearby weather stations, Figure 2-1 shows the location of these weather stations. One is in Linköping and the other is in Jönköping. The weather station in Jönköping is closer to Kvänum, but it is next to a big lake which influences the weather data. The weather station in Linköping is further away than the one in Jönköping, but it is more enclosed by land, like Kvänum. It has therefore been decided that the weather data from Linköping should be used to simulate the building models with. 15

16 Figure 2-1 Location of Kvänum, Jönköping and Linköping Kvänum Outdoor CO 2 level The outdoor CO 2 level is set at 400 ppm. This is done because the outdoor air usually has a CO 2 level of 350 to 450 ppm and 400 ppm is the average of those two numbers [6]. It is also the standard setting in the IDA ICE software. Wind profile There are several different wind profiles that can be chosen for the building. For this building the suburban wind profile has been chosen. The area of Kvänum is an open and spacious area, but this part of the building is directly surrounded by other parts of the cluster of buildings, so there are less surfaces where the wind can affect the building. 16

17 Holiday data Table 2-3 shows the dates that are official Swedish holidays when the office will be closed for the entire day. This does not include the summer holidays, when the majority of the Swedish working population takes their official holiday. Table 2-3 Sweden s national holidays Sweden s national holidays New Year Epiphany Good Friday Easter Sunday Easter Monday International Workers Day Ascension Day National Day of Sweden Pentecost Midsummer s Day All Saints Day Christmas Eve Christmas Day Boxing Day New Year s Eve January 1 st January 6 th April 18 th April 20 th April 21 st May 1 st May 29 th June 6 th June 8 th June 21 st November 1 st December 24 th December 25 th December 26 th December 31 st 2.2 IDA ICE Installation data The air handling unit The air handling unit is build up with a supply and extract fan, a heat exchanger and a heating and cooling coil, which is placed after the supply air fan. Table 2-4 shows the parameters of the air handling unit which are being used in the simulation software. These parameters have been taken from the building management system. The program is set up in such a way that the air handling unit can adapt to the circumstances it is simulated in. This means that there is not a limit to what it can deliver in the simulations. Table 2-4 Air handling unit parameters AHU parameters Max supply pressure 400 Pa Max extract pressure 400 Pa Max airflow l/s Temperature supply air 16 ⁰C Average heat exchanger efficiency 85 % 17

18 Lighting The lighting is controlled by schedule. All the lights in the entire building are switched on every workday at 07:00 when the first persons enter the building. It is switched off at the end of the workday at 19:00 when the last persons leave the building. The internal load of the lighting equipment can be seen in Table 2-7. The type of lighting is LED lightbulbs throughout the entire building. In the offices on the 3 rd floor T5 fluorescent light will be installed. External solar shading The external solar shading that are used for the simulations are external vertical screens that cover the entire area of all the windows with a South-Eastern orientation. The screens are automatically controlled by the amount of solar radiation the sensor registers. When the solar radiation is above 200 W/m 2 the external solar shading will go down and when it goes below 200 W/m 2 it will go up. The 200 W/m 2 set point is used because this is the standard setting in the IDA ICE software and it is the maximum standard setting for sun sensors according to the book Solar shading by REHVA, the federation of European Heating, Ventilation and Air-conditioning Associations [7]. The g-value used for the vertical screens is 0,15. This value is a typical g-value for vertical screens [8]. There is no time delay calculated in the registering of the amount of solar radiation and the activation of the solar radiation. Heat and cold generation The rooms in the building are ventilated, heated and cooled by comfort modules. Comfort modules are installed in the ceiling and can distribute the air into 4 different directions and supply heating or cooling in a room. The building has been equipped with a 4 pipe comfort module system, so that heating and cooling can be provided at the same time. In the simulations however, the zones are heated and cooled by ideal heaters and coolers. These are computer generated components that can supply the required heating and cooling into the simulated building. This is done mainly because the model did not respond well to the simulation of comfort modules and the results from these simulations are inaccurate or unrealistic. The evaluation is not done on the installed equipment in the building Internal load data The occupancy The model has been built up with several different zones. These zones have different occupancy rates, equipment loads, lighting and set points. Table 2-5 shows the occupancy rates from 07:00 till 19:00 for all workdays where the majority of the people come in between 09:00 and 17:00, divided into sections of 2 hours each. These percentages are divided up in the office landscape, that houses all the employees for a longer period of time, and in the conference rooms, that house a portion of the employees for a shorter period of time. The percentages are set up as an estimation made by the supervisors of this thesis, the people involved in the project at the new office building in Kvänum and the author of the thesis. On average, offices are occupied 30-50% of the time [9]. The presence seen between 13:00 and 15:00 in the office landscape is 50%, but in the conference rooms it is. This suggest that there is a 150% occupation in the building. The occupancy in the office room is for 25 persons, but in the conference rooms this is 1 person per 1,5 m 2. This differs per conference rooms between persons, depending on the size. This is made up out of people who work in the office landscape and people from other parts of the building or other companies that have a meeting in the conference room. 18

