Heating energy consumption of a multi-storey municipal residential building: Measurement methodology analysis, modeling and optimization

Heating energy consumption of a

multi-storey municipal residential building

Measurement methodology analysis, modeling and optimization

CENAC-MORTHE Romain 01/08/2011

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ABSTRACT

Energy issues in the building sector become more and more important nowadays. Although the technology improves, the energy consumption remains the same because of people’s way of living.

To reduce the energy consumption, it is possible to improve the technical components that form the building envelope and to change people’s habits.

This report aims at determining the best measurement methodology of the heating and hot water consumption of a building to insure real-time visualization and evaluating the energy savings that could be made by changing people habits.

To do so, an existing measurement methodology is analyzed by making error calculations and computer-based modeling and simulations are carried out to determine the heating consumption of the building under different conditions. The program DesignBuilder is used to assess the energy consumption of the building.

The study shows that a consequent reduction of the heating consumption is possible by only changing people’s habits. Real-time visualization would be really helpful but it needs very accurate measurements that are almost impossible if they are not integrated in the first stages of the building process.

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AKNOWLEDGEMENTS

I would like to thank to following people who helped me during this master’s thesis project:

Professor Ivo Martinac who gave me the opportunity to conduct this project. He offered me freedom and responsibility, which was needed for me to be efficient. His help and support were really precious.

Professor Jaime Arias Hurtado who participated a lot and followed my work throughout the project.

Lars Rydgård who gave me very useful information about Minol products that were necessary to analyze the measurement methodology as deep as I wanted. He answered all the questions I had and without him it would have been impossible to do what have been done.

