5.4. individual reports on the monitoring results ... · pdf file4.1 energy monitoring points...

Dissemination level X PU = Public

PP = Restricted to other programme participants (including the JU) RE = Restricted to a group specified by the consortium (including the JU) CO = Confidential, only for members of the consortium (including the JU)

5.4. Individual reports on the monitoring results Residential building - Roth Fastigheter 16 November 2016

Authors: Carolina Faraguna - IVL Swedish Environmental Research Institute

IVL Report No. E 004

BUILDSMART Monitoring results - Roth Fastigheter D 5.4.

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Disclaimer

The information in this document is provided as is and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability.

The document reflects only the author’s views and the Community is not liable for any use that may be made of the information contained therein.

Document history V Date Author Description

1.0 2016-11-01 CF First version 2.0 2016-11-11 EG Review


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Summary

Build Smart - Energy Efficient Solutions ready for the market"(BuildSmart) is a collaborative, demonstration project funded by the European Commission. The objective of BuildSmart is to demonstrate and mainstream cost effective techniques and methods for constructing buildings with very low energy demand. This is in accordance with the accepted EU directive regarding energy performance of buildings (EPBD II).BuildSmart includes low energy residential and commercial buildings constructed in Sweden and Spain.

The BuildSmart project defines a common structure for measurement, analysis and monitoring the energy performance of buildings. Measurements are reported for at least one year, starting from the day when the building is in operation.

An important part is to analyse the discrepancy between calculated and measured energy performance. Measured data is used to verify the building’s energy performance and operation and to analyse the environmental impact. Furthermore, monitored energy data is transformed into energy performance indicators which are used to compare different buildings with each other. The measured energy is documented with two different indicators, i.e. final energy and primary energy. Finally, the climate impact related to the energy consumption is evaluated.

This report compiles and visualises the results of the measurements for the residential building built by Roth Fastigheter.

.


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Contents 1 Background ...................................................................................................................................... 5

2 Introduction and purpose of the report .......................................................................................... 5

3 Case study - Roth Fastigheter, residential building ......................................................................... 5

4 Monitoring strategy ......................................................................................................................... 7

4.1 Energy monitoring points for residential buildings ................................................................. 7

4.2 Data handling routines .......................................................................................................... 10

5 Quantitative evaluation ................................................................................................................. 10

5.1 Climate normalisation ........................................................................................................... 10

5.2 Energy signature .................................................................................................................... 11

5.3 Building energy performance indicators ............................................................................... 11

6 Energy use ..................................................................................................................................... 12

6.1 Calculated energy performance ............................................................................................ 12

6.2 Monitored energy performance............................................................................................ 13

6.3 Discrepancy between calculated and monitored energy performance ................................ 14

6.3.1 Energy signature ............................................................................................................ 14

6.3.2 Electricity, EUM ............................................................................................................. 15

6.3.3 District heating, DHM .................................................................................................... 16

6.3.4 Solar thermal, OST ......................................................................................................... 17

6.3.5 Heat for domestic water, TDHW ................................................................................... 18

6.3.6 Final energy ................................................................................................................... 19

6.4 Indicators ............................................................................................................................... 20

7 References ..................................................................................................................................... 21

Appendix A Heating degree days ...................................................................................................... 22

Appendix B District heating statistics for E.ON Malmö värme 2015 ................................................ 23


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1 Background The building sector is responsible for significant energy consumption. Construction and use of buildings within EU account for more than 40% of the total energy use [1][2]. Hence, the potential for energy efficiency measures is big.

EU has passed a directive to improve the energy performance of European buildings, the “directive on the energy performance of buildings” or “EPBD II” for short. Amongst other things, the directive requires that all new buildings that are used and owned by public institutions must be nearly zero-energy buildings from 2019. The nearly zero standard applies to all other buildings from 2021 [3].

Build Smart - Energy Efficient Solutions ready for the market"(BuildSmart) is a collaborative, demonstration project funded by the European Commission within the Seventh Framework Programme. The objective of BuildSmart is to demonstrate and mainstream cost effective techniques and methods for constructing very low energy buildings. This is in accordance with the accepted EU directive regarding energy performance of buildings (EPBD II) [4].