19 Table 2-5 Occupancy rates and profiles 07:00 09:00 11:00 13:00 15:00 17:00 Type Occupancy 09:00 11:00 13:00 15:00 17:00 19:00 Office landscape 25 persons 20% 50% 30% 50% 40% 20% Conference room 1 per 1,5 m 2 0% 30% 20% 0% 0% Toilets Constant air volume of 15 l/s/toilet Temperature and internal loads Table 2-6 shows the different temperature and CO 2 set points that are being used in the building management system at this moment. Table 2-7 shows the internal loads that are used in the simulations. The equipment load is the standard load for equipment in the IDA ICE program, but they are also within the boundaries described in the EN standard, subsection 6.7.4, where it says that the equipment load is usually between 25 Watt and 200 Watt. The lighting equipment has been set in coordination with the supervisors and the estimation from Table 27 in the EN standard [10]. The office landscape has no temperature control in the holidays and with night time cooling because these set points are not incorporated in the building management software for the equipment used in the office landscapes. This is however built in the software of the conference rooms. The office landscapes and conference rooms are controlled with different equipment and as such have different software capabilities. Table 2-6 Temperature and internal load set points Occupied temperature Unoccupied temperature Holiday temperature Night time cooling Type Cool Heat Cool Heat Cool Heat Cool Heat CO 2 set points Office landscape 23⁰C 21⁰C 25⁰C 20⁰C N.A. N.A. N.A. 18⁰C N.A. Conference rooms 22⁰C 21⁰C 24⁰C 21⁰C 25⁰C 16⁰C 24⁰C 15⁰C ppm 2.3 The Excel model Table 2-7 Internal loads Persons Equipment Lighting 70 W/p 150 W/p 9 W/m 2 70 W/p 150 W/p 9 W/m Energy production in the model These are the 7 different methods of producing that are used in this thesis, but for all methods the air handling unit (AHU) is powered by electricity: A. A multifunctional unit that produces heating, cooling and ventilation simultaneously or independently from each other. Cooling and heating is produced for the supply air and for the secondary water circuit. Due to multiple internal recovery processes free-heating and free-cooling can be maximized. B. AHU with an electric chiller to produce cooling in combination with a heat pump. C. AHU with an electric chiller to produce cooling in combination with direct electric heating. D. AHU with an electric chiller to produce cooling in combination with oil for heating. 19