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TABLE OF CONTENTS

ABSTRACT ... 1

AKNOWLEDGEMENTS ... 2

TABLE OF CONTENTS ... 3

INDEX OF FIGURES ... 5

INDEX OF TABLES ... 6

1. INTRODUCTION ... 7

1.1. DESCRIPTION OF THE NYNÄSHAMN PROJECT ... 7

1.1.1. Nynäshamnsbostäder AB ... 8

1.1.2. Minol ... 8

1.1.3. Tyréns ... 8

1.2. ENERGY SAVING BY VISUALIZATION PROCESS ... 8

2. OBJECTIVES ... 9

3. METHOD OF ATTACK ... 10

4. LIMITATIONS ... 10

5. CHAPTER I: HEATING AND HOT WATER CONSUMPTION MEASUREMENTS ... 12

5.1. CENTRAL HEATING TECHNOLOGY DESCRIPTION ... 13

5.2. HEATING CONSUMPTION ... 14

5.2.1. Description of the measurement method ... 14

5.2.2. Consumption calculations ... 15

5.2.3. Error calculations ... 17

5.3. HOT WATER CONSUMPTION ... 23

5.3.1. Description of the measurement method ... 23

5.3.2. Consumption calculations ... 24

5.3.3. Error calculations ... 24

5.4. CRITICAL ANALYSIS AND SUGGESTIONS FOR FUTURE PROJECTS ... 26

5.4.1. Existing building: Nynäshamn project case ... 26

5.4.2. Non-existing buildings: New projects ... 28

5.5. CONCLUSION ... 28

6. CHAPTER II: DETERMINATION OF THE HEATING CONSUMPTION WITH COMPUTERIZED MODELING... 30

6.1. MODEL CONSTRUCTION ... 30

6.1.1. Geometry ... 30

6.1.2. Construction data... 35

6.1.3. Occupancy profiles ... 36

6.1.4. Heating, cooling and ventilation system ... 38

6.1.5. Model data summary ... 39

6.2. SIMULATIONS –MINIMUM ENERGY CONSUMPTION CALCULATIONS ... 40

6.2.1. Methodology ... 41

6.2.2. Results ... 43

6.3. CONCLUSION ... 47

7. CHAPTER III: OPTIMIZATION AND REDUCTION OF THE HEATING CONSUMPTION ... 48

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7.1. OPTIMIZATION THROUGH TECHNOLOGICAL IMPROVEMENTS ... 48

7.1.1. Shading devices ... 48

7.1.2. Windows ... 52

7.1.3. Insulation ... 55

7.2. OPTIMIZATION THROUGH CHANGE OF PEOPLE HABITS ... 56

7.2.1. Heating set point temperature ... 56

7.2.2. Heating profile ... 57

7.3. OPTIMIZED SOLUTION ... 58

7.3.1. 1^st optimized model - Technology ... 58

7.3.2. 2^nd optimized model – Human ... 60

7.3.3. Global optimized solution ... 61

7.4. CONCLUSION ... 61

8. CONCLUSION ... 62

REFERENCES ... 63

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INDEX OF FIGURES

FIGURE 1.1: ENERGY SAVING BY VISUALIZATION PROCESS ... 9

FIGURE 5.1: CENTRAL HEATING SYSTEM USED BY NYNÄSHAMNSBOSTÄDER ... 13

FIGURE 5.2: MINOMETER M6 ... 14

FIGURE 5.3: COLLECTING AND SENDING DATA WITH MINOMETER M6 AND MINOMAT S/M [MINOL] ... 15

FIGURE 5.4: MINOMESS WATER METER [MINOL] ... 23

FIGURE 6.1: HUS 2 MODEL ... 31

FIGURE 6.2: HUS 2 – NORTH-WEST FAÇADE ... 31

FIGURE 6.3: HUS 2 – SOUTH-EAST FAÇADE ... 32

FIGURE 6.4: HUS 2 – NORTH-EAST FAÇADE ... 32

FIGURE 6.5: HUS 2 – SOUTH-WEST FAÇADE ... 33

FIGURE 6.6: HUS 2 – NON-SIMPLIFIED BOTTOM FLOOR ... 34

FIGURE 6.7: HUS 2 – SIMPLIFIED BOTTOM FLOOR ... 34

FIGURE 6.8: CONSTRUCTION TEMPLATE – EXTERNAL WALLS ... 35

FIGURE 6.9: EXTERNAL WALLS U-VALUE ... 36

FIGURE 6.10: CONSTRUCTION TEMPLATE – WINDOWS U-VALUE ... 36

FIGURE 6.11: OCCUPANCY PROFILES ... 38

FIGURE 6.12: HVAC TEMPLATE ... 39

FIGURE 6.13: APARTMENTS ASSESSED – BA1 AND BA3 – BOTTOM FLOOR ... 41

FIGURE 6.14: APARTMENTS ASSESSED – P3A1 AND P3A5 – PLAN 3 ... 42

FIGURE 6.15: ANNUAL RESULTS – WHOLE BUILDING ... 43

FIGURE 6.16: MONTHLY RESULTS – WHOLE BUILDING... 44

FIGURE 6.17: DAY RESULTS – WHOLE BUILDING ... 44

FIGURE 7.1: ANNUAL RESULTS – WHOLE BUILDING WITH REFLECTIVE SHADING ... 50

FIGURE 7.2: ANNUAL RESULTS – WHOLE BUILDING WITH TRANSPARENT SHADING ... 51

FIGURE 7.3: DOMESTIC FAMILY HEATING PROFILE – HEATING CONSUMPTION OVER ONE WEEK ... 58

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INDEX OF TABLES

TABLE 5.1: BASIC UNCERTAINTY CALCULATIONS FORMULAS ... 18

TABLE 5.2: ERRORS IN THE HEATING CONSUMPTION MEASUREMENT ... 23

TABLE 5.3: ERRORS IN THE HOT WATER CONSUMPTION MEASUREMENT ... 25

TABLE 5.4: ADVANTAGES AND INCONVENIENT OF THE MEASUREMENT METHOD IN NYNÄSHAMN PROJECT ... 26

TABLE 5.5: MEASUREMENT METHODOLOGY IN NON-EXISTING BUILDINGS – FUTURE PROJECTS ... 28

TABLE 6.1: CONSTRUCTION DATA SUMMARY ... 40

TABLE 6.2: ASSESSED APARTMENTS CHARACTERISTICS ... 42

TABLE 6.3: SIMULATION RESULTS – BALDER RESIDENCE, HUS 2 ... 45

TABLE 6.4: SIMULATION RESULTS – BALDER RESIDENCE, HUS 2, FLOORS ... 45

TABLE 6.5: SIMULATION RESULTS – BALDER RESIDENCE, HUS 2, APARTMENTS ... 46

TABLE 7.1: SHADING DEVICE CHARACTERISTICS ... 49

TABLE 7.2: REFLECTIVE SHADING EFFECT ON THE BUILDING’S HEATING CONSUMPTION ... 50

TABLE 7.3: SHADING DEVICE CHARACTERISTICS ... 51

TABLE 7.4: SHADING DEVICE EFFECT ON THE BUILDING’S HEATING CONSUMPTION ... 52

TABLE 7.5: TESTED WINDOWS CHARACTERISTICS ... 53

TABLE 7.6: WINDOW’S TYPE EFFECT ON THE BUILDING’S HEATING CONSUMPTION ... 54

TABLE 7.7: TESTED INSULATION CHARACTERISTICS ... 55

TABLE 7.8: INSULATION THICKNESS EFFECT ON THE BUILDING’S HEATING CONSUMPTION ... 55

TABLE 7.9: HEATING SET POINT EFFECT ON THE BUILDING’S HEATING CONSUMPTION ... 56

TABLE 7.10: HEATING PROFILE EFFECT ON THE BUILDING’S HEATING CONSUMPTION ... 57

TABLE 7.11: OPTIMIZED SOLUTION – 1^ST MODEL DESCRIPTION ... 59

TABLE 7.12: OPTIMIZED SOLUTION – 1^ST MODEL RESULTS ... 59

TABLE 7.13: OPTIMIZED SOLUTION – 2^ND MODEL DESCRIPTION ... 60

TABLE 7.14: OPTIMIZED SOLUTION – 2^ND MODEL RESULTS ... 60

TABLE 7.15: GLOBAL OPTIMIZED SOLUTION - RESULTS ... 61

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1. INTRODUCTION

Energy consumption has become one of the biggest issues in the 21^st century. With the decrease of non-renewable energy resources, which leads to an increase of the energy price, but also with environmental issues, people, communities and governments are now aware that it is important to reduce our energy consumption. More particularly, the building sector consumes almost 30% of the world total final consumption. [IEA, 2008]