BuildSmart includes low-energy residential and commercial buildings constructed in Sweden and Spain [4]. The buildings are characterised by very low total energy consumption. Dense envelopes create high air tightness and low energy losses. Local renewable energy production in combination with energy efficient installations like heat recovery systems and heat exchangers, for heating and cooling ventilation air, reduce the need for bought energy [5].

The BuildSmart idea is to combine existing and tested technologies in a new way to show cost effectiveness and a high replication potential.

2 Introduction and purpose of the report An important part of the BuildSmart project is to develop a common structure for measurement, analysis and monitoring of energy performance of buildings. A common structure is necessary to compare results from different building projects and different climate zones. All monitored data will be reported by the local partners in the accepted reporting format. Measurements are reported for at least one year, starting from the day when the building is in operation.

This report compiles and visualises the results of the measurements for the residential building built by Roth Fastigheter.

3 Case study - Roth Fastigheter, residential building The residential building by Roth Fastigheter is located in the district of Hyllie, which is a new city district in the south of Malmö. Hyllie is built around a new rail station and rail link to central Malmö and Copenhagen.

The residential building was ready for moving in, in November 2013. It consists of three houses with varying height and a total of 53 apartments, see Figure 1. The size of the apartments varies from one


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room apartments of 35 m² up to four room apartments of 119 m². However, the majority of the apartments are two room apartments of 63-72 m² and three room apartments of close to 90 m².

The interior area of all floors, attic floor and basement that is heated to more than 10°C, Atemp, is 4740 m2. Atemp is defined in the Swedish building regulations, BBR [6].

The building is designed to have a very low, close to passive house standard, energy consumption. A combination of building design, modern energy saving techniques and renewable energy sources will be used to reach the target.

The building envelope is well insulated to reduce the need for heating. The house is equipped with solar panels to heat hot water. The ventilation system is mechanical and has a heat recovery system, where the hot exhaust air is used to heat the incoming air. Furthermore, the air can be filtered in the heat exchanger unit. Temperatures, pressures and flows are set and monitored by a control system. The system is designed so that the temperature can be adjusted in all rooms and apartments. The lighting system is equipped with presence control to further reduce the energy need.

Hot tap water, heat and electricity use is measured in each apartment. The energy consumption and cost thereof can be followed on information screens in the hallway, on the computer or with a mobile app.

All apartments are equipped with washing machines, hence it is expected that common electricity usage will be lower than for residential properties with common laundry rooms.

The building will be connected to the smart grid of the Hyllie area. The smart grid includes a load shift control system that steers energy use in the district for economic optimization.


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Figure 1 The residential building of Roth Fastigheter.

4 Monitoring strategy Energy use is monitored and reported according to the BuildSmart monitoring strategy [4]. The energy performance is divided in the following four main categories: bought energy, sold energy, produced energy and used energy. For the Roth building no energy is sold. The solar panels are used to heat tap water in the building.

When applicable, climate normalisation is done according to the method defined by SCIS [8].

4.1 Energy monitoring points for residential buildings The metering points are divided in three groups: basic metering extended metering and advanced metering points. The basic points represent points that are required to be metered in Sweden. The extended points and the basic points represent the necessary metering points to fulfil the goals in the BuildSmart project. Finally the advanced points are points that can provide a deeper knowledge of the energy performance of the building [4]. A schematic overview of the metering points is shown in Figure 2. Table 1 briefly explains what the different meter points in the previous figure represent.


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*If applicable and if not measured indirectly by subtraction of other meter data

Green points represent basic metering requirements in Sweden.

Yellow points represent additional metering points needed to meet the goals within the frame of the BuildSmart project.

Orange points represent advanced metering options that can provide information for a more detailed analysis of the building’s energy performance.

Figure 2 Schematic overview of metering points in dwellings


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Table 1 Meter table

DCM District Cooling Meter (Energy amount and temperature on supply and return flow rate)

DHM District Heating Meter (Energy amount and temperature on supply and return flow rate)

EUM Electricity Utility Meter

EXC EXCluded energy (cannot be allocated to the building’s energy use)

FM Fuel Meter (e.g. utility gas meter or documenting of delivered stored fuel)

IE Individual Electricity

AHU Air Handling Unit data (Air flow rate, electricity use, heating and cooling supply and heat recovery data)

CD Conversion Data (operation parameters heat pumps, boilers etc.)