20 E. AHU with an electric chiller to produce cooling in combination with gas for heating. F. AHU with district cooling to produce cooling in combination with district heating. These different production methods are used in the Excel model because this gives the insight in the difference in the required amount of purchased. This has influence on the total operating costs which are mentioned below. It has also influence on the greenhouse emissions such as CO 2-emissions produced for heating, cooling, ventilating and using the building. The investigation in the CO 2-emissions is not part of this thesis, but the results from the Excel model could be used for further investigation into the possible CO 2-emissions produced for the running of this building. Table 2-8 shows the different efficiencies that apply for each method. All these efficiencies are taken from the IDA ICE software. The Energy efficiency ratio or EER is the efficiency of a chiller and the Coefficient of performance or COP is the efficiency of a heat pump. These efficiencies are different per country and sometimes even per location in the country itself. This is because these efficiencies are based on local conditions like the weather, but also the supplied types of. Oil and gas from different locations have different properties and as such influence the efficiency of the system. The same goes for the chillers and heat pumps. The efficiency of these systems are influenced by the temperature and pressure conditions outside the buildings. The tables in the Excel model have been set up in such a way that they can easily be adapted to new or different efficiencies for each production method. Table 2-8 Production efficiencies Type of production method Energy efficiency ratio (EER) cooling 3,0 Coefficient of performance (COP) heating 4,0 Electricity 1,0 District heating 1,0 District cooling 1,0 Oil 0,9 Gas 0, Cost of production The prices that have been used for the calculation of the operating costs can be seen in Table 2-9. The prices are taken from IDA ICE and are converted from Swedish Kronors to Euro. The conversion factor is 9,2 SEK per Euro and is taken in September 2014, at the start of the project. These costs are put in as variables because these differ per country. That way the results from the Excel model can be adjusted to different situations in different countries. The prices are noted per kwh and taxes are included. Table 2-9 Energy prices in Euros and Swedish Kronors Energy type Price in EUR Price in SEK Electricity 0,13 EUR 1,20 SEK District heating 0,09 EUR 0,83 SEK District cooling 0,11 EUR 1,01 SEK Oil 0,10 EUR 0,92 SEK Gas 0,09 EUR 0,83 SEK 20

21 3 METHODS This chapter contains the general overview of the design and use of the new office building, the IDA ICE software and the Excel model. It shows the different methods that are used to come to the end result of the thesis. The building section describes what is used to investigate the building with and where some of the data that are used can be found. It is set up in the way that first the entire cluster of buildings, both office buildings and factory, is described in general, where after the new office building, which is the core of this thesis, will be described in further detail. This is done for both the design of the cluster of buildings and the usage of the buildings. The IDA ICE section explains what IDA ICE is and the Excel model section describes the working and possibilities of the Excel model. 3.1 The building The building has been surveyed during a visit to the building. The drawings that can be found in the appendix have been analyzed and have been used to build the building model in the simulation software mentioned in chapter 3.2. The settings for the building management system have been analyzed and the settings that are used are the temperature set points seen in Table 2-6 and the airflow settings seen in Table 9-2 and Table 9-3 in the appendix. Design of the cluster of buildings The surveyed factory in Kvänum, Vara Municipality, Västergötland province, Sweden, (GPS coordinates: 58 17'53.4"N 13 11'25.6"E) has a multifunctional use. It consists of a production hall, assembly hall, storage areas, offices, a showroom, conference rooms and background facilities like a cafeteria, a library, and a winter garden. The buildings have been expanded over the course of 50 years, where new buildings where added whenever there was a need for expansion. In total this cluster of buildings has a floor area of m 2, of which m 2 is being used as offices, including m 2 of a newly built office space the focus point of this thesis. The structures of the cluster of buildings are made out of steel columns and beams with concrete floors. The walls are made out of concrete elements and have insulation in between the internal and external concrete elements. The windows consist of a double pane glazing with an aluminum window frame. The main entrance has a North-West orientation, with the majority of the windows of the offices facing a North-West orientation. In the old office building the windows on the first and second floor in the South-East orientation are overlooking the winter garden, and the windows on the third floor are connected to the outside [11]. Figure 3-1 shows a frontal view of the old and new office building. The green frame encircles the new office building that is investigated. Figure 3-1 The Swegon factory in Kvänum. The old office building is yellow, the new office building is grey 21