Even though technology can now answer almost all technical issues, and buildings are built more and more in a sustainable way, their energy performance still strongly depends on people’s way of living. Indeed, technology benefits may not even be apparent if occupants do not pay attention to their consumption and way of living. And this is an urgent problem the building sector is facing. [Mumovic et al, 2009]

Consequently, building occupants have to change their habits and live in a more sustainable way. Nevertheless, people do not have at the moment direct feedbacks about their own energy consumption, and therefore it is difficult for them to really pay attention to their energy consumption. In this context, electricity meters start to appear on the market, but there is no solution yet concerning hot water use in buildings.

The Royal Institute of Technology of Stockholm (KTH) and the Swedish housing company Nynäshamsbostäder AB are collaborating in order to assess the link between the visualization of hot water consumption and the consumption itself in municipal buildings.

This study aims to give a critical analysis of the current project measurements method leading to suggestions, to identify the heating consumption of the building under study in order to calculate how much savings can be made by changing tenants’ habits and by optimizing the technical components of the building envelope.

1.1. DESCRIPTION OF THE NYNÄSHAMN PROJECT

The commune of Nynäshamn, located around 60 kilometers south of Stockholm. To the south is a beautiful part of the Stockholm archipelago and to the north a varied cultural countryside. It counts some 25,000 inhabitants of whom 13,000 live in apartment blocks, situated in estates. With this amount of people living in apartment blocks, Nynäshamn offers a good location to assess the energy consumption in municipal buildings. [Nynäshamn]

Some companies are involved in the project. They will be presented right after the objectives of the project, which are:

- Analyse the energy use and energy-use behavior of various categories of occupants (tenants, municipal employees),

- Develop a methodology for energy-measurement and user-adapted visualization of the energy consumption,

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- Develop user- and building-adapted energy saving strategies and measures,

- Carry out energy-saving measures by way of information/education campaigns tailored to the needs of specific user categories, energy measurements, and user-adapted energy use visualization,

- Measure and document the energy savings achieved through these measures,

- Disseminate the experiences and results from this study to other municipalities and key stakeholders, as well as the general public, through seminats and publications in scientific and professional journals.

The first point was studied in previous reports [Wahlström, 2010].

1.1.1. NYNÄSHAMNSBOSTÄDER AB

Nynäshamnbostäder AB, the local and principal housing company in Nynäshamn, has been renting apartments since 1995 and owns around 2,700 apartments. Its heardquarters are situated in the town and the company employs around 30 people who are in charge of the payment of the rent, disturbances, key management and so on. Nynäshamn commune owns the company.

1.1.2. M^INOL

Minol is family-owned, long-established company and is one of the leading companies in meter reading and billing service worldwide. The company develops innovative metering solutions for heating, cold and hot water consumption as well as billing services. The company provides 5.4 million of bills each year, 1.3 million of those are for German households. By promoting the sensible and the efficient application of new technologies, Minol aims to contribute to a more consciencious use of valuable energy.

1.1.3. TYRÉNS

Tyréns is one of Sweden’s leading consulting companies in the urban and rural development sector.

The company provides highly qualified consulting services in the fields of housing, property development, IT and infrastructure. Tyréns operates in six markets: Urban and Rural Planning, Buildings, Industry, Infrastructure, Climate and Environment, and Water.

1.2. ENERGY SAVING BY VISUALIZATION PROCESS

Energy in households is difficult to control since it has become almost invisible to most people. Its consumption, through heating, water or electicity is now part of a routine of everyday’s life. And therefore it is hard to make efforts to live eco-friendly. By not paying attention and not being aware of their consumption, people domesticated energy consuming systems and got unsustainable habits. For instance to open a window when heaters are at high power level, or to leave the house/apartment with heaters on are common things that many people do. [Löfström, 2008]

In this context, and as already said before, it is important to assess the possibility of a change in human behavior by visualizing energy consumption. It is the main objective of the Nynäshamn project.

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The energy saving by visualization process can be divided into three main steps: measurements, visualization and saving measures. Throughout the process people and professionals are involved.

Figure 1.1 below illustrates the process:

Figure 1.1: Energy saving by visualization process

The final goal for this visualization process is to achieve reliable and smart measurements of energy consumption, real-time visualization to allow people having a direct feedback and adapted measures leading to long-term energy savings. The Nynäshamn project aims to make step forward in that direction. More particularly, this report focuses on the measurements, with an in-depth analysis of the measurement methodology applied to the project, and on the measures, giving an idea on how much tenants can reduce their own energy consumption.