22 Design of the new office building The new office building was constructed in 2013, to accommodate more office space for the employees of the company. The new office building has steel columns and beams with concrete floors for structural support. Table 2-1 shows the building dimensions. The new office building is oriented towards the North-West like the old office building. The first two floors are built adjacent to the factory in the South-East direction and the old offices to the North-East, so these walls have no windows at the first and second floors in the South-East and North-East walls. However, the third floor is above the roof of the factory hall, so here the South-East facade has windows in them. None of the windows in the new office building have active external solar shading installed but each window has manual internal shading on the inside of the building. Almost half of the external walls are made out of pre-fab concrete walls with insulation and a high pressure laminate plate finishing. The other half of the external walls are made out of sandwich panels. The third floor is currently not being used, but can be used when expansion is needed. See the appendix for the drawings of the building. Table 2-2 shows the other building properties. Ventilation in the cluster of buildings The entire cluster of buildings has 46 air handling units which supply the production hall, assembly hall and storage area with heated or cooled fresh air. The old office buildings are heated and cooled with different types of waterborne systems like comfort modules, active climate beams and passive climate beams and airborne systems with active air diffusers, passive diffusers, different types of air diffusers for supply, extract and transfer air and several different damper components at different levels in the system. Not all of these air handling units are the same, since the cluster of buildings were made over a course of 50 years. Some do not have sensors in them to regulate or register data about how they function. The air handling units have been installed all over the building, each of them supplying fresh air to a certain zone in the cluster of buildings. Multifunctional unit in the new office building The new office building is being heated and cooled with comfort modules and fresh air is supplied, extracted and transferred by different types of air diffusers. Several different damper components are placed at different levels in the air supply system. The hot tap water connection is not connected to the building, but it is possible to also supply hot tap water to the new office building, using the multifunctional unit. This is will not be done for the simulations, since this is not the real case. All of the conference rooms are demand controlled on CO 2 and temperature base. The office landscapes are demand controlled on a temperature basis. The multifunctional unit supplies the entire new office building with all the required air and warm and cold water for the comfort modules. The third floor has not yet been used, so the system has been running for up to 66% of its designed output. Figure 3-2 shows the multifunctional unit that is installed in the new office building. The beige component is the air handling unit which supplies the building with fresh air. The white component is a module that gets the last remaining out of the extract air before it is ventilated out of the building. The green component is the component that has a chiller which uses both sides to deliver both heating and cooling to the building. The blue component has all the plumbing and valves in one place, for easy access during maintenance. The system supplies heating and cooling 22

23 water, tempered air and hot tap water on a demand controlled basis. Because of this the supplied to the building can be optimized and all the controls for regulation the different processes for supplying hot or cold air and hot tap water are centralized in one machine. The multifunctional units gives the possibility to store heating and cooling and has all the plumbing controls integrated in one machine. Figure 3-2 The multifunctional unit Usage of the cluster of buildings The cluster of buildings is partly a manufacturing factory and partly an office building with conference rooms. In the manufacturing factory the air handling units and its components are produced, assembled and stored. The old office buildings are used as normal offices, usually with one person per office room, with one laptop and one extra screen. Figure 3-3 Floor plan of floor 1 N 23

24 Usage of the new office building The new office building is mainly being used as an office building with open plan offices, a few single office rooms and a few conference rooms at the first and second floor. The third floor is currently not being used, but designed to have an office landscape, 6 single offices and 2 conference rooms. Figure 3-3 shows the floor plan of floor 1. In the appendix more drawings can be found. management system The building management system controls all the climate products in the building from one server. This gives optimum control up until the room level. This system can be accessed via a web browser. It can control different temperatures, airflows, pressures and CO 2 set points per product. It also monitors these parameters if required. Table 9-2 and Table 9-3 show the airflow set points used in the building management system before the adaptations are made. Additionally, Table 2-6 shows the temperature and CO 2 set points used in the building management system before the adaptations are made. 3.2 IDA ICE IDA Indoor Climate and Energy (IDA ICE) software is a whole year and dynamic multi-zone simulation application made by a Swedish software company called Equa. It models the building, its systems, and controllers. This gives the ability to calculate and study the lowest possible consumption and the best possible indoor climate whilst providing comfort to the occupants. IDA ICE gives the possibility to work with different climate data, standards and component and material data. Figure 3-4 shows 3 different tabs that can be seen in IDA ICE. From left to right the model tab is presented where the entire building is being built. In the middle the installation tab can be seen where the entire heating and cooling system can be built in detail and on the right the simulation tab that shows the calculation. The program has been validated according to several different standards, including the ASHRAE 140, 2004, the CEN standards EN 15255, EN 15265, 2007, EN and LEED and BREEAM standards [12]. Figure 3-4 IDA ICE in 3 tabs, from left to right, the model tab, the installation tab and the simulation tab IDA ICE generates a lot of data on a building and zone levels. At the building level the overall consumption per month, indoor air quality and air handling unit performance is shown. At the zone level the indoor air quality per zone is shown, together with a year round heat balance and a year round indoor temperature chart of that particular zone. 24