2. OBJECTIVES

The first main objective of this thesis is to analyze the measurements methodology used for the Nynäshamn project, from the devices installed to the collection of the data. In this objective, the steps are:

- a description of the method and of the devices used - an analysis of the reliability of the method

- advices for future projects

Measurements

Visualization Feedback Measures

Devices Calculations

Display Environmental sensibilization Advices

Impact on rent

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The second main objective is to define the heating consumption of one of the municipal buildings under study. This will help other participants to carry-out energy saving measures as they will know how much they theoretically can save. This objective can be divided into two parts:

- creation of a computerized building model - simulations of heating consumption

The third and last objective of this study is to optimize the building’s envelope and tenants’ habits to reduce its heating consumption, based on the model and results of the second objective, by using DesginBuilder simulations. Isolation, windows and heating profiles will be assessed.

3. M^{ETHOD OF} ATTACK

First of all, a large literature review about measurements and visualization of hot water and energy consumption is needed. Also, a literature review on other projects similar to the one conducted in Nynäshamn is very useful.

Concerning the analysis of the measurement methodology of the project, error calculations will be made in order to assess its reliability. Therefore it is necessary to have information about the precision and the accuracy of the devices used, from the company that provides them which in that case is Minol. A contact with Minol technical responsible of the project is needed.

Third of all, the program DesignBuilfer will be used in order to evaluate theheating consumption of the building. DesignBuilder is a software that aims to help assessing impact of design decisions by making computer based building models at an early design stage. It allows to evaluate the energy consumption of a building and its carbon footprint, and thus can help to develop energy reduction and environmental friendly strategies. Indoor air quality, daylight factor and use of renewables can also be assessed, which gives the user important information on the coming building performances.

Here the building is already built and the software will be used to make a comparison of the theoretical and the actual energy consumption of the building.

The same program will be used to optimize the building enveloppe and to simulate changes on tenants’ habits.

4. LIMITATIONS

In chapter I, the focus is set on water heating systems, and more especially district heating system.

Other means of heating – like electrical heating or heat pumps – will not be assessed. This is due to the fact that the heating system used in Nynäshamn buildings is a district heating system, where the energy to municipal buildings is provided by a wood-pellets power-plant. It is assumed that all the apartments are only heated by the use of domestic radiators.

Mathematical formulas concerning energy in radiators are given in order to explain the measurment method. The aim is not to calculate the energy consumption of a radiator, but to

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evaluate errors when measuring and calculating his heating consumption. Therefore some parts of the formulas will not be deeply explained.

In chapter II, the model built with DesignBuilder had to be simplified due to student license restrictions. Indeed the building model should not have more than 50 zones or the simulations to determine the energy consumption are not available. However the building was fully designed first and then simplified.

Occupancy profiles were also simplified. Heat gains from equipment such as computers and tenants metabolisms were not taken into account. The aim is to have a continuous temperature of around 22°C in the apartment all year round.

Construction data, such as isolation components or windows, were not provided. This is the reason why common values were used to build the model. All constructions data are given later on in the related parts.

The aim of the study in chapter II is to give an idea of the minimum energy consumption of the whole building, and not to make prediction on its future energy consumption. Moreover DesignBuilder does not allow making predictions and it bases its calculations on previous meteorological data. Here temperatures of year 2002 are used to assess the energy consumption, not only in Chapter II but also in Chapter III. It is assumed that there would not be a large difference when using another temperature set.

In chapter II and III, simulations on energy consumption only takes into account heat losses through walls, windows and roof and heat losses due to infiltration. Since the ventilation system was not under study, the heat losses due to ventilation were not taken into account. This has to be kept in mind since these losses represent a large part in the energy consumption of the building. Therefore all the figures given in this report are expected to be lower than common values. To compare with common values that include heat losses due to ventilation, the reader can divide the heating consumption figure by 0.8 since usually the ventilation losses represent around 20% of the heating consumption.

In chapter III, the economical issues of the energy performance optimization is not taken into account because of lack of information. Indeed it is almost impossible to have good estimations or prices for products in such a short time. Instead of quantitative studies, qualitative estimation have been made in order make reader remember that the economical factor remains one of the most important factor when optimizing the building envelope.

Regarding heating profiles, a common domestic family has been chosen to represent the tenants living in the apartments. That means that they will be out of work during the day on weekdays.

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5. C^HAPTER I:HEATING AND HOT WATER CONSUMPTION MEASUREMENTS

In many cases, heat is provided to houses and apartments through water. As pointed out in the limitations paragraph, other ways of heating – electrical, heat pumps – will not be assessed.

Depending on the system used, the water can be heated by an individual water heater or by a power-plant if district heating is used. The focus of the study is put onto district heating systems.

There are two ways of determining the heating and hot water consumption of a habitation:

- direct method – calculating the energy provided by the energy source, for instance by a domestic water heater or by a power-plant

- indirect method – measuring variables, like temperature, pressure or flow rate, in order to calculate the energy consumed

The direct method corresponds to the most reliable way of evaluating the energy consumption, since it does take into account all the losses in the system. In the case of district heating, however, this method does not allow an individual measuring system, i.e. it gives access to the energy consumption of all the apartments connected to the district heating system but not to the energy consumption of one individual apartment. This is the reason why the indirect method has to be used.