25 3.3 The Excel model The Excel model generates an overview that shows the efficiency and consumption of all the seven simulations mentioned in chapter 2.2 in combination with all production methods mentioned in chapter 2.3. Part of the results of the simulation is the consumption per month, which is used to build up the Excel model with. This can be used to calculate the operating cost of each simulation in relation to each production method. This is useful to see which simulation with an optimized indoor climate, but different building and installation adaptations is the cheapest to use. It is possible to adjust the efficiencies and prices in the Excel model. This gives the possibility to use the Excel model for different situations or scenarios where other types of installations with a different operating cost apply. After all the boundaries and data has been put in the Excel model, seven production methods will each calculation their respective consumptions and prices per simulation. This way it can be easily seen which production method is the most efficient, has the lowest annual operating costs and has the lowest purchased per square meter. The different production methods can be interesting for different locations. In Sweden district heating with a chiller is a common way of heating and cooling the building, but in the Netherlands gas is much more common as a source of heating. In other countries heating with a heat pump is more common. These can all be compared for each country on its own, when the respective efficiencies and prices are inserted in the Excel model, together with the dynamic simulation data. For this thesis a comparison of 2 different production methods will be made. This is production method A, the multifunctional unit and the most common method in Sweden, production method B, an AHU with a chiller and district heating. This is done to show how much and money can be saved annually when the multifunctional unit is used. The Excel model will also be used to show which simulation has the lowest consumption and the cheapest operating cost by comparing all simulations with each other. This means that both the production methods and different simulations are easily comparable to each other. In addition to that a comparison between production method A, the multifunctional unit, and production method B, the AHU with a chiller and a heat pump will be made. This is done because these two production methods are comparable. The multifunctional unit has a chiller/heat pump for both heating and cooling the building at the same time. This way the savings that can be made by installing the multifunctional unit can be shown, when compared to a scenario that has the same production machines, but without the optimization between the different components. 25

26 CO 2 levels (ppm) 4 ANALYSIS This chapter contains all the adaptations that are made to the building and the building management system. First the adaptations to the set points in the building management system are discussed. After that the simulations that will be made are presented, followed by the explanation of the validation of the simulation model. In the last part additional input in the Excel model is explained, after which the presentation and overview of the output data is explained. 4.1 The building Adaptations to the simulation models Simulation 1 is the model that represents the current situation. After running the simulation it showed that the IAQ is already below the required 6% PPD to be in comfort category 1. This is because the building envelope has a low U-value, and the set points in the building management system are already within the comfort category 1 parameters. As such, the adaptations to the set points in the building management system is not done to optimize the IAQ, since it is already optimized. However, it is possible to adapt the set points in order to save, but still maintain the best IAQ. This will be simulation 1a, the baseline model, from which all other simulations will be run, to assure the best possible indoor climate with the lowest possible use as a starting point for all the other adaptations. The set points that can be adapted are: - Maximum CO 2 level - Cooling set point - Heating set point Maximum CO 2 level The conference rooms have a maximum CO 2 set point of ppm. The CO 2 set point do not have to be adapted to provide a better indoor air quality, it is already the best indoor air quality. By lowering the CO 2 set point to 750 ppm conform the comfort category 1 set point for CO 2 levels, the air quality, which is already good, does improves slightly, but the consumption goes up whilst the indoor climate cannot be further improved. Figure 4-1 shows the average CO 2 level in the office landscape. This does not go higher than 500 ppm. Figure 4-2 show the average CO 2 levels of the conference rooms. In the conference rooms the CO 2 levels do not go higher than 800 ppm. This is 50 ppm higher than the set point of 750 ppm, and this occurs between 13:00 and 15:00, when the occupancy in the conference rooms is at or higher. Figure 4-1 CO2 levels in office landscapes CO 2 level in hours 26

27 CO 2 levels (ppm) Figure 4-2 CO2 levels in conference rooms CO 2 level in hours In the appendix Figure 9-7 and Figure 9-8 show the average air age of the office landscapes and conference rooms. The air age indicates the age of the air inside the zone. This is not the amount of air changes inside the zone. It is clear that the office landscape has a much lower air age than the conference rooms. This is because the office landscapes have CAV settings in the building management system (BMS), whilst the conference rooms have DCV settings in the BMS. In the other simulations this will of course change since the set points in the BMS will be adapted. Figure 9-9 and Figure 9-10 show the average relative humidity of the office landscapes and conference rooms. The relative humidity cannot be actively controlled in the building by the installed equipment. This has influence on the temperature set points and the consumption that are required to provide the best indoor climate with the lowest consumption. Cooling set points The cooling set point for when the rooms are occupied has been set at a maximum of 22⁰C for the conference rooms and 23⁰C for the office rooms. Since the cooling set point for comfort category 1 has been set at 25,5⁰C it is logical to assume this is a set point that can be used for the baseline model. However, several simulations have shown that when 25,5⁰C is used as a maximum temperature set point for cooling, the PPD goes up. This is because, especially in summer time, the rooms more easily overheated and the system needs time to adjust to the new load. After running several simulations with different set points, it has been concluded that the optimum cooling set point should be at 23⁰C when the room is occupied. This ensures a PPD of 6% whilst saving as much as possible. When the room is unoccupied the cooling set point can go up with 2⁰C to 25⁰C to save. When there is no occupation in the room this has no influence on the PPD, since there are no people to dissatisfy. When people come back into the room the system needs time to adjust to the previous presence set point. Because of that the internal temperature can be above that of the cooling set point for occupation the first few minutes of the use of the room. As Table 4-1 shows, the set points used from simulation 1a onward are of 23⁰C when the room is occupied and 25⁰C when the room is unoccupied for both the conference rooms and office rooms. This is the optimum cooling set point when it is desirable to stay within comfort category 1 in the newly build office building in Kvänum. 27

28 Table 4-1 New cooling set points New cooling set points When occupied When unoccupied Office landscape 23 C 25 C Conference room 23 C 25 C Heating set point The minimum heating set points for the conference rooms are 21⁰C for both when it is occupied and when it is unoccupied. In addition, the minimum heating temperature for holidays is 16⁰C and the minimum heating temperature for night time cooling is 15⁰ Celsius. The office landscapes have a minimum heating temperature set point of 21⁰C when it the room is occupied. When the room is unoccupied the minimum heating temperature set point is set at 20⁰C. The office landscapes are not separately controlled with an extra set point for holidays, but the night time cooling set point is set at 18⁰C. Since the minimum temperature set point for when the rooms are occupied is already at the minimum of comfort category 1 it is not required to adjust this. Setting the minimum temperature at 20⁰C will increase the PPD. The set points for heating when the rooms are unoccupied do not change for the conference rooms, where it is still maintained at 21 C, and it changes by 1 C to 20 C for the office landscapes. When the minimum temperature set point for when the rooms are unoccupied are put in at 19⁰C the PPD does not go up whilst saving at the same time. A difference of 2⁰ Celsius to 19 C can be used for the minimum temperature when the rooms are unoccupied to save. This is also shown in Table 4-2. Table 4-2 New heating set points New heating set points When occupied When unoccupied Office landscape 21 C 19 C Conference room 21 C 19 C The minimum temperature set point for the holidays does not have to be adjusted. It does not have an influence on the PPD, since there will be no presence in the rooms and it will save because it gives more room for temperature fluctuations. adaptations The adaptations to the building will be made by modeling external solar shading and demand controlled lighting in the software. The external solar shading will be modeled in the South-East orientation since that orientation has a large window area with Southern orientation. There are two windows in the South-West wall, but these windows are in the staircases and the staircases are not simulated with any occupancy. Therefore the effect of modeling external solar shading with such orientation would be very small and would not affect the indoor climate, since there is no permanent residence in the staircase. A payback time will then be calculated to show the financial feasibility for applying external solar shading to the building. These simulations will also have a complete demand controlled lighting system installed. This will optimize the use by only having lighting in areas where people are present. It must be noted that the more efficient Compact Fluorescent Lamp (CFL) and Light Emitting Diode 28