Using the indirect method, the best solution to determine the consumption is to measure the flow and the temperature difference:

^ = ^ ∗ _∗ ∆ Eq. 1

Where:

- Q is the energy consumed - m is the mass flow of water used

- C_p is the specific heat of water at mean temperature - ΔT is the temperature difference

The specific heat of water is temperature dependent and can be known from tables. Therefore measurements of the mass flow and the temperatures gives access to the energy consumed. In an ideal project, measurements of these two factors with minimal errors would be done.

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5.1. CENTRAL HEATING TECHNOLOGY DESCRIPTION

Most of Nynäshamnsbostäder’s apartments use the same central heating system, which is described in this part.

A wood pellets-driven power plant provides the heat to meet hot water and heating needs. The hot water from the plant goes through two heat exchangers in each apartment, one for the heating and the other one for the hot water, and then returns to the power plant. The total mass flow remains constant and thus only the temperature of the return water changes. The total heat consumption is recorded and is available for Nynäshamnsbostäder and for the energy supplier, Fortum.

Figure 5.1 below illustrates the central heating system:

Figure 5.1: Central heating system used by Nynäshamnsbostäder

Only the amount of heat given at the residence scale is accessible for Nynäshamnsbostäder, who then evaluates the consumption of each apartment proportionally regarding several criteria, for instance the area of the flat or the number of persons living in the apartment. The goal of the housing company is to monitor the energy consumption of each flat, having a more accurate process and creating separated bills for cold water, hot water and heating. [Leconte, 2009]

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5.2. HEATING CONSUMPTION

5.2.1. DESCRIPTION OF THE MEASUREMENT METHOD

The method described in the chapter’s introduction could not be applied in this case. The reason is that there are space constraints and devices that measure water flow and its temperature could not be installed.

In order to calculate the heating consumption of an apartment, a device called Minometer M6 is used. Figure 5.2 below shows the measuring device.

Figure 5.2: Minometer M6

A Minometer M6 is placed on every radiator in the apartment. It measures the radiator’s and the room’s temperatures. The Minometer M6 detects very small changes in temperatures, thanks to very precise sensors. External sources of heat are excluded from measurements by doing series of plausibility checks with the logged room and radiator temperatures. [Minol]

Information are sent and stored in two other devices, the Minomat S and Minomat M. Figure 5.3 illustrates the process.

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Figure 5.3: Collecting and sending data with Minometer M6 and Minomat S/M [Minol]

The Minomat M sends the data to Minol center. These data are accessible by the client and by the company which can then create bills.

5.2.2. CONSUMPTION CALCULATIONS

Heating consumption calculations are made following a document provided by the company Minol which is in charge of the consumption measurements and calculations and which is given in Appendix 1.

It is assumed that the apartments are only heated by the use of domestic radiators, as stated in the limitations. The total heating consumption is the sum of the energy consumed by each domestic radiator, as shown in Equation 2:

 =
 ,





Eq. 2

Where:

- Q_heating is the energy consumed for heating - Q_radiator is the energy consumed by one radiator - n is the number of radiators in the apartment

The heating consumption of a radiator can be calculated with Equation 3:

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  =


_

  Eq. 3

Where:

- Q_r (dot) is the power of the radiator - τ represents time

Radiator power can be calculated by using the two following equations:

=
. ∆!

59,44%



Eq. 4

∆!= !&− !

() *!^&− !+

!− !+, Eq. 5

Where:

- Qnorm (dot) is the radiator power under normal conditions

- t_v, t_r and t_l are respectively the entering flow, the return flow and the ambient room air temperatures

- Δtm is the mean temperature difference

- 59,44 corresponds to the logarithmic mean temperature at standard conditions - n is the radiator exponent

The radiator power under normal conditions is assessed once or is given by the radiator provider.

The Minometer M6 does not allow measuring flow temperatures and Minol has to approximate the energy consumed by the radiator with the two following equations, in which the integral of Equation 3 is replaced by a sum and the power of the radiator is calculated from its temperature and the room air temperature.

 =
. -.− / Eq. 6

=
. 01. -!2− !+/

59,44 3^ Eq. 7

17 Where:

- k is a correction factor

- t_hk and t_rl are respectively the radiator and the room air temperatures - n is the radiator exponent

The correction factor is determined when the measuring device is installed, by measuring the flow temperatures with special devices. The mean temperature difference Δt_m is calculated and the correction factor is derived from it. As this correction factor will not interfere with the next part which treats error and uncertainty calculations, the calculations of the energy consumption of radiators will not go any further on.

5.2.3. ERROR CALCULATIONS

This part aims to give an approximate value of the total error induced by the measurement and the consumption calculations methodology. Relative errors will be assessed, calculated or assumed when it is impossible to get the right value, trying to be as realistic as possible.

5.2.3.1. HYDRAULIC SYSTEM HEAT LOSSES

This measurement method evaluates the end-use heating consumption of the apartment. It means that all the losses which take place in the hydraulic system are not taken into account. In other words, the heating consumption measured is lower than it should be if all the losses are in the calculations.

The heat losses occurring in the hydraulic system – from the power-plant to the individual apartment – are negligible. Moreover, as soon as the measurements are made for each apartment, these losses are not taken into account anyway. Suggestions on how to include them in the consumption bill will be given later in this report.

5.2.3.2. DEVICE ERROR

Measuring a physical quantity is not an easy task. There always are errors when using a measuring device, no matter which one is used. A better device will only gives a lower error. Three main kinds of error can be seen, to which the human factor has to be added:

- resolution: represents the smallest interval of the scale with which the quantity is measured - precision: corresponds to the statistical dispersion of the measures

- accuracy: linked to the systematic error when measuring

This will create a final error when looking at the measured value. For instance, someone is measuring the light velocity. The value considered to be true nowadays for the light velocity is:

4₅ = 299792 1. 9^:

18 The value measured is:

4 = 300000 1. 9^:

The absolute error is:

∆4 = |4 − 4₅| = 208 1. 9^:

The relative error is:

∆4

4₅ = 208 1. 9^:

299792 1. 9^: = 0,07%

However, most of the time the real value is unknown, as in our case when measuring temperatures, and so uncertainty calculations are used. The uncertainty of the measurement corresponds to the maximal error, objectively approximated from how the measurement has been made. As a simplification, it is common to consider that the uncertainty of a device is the same as its resolution.

Table 5.1 below gives calculation steps that will be used later on.

TABLE 5.1:BASIC UNCERTAINTY CALCULATIONS FORMULAS

Operation X ΔX (absolute error) ΔX/X (relative error)

Sum a+b Δa+Δb (Δa+Δb)/(a+b)

Difference a-b Δa+Δb (Δa+Δb)/(a-b)

Product a*b a.Δb+b.Δa Δa/a+Δb/b

Quotient a/b (a.Δb+b.Δa)/b² Δa/a+Δb/b

Power aⁿ n.a^n-1.Δa n.Δa/a

Constant k 0 0

Using Table 5.1, Equation 6 gives:

∆
 

  = ∆
_
^

 + ∆_-^{-.− /}

.− / Eq. 8

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The device only measures the temperatures in order to calculate the power output of the radiator.

Therefore the relative error of the time term is null.

∆
 

  = ∆
_
^

 Eq. 9

From Equation 7 and Table 5.1:

∆


 = ∆
_
^

 + ).∆AA Eq. 10

Where:

A = 01. -!2− !+/

59,44 3 Eq. 11

The power output under normal conditions is measured only once and the same value is used for all the other calculations. The error due to this term is considered to be negligible. And so Equations 9 and 10 lead to:

∆
 

  =).∆AA Eq. 12

The relative error of A-term is calculated from Equation 11 and Table 5.1:

∆A A ⁼

∆-!_ℎ1− !_C(/

-!ℎ1− !C(/ Eq. 13

This leads to:

∆A A ⁼

∆!ℎ1+ ∆!C(

-!ℎ1− !C(/ Eq. 14

Finally, the relative error induced by the measurement of one radiator’s consumption is:

∆
 

  = ).∆!2+ ∆!+

-!₂− !+/ Eq. 15

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The radiator exponent is chosen to be 1.3, which is a common value for radiator’s exponent.

[Grundfos]. It is accepted that the calculation method takes into account the heat losses in the radiator through the radiator exponent. The heat losses in the radiator will vary with its temperature. Indeed the radiator’s efficiency changes according to its temperature. Without calculations, these losses are extremely difficult to evaluate. A change of the radiator exponent would induce a very small error and then is considered to be negligible.

It is assumed that the resolution of the Minometer M6 is of 0.1°C. As the room and radiator temperatures are unknown and that they will influence the result, it is necessary to assume two realistic couples of temperature that will minimize and maximize the error. The calculations are made when the radiator is turned on. These couples are (t_hk, t_rl)_min = (70,20) and (t_hk, t_rl)_max = (40,20). The minimum relative error induced by the device resolution is:

∆
 

  = 1.3.0.1 + 0.1 70 − 20

∆
 

  ≈ 0.5%

The maximum relative error is:

∆
 

  = 1.3.0.1 + 0.1 40 − 20

∆
 

  ≈ 1%

5.2.3.3. ROOM TEMPERATURE

The Minometer M6 measures both radiator and room temperatures. Measuring the surrounding temperature very close to the radiator might give a higher temperature than the actual room’s temperature. This will give a smaller temperature difference, and using Equation 2, will lead to lower energy consumption.

Equation 15 can be used also here to calculate the error induced by this. In this case, the error in the radiator’s temperature measurement is null. The two couples of temperatures used before to assess minimum and maximum errors are used here too. An error of 1°C in the room’s temperature measurement will lead to a minimum error of:

21

∆
 

  = 1.3. 0 + 1 70 − 20

∆
 

  ≈ 2.5%

The maximum relative error is:

∆
 

  = 1.3. 0 + 1 40 − 20

∆
 

  ≈ 6.5%

As it can be seen, this leads to a very high error. Moreover, the error in the room’s temperature measurement might even be higher than 1°C, which would lead to a higher relative error in the radiator energy consumption. For instance, during the winter, when the radiators have been turned off for a while and the room is very cold, there might be a very high difference between the temperature measured close to the radiator and the room temperature itself, which may be more than only 1°C. The error induced in this case might be really high. Supposing a temperature difference of 5°C, the minimum error is:

∆
 

  = 1.3. 0 + 5 70 − 20

∆
 

  ≈ 13%

22 The maximum relative error is:

∆
 

  = 1.3. 0 + 5 40 − 20

∆
 

  ≈ 32.5%

This would have a considerable effect on the energy consumption measurement.