29 (LED) wear down faster when they are switched on and off again quickly. This is something that is likely to happen when the light in a room is controlled by a sensor. This can be minimized by setting a time delay in the off switch, but there is still a chance that these types of lamps wear down quicker than the traditional light bulbs. Ventilation adaptations The adaptations to the ventilation will involve modeling a complete DCV system. At the present, the office landscape areas have a constant air volume system installed. The conference room have a DCV system installed. Table 4-3 shows what percentage of the building already has a DCV system. Table 4-3 Ventilation system Type Area % System Office landscapes m 2 88% CAV Conference rooms 207 m 2 12% DCV m 2 By implementing a demand controlled ventilation system there will be less needed for ventilation, but the set points from the baseline model will still guarantee an optimized IAQ. This way the optimized climate will be supplied and distributed in a more efficient way. There will also be 2 simulations where the entire building will be ventilated by a CAV system. This is done to show the effect on the consumption and operating cost of a CAV system compared to a DCV system. To give a realistic representation of the actual possible use of the CAV system it will be on from 07:00 until 19:00. From 19:00 until 07:00 the next day, weekends and holidays the ventilation will only ventilate the minimum required 0,35 l/s/m 2, in accordance to Swedish building standard BFS 2014:3 - BBR 21 [13]. Table 9-2 in the appendix shows the current CAV set points in the building management system for all the office rooms. These set points are controlled per group of 4 comfort modules. Table 9-3 in the appendix shows the current DCV set points for the conference rooms. These will not be adjusted since it is already a DCV system. The maximum ventilation set points will not be adjusted, only the minimum and unoccupied set points will be adjusted to accommodate a DCV system. In the real office building in Kvänum the third floor is currently not being used. In the simulations however, the entire third floor is simulated as being used. The building management system does not yet have set points for the third floor. As part of the thesis there will be recommendations for the set points on the third floor. The set points of the first and second floor have been used as a starting point for the ventilation set points of the third floor. Table 9-5 shows the set points for the entire floor that have been used. The simulations The simulations are built up as follows: Simulation 1: As mentioned before, this is the building and distribution set as they are in the real new office building in Kvänum. This simulation is done as a starting point, to show how much is used right now and how much can be saved by adaptations to the temperature set points, the building and the distribution system. 29

30 Simulation 1a, baseline: In this simulation the temperature and ventilation set points are optimized in the model of simulation 1. This is done to create the most optimized and efficient indoor climate. These set points are used for all other simulations from here on so that the indoor climate is always as good as possible. Also, during the nights the ventilation is decreased to 0,35 l/s/m 2 to accommodate the Swedish law of ventilation, but without the 7 l/s/person, to minimize the ventilation. All the air distribution systems from this simulation on are called comfort+ to indicate that the set points have been optimized, but comfort+ is not a product name. Simulation 2: The building is improved by simulating demand controlled lighting and external solar shading. The air distribution remains at 88% CAV and 12% DCV. This is done to show the effect of the building adaptations in itself. Simulation 3: The building is simulated without demand controlled lighting and external solar shading, instead the air distribution is improved by simulating it with DCV. This is done to show the effect of the air distribution adaptations in itself. Simulation 4: Both the building and the distribution are improved. The building is simulated with demand controlled lighting and external solar shading, and the air distribution is improved by installing it with DCV. This is done to simulate all the adaptations together for the most efficient building. Simulation 5: The building is improved with demand controlled lighting and external solar shading, however the air distribution is installed with CAV, to show the difference in the consumption compared to other simulations. Simulation 6: The building is simulated without demand controlled lighting and external solar shading, and the air distribution is simulated with CAV, to show how big the difference is when the building is not improved and what the consumption would have been if the building had not been installed with a DCV system. Figure 4-3 shows an overview of all the simulations that will be made. Figure 4-3 Overview of the simulations Simulation 1 Existing indoor climate CAV / DCV Current building, no adaptations Simulation 6 Class I indoor climate CAV Simulation 1a Class I indoor climate CAV / DCV Simulation 3 Class I indoor climate DCV with demand controlled lighting and external solar shading Simulation 5 Class I indoor climate CAV Simulation 2 Class I indoor climate CAV / DCV Simulation 4 Class I indoor climate DCV 30