5.2.3.4. NUMBER OF RADIATORS

According to Table 5.1 and Equation 3, the relative error of the heating consumption would be:

∆
 

  =∑ ∆
  ,

∑
  ,

 Eq. 16

As the absolute errors and the energy consumptions of the radiators cannot be calculated in this report, the relative error of the heating consumption cannot be assessed in this way. A simplifying assumption is to consider that all the radiators have the same absolute error and the same energy consumption. This leads to:

∆
 

  =∆
 

  Eq. 17

Therefore, making this assumption, the relative error of the heating consumption can be approximated by the relative error of one radiator.

5.2.3.5. SUMMARY

Table 5.2 below summarizes the errors induced by the heating consumption measurement method.

23 TABLE 5.2:ERRORS IN THE HEATING CONSUMPTION MEASUREMENT

Cause Value

Hydraulic system losses Not taken into account

Device (resolution) 0.5% - 1%

Room’s temperature measurement 2.5% - 32.5%

Total 3% - 33.5%

These results show that the error induced by Minometer M6 can be really high. It is not due to the device’s resolution but to the method of measurement, and more especially to the fact that the room temperature is measured by the same device that measures the radiator’s temperature.

5.3. HOT WATER CONSUMPTION

5.3.1. DESCRIPTION OF THE MEASUREMENT METHOD

The hot water consumption is measured with a Minomess water meter, illustrated in Figure 5.4 below.

Figure 5.4: Minomess water meter [Minol]

Two Minomess are installed in each apartment, one for cold water and one for hot water. They could be installed in this way because the installation was done during the construction of the building. Usually Minol provides at least four Minomess, two in the kitchen and two in the bathroom. Minomess only measures the water flow, and the temperature is assumed, like in this case, to be 50°C for hot water. It is equipped with radio transmission, like the Minometer M6 so Minol can treat the information.

One thing that it is important to notice is the fact that the Minomess water meters could easily do temperature measurements if they were equipped to do so. Since they already measure the flow, it would not involve a lot of changes to measure the water temperatures, and the Minomess water meters would be much more accurate and therefore much more efficient.

24 5.3.2. CONSUMPTION CALCULATIONS

The hot water consumption is calculated with Equation 18 below:

_{ℎH! IJ!KC}=∗ ∗ ∆ Eq. 18

Where:

- Q_{hot water} is the energy consumed - m is the mass of water

- Cp is the specific heat of water at the mean temperature - ∆T is the temperature difference

The mass of water derives from the volume (or flow if time is taken into account) measured by the Minomess:

=L∗M Eq. 19

Where:

- q is the volume of water

- ρ is the density of water at the mean temperature

With Equation 18 and Equation 19, it is possible to calculate the hot water energy consumption from Minomess measurements and from tables.

5.3.3. ERROR CALCULATIONS

As said before, the water density and specific heat are temperature dependent. However, both vary very slowly in the temperature range treated in this report, and therefore their effect on error calculations will not be assessed.

In this part, two factors will be taken into account: the effect of the Minomess resolution and a change in the hot water temperature, set at 50°C.

Using Table 5.1 “Basic uncertainty calculation formulas” presented in part 5.2.3.2., and following the same methodology as previously, the relative error of hot water consumption is:

∆
_{ℎH! IJ!KC}

_{ℎH! IJ!KC} = ∆_L^L+ ∆^!+∆!

-!− !/ Eq. 20

Where:

- t_e and t_i are respectively the entering and the return water temperatures 5.3.3.1. DEVICE ERROR

25

Minomess only measures the volumetric flow and its resolution will only affect the term in q in Equation 20. The relative error due to Minomess, according to its description document given by Minol [Minol], is 5%.

∆L

L = 5%

5.3.3.2. TEMPERATURE ASSUMPTIONS

The entering and return water temperatures need to be assumed in order to calculate the hot water energy consumption. Minol sets the entering water at 50°C and the return water temperature is assumed to be 20°C, which corresponds to a common mean ambient temperature.

If there is a cumulated temperature difference of 5°C, for instance the entering water is at 54°C and the return water is at 21°C, this leads to a relative error of:

∆!_K+∆!_C

-!K− !C/ = 4 + 1

54 − 21

∆!_K+∆!_C

-!K− !C/ ≈ 15%

5.3.3.3. SUMMARY

Table 5.3 below summarizes the errors induced by the hot water consumption measurement method.

TABLE 5.3:ERRORS IN THE HOT WATER CONSUMPTION MEASUREMENT

Cause Value

Device (resolution) 5%

Temperature assumptions 15%

Total 20%

Here again, the error induced by the measurement can be high. Not because of the device resolution but more because of the methodology. Assuming temperatures in this case can lead to high errors.

26

5.4. CRITICAL ANALYSIS AND SUGGESTIONS FOR FUTURE PROJECTS

The measurement of the heating and hot water consumption will become more and more important in the future in order to reduce people’s energy consumption. To be able to evaluate the effect of the visualization of the energy consumption, it is important that the measurements are as accurate as possible. If it is not the case, the efforts that people make to reduce their own consumption might not be visible and therefore they can be dissuaded to pursue them.

Two cases have to be separated: a case like Nynäshamn project where the heating and hot water systems are already built, and new projects and buildings that can be thought in the way that the heating and the hot water consumption will be measured. These two cases correspond to the subject of the following paragraphs.

5.4.1. EXISTING BUILDING:NYNÄSHAMN PROJECT CASE

In existing building, heating and hot water systems were not imagined to be measured in a specific way. This leads to constraints, for instance space constraints, when measurement devices have to be installed to assess the energy consumption. In Nynäshamn buildings, central heating systems were installed and thus the measurement of the energy consumption of each apartment remains an issue. Minol offered a solution that has its advantages and inconvenient. They are listed in Table 5.4 below.

TABLE 5.4:ADVANTAGES AND INCONVENIENT OF THE MEASUREMENT METHOD IN NYNÄSHAMN PROJECT

Heating consumption: Minometer M6

Advantages Inconvenient

- Can be installed in existing systems - Facility of installation

- Radio equipment to send figures

- Accuracy (measurement method) - End-use measurements

- Many devices (not only one for the whole apartment)

- Not suitable for real-time visualization

Hot water consumption: Minomess

Advantages Inconvenient

- Can be installed in existing building (in each room)

- Radio equipment - Flow measurement

- Accuracy (measurement method) - Not suitable for real-time visualization

27

As described in Table 5.4, the measurement method used for Nynäshamn project is more suitable for a new billing process than for assessing the effect of the visualization on the energy consumption. Indeed, the measurement method of the consumption can lead to high errors than can disturb the efforts made by the tenants to reduce their energy consumption. The errors are not due to the devices but more to the measurement method, more especially to temperature measurements. Also this method uses a lot of devices in order to measure the energy consumption in the apartment, so the tenants can be confused and not be interested in checking all the figures.

For future projects that aim at measuring the heating and hot water consumption in an existing building to evaluate the impact of the visualization, some devices can be useful:

- Choose devices that are suitable with real-time visualization, or at least that can be followed by tenants

- Remember that the accuracy of the measurements is really important in order to make people visualize their smallest efforts. Best devices measure the flow and the temperature - Divide the energy consumption into two parts: heating consumption and hot water

consumption. A third part could be the electricity consumption

28 5.4.2. NON-EXISTING BUILDINGS:NEW PROJECTS

Energy consumption measurements should be included in the study and the choice of the heating and hot water systems. If so, measurement method and devices could be chosen and developed in collaboration with architects, builders and engineers.

Table 5.5 below lists the different characteristics and advices on how the measurement method should have in future projects:

TABLE 5.5:MEASUREMENT METHODOLOGY IN NON-EXISTING BUILDINGS – FUTURE PROJECTS

Period Advices

Before construction

- Build the hydraulic system in order to make flow and temperature

measurements available (single entering pipe, space constraints…)

Building lifetime

- Choose devices that are suitable with real-time visualization (accuracy, system of visualization…)

- Transmission equipment to have individual bills

- Separate heating, hot water and cold water

Real-time visualization is not treated here, but many works have been done about it. PhD thesis

“Visualisera energi i hushåll” by Erica Löfström gives deep information on the subject. [Löfström, 2008]

5.5. CONCLUSION

Minol found here a very good solution to make individual bills for tenants, which was an objective for Nynäshamnbostäder. However, real-time visualization is not possible with this methodology since the tenants cannot have access to their own energy consumption. Minol is responsible of showing the figures to the tenants, since they control the measuring devices. This is very penalizing for the project since a system for the visualization itself must be found in some way.

According to Equation 7, if the room’s temperature is overestimated, the power of the radiator would decrease. Consequently the heating consumption should decrease and the energy bill would too. However it seems that Minol considers that when the room temperature is higher, it involves that the tenants are using more energy to heat their own apartment, and so their energy bill will be higher. The room temperature is not only dependent on the radiator power, since other heat gains have to be taken into account, such as appliances, heat gains through windows and so on. This is actually of one the primary issues that Minol should answer.

29

In heating and hot water measurements, the best methodology that insures a good accuracy consists in measuring the flow and the temperature. Ideally, heating and hot water consumption should be separated so tenants can have access to both values. With real-time visualization, they would see the effect of their lifestyle on their consumption and could then try to change their habits in order to reduce it.

As seen in this first chapter, such a methodology is not really feasible with existing buildings.

Measurements and visualization issues must ideally be taken into account before the construction of the building, in the study process. Regarding all the constraints, Minol offers a good measurement method for individual billing process.

Tenants will make efforts to reduce their energy consumption; however they often do not know how far they could go. The subject of the second chapter is to determine the minimal heating consumption of a building in Nynäshamn by modeling.