DC Distributed Cooling

DE Distributed Electricity

DSH Distributed Space Heating

IAQ1 Indoor Air Quality (Ventilation flow rate and indoor temperature)

IDHW Individual Domestic Hot Water metering

LC1 Local Climate (air temperature)

LPE Locally produce electricity

OST On site Solar Thermal used in building

SE Sold Electricity: PV, wind power, CHP - electricity

TDHW Total Domestic Hot Water production energy

IAQ2 Indoor Air Quality (CO2 concentration)

LC2 Local Climate (solar radiation, wind speed, wind direction, humidity)

OP Operation Parameters (operation mode monitoring on advanced regulation of sun shielding, Trombe walls etc.)

ISHC Individual Space Heating and Cooling metering

LHS Local Heat Source (e.g. ground or air)

HRL Heat Re-Loading (Solar thermal heat for ground storage/reloading)

CL Conversion Losses


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4.2 Data handling routines Roth has compiled measured data on a monthly basis and sent it to IVL Swedish environmental institute, for analysis. IVL is responsible for analysis and reporting to Smart Cities Information System, SCIS [9]. SCIS is supported by the European Commission and a continuation of the Concerto projects. After the BuildSmart project has finished, the respective partners are responsible for reporting any outstanding data points to SCIS.

5 Quantitative evaluation Measured energy-related building data is used to verify the building’s energy performance and operation and to analyse energy performance regarding environmental impact. It is however necessary to post-process the energy usage data and to take varying climate into consideration. Finally, monitored energy data is transformed into energy performance indicators which are useful in comparison with other buildings [7].

5.1 Climate normalisation The energy consumption of a building varies from year to year. The main reason is that the outer climate is different from year to year, i.e. the outside temperature varies from year to year. On a cold year the need for heating energy increases and vice versa. To compare data from different years it is necessary to compensate for the external climate. This is called climate normalisation. Please note that only the climate-dependent energy use, e.g. energy for heating, should be compensated [11].

Different countries in Europe use different methodologies for to carry out climate normalisation. This means it is difficult to compare measurements from different countries. SCIS has therefore defined a common methodology for correction based on the standard concept of heating days [8].

𝐻𝐻𝐻𝐻𝐻𝐻18 15⁄ = �(18°𝐶𝐶 − 𝑡𝑡𝑎𝑎)𝑧𝑧

1

𝑡𝑡𝑎𝑎 =𝑡𝑡𝑚𝑚𝑚𝑚𝑚𝑚 + 𝑡𝑡𝑚𝑚𝑎𝑎𝑚𝑚

2

𝐻𝐻𝐻𝐻𝐻𝐻𝑡𝑡𝑖𝑖 𝑡𝑡ℎ𝑡𝑡⁄ Heating degree days for a time period with z heating days (ambient air temperature being below the heat threshold temperature, 𝑡𝑡ℎ𝑡𝑡).

𝑡𝑡𝑚𝑚 Inside set temperature of the building

𝑡𝑡ℎ𝑡𝑡 Inside set temperature of the building

𝑡𝑡𝑎𝑎, 𝑡𝑡𝑚𝑚𝑚𝑚𝑚𝑚, 𝑡𝑡𝑚𝑚𝑎𝑎𝑚𝑚 Daily average, min and max ambient air temperatures

𝑧𝑧 Number of heating days in the time period

This method will be used for climate normalisation of data in the BuildSmart project. The arithmetic mean is calculated with data from one of the Swedish meteorological institute’s (SMHI) measuring stations in Malmö, see Appendix A.


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5.2 Energy signature The energy signature, of a building is a tool to gain knowledge about the energy relations existing in the building and to visualize its energy performance. The method is based on the buildings real energy balance and reflects its heating technical properties [11].

Here the energy signature constructed by plotting the monthly energy consumption against average outside temperature for the month, i.e. the outside temperature on the x-axis and the corresponding energy consumption on the y-axis. Obviously the energy consumption varies with the size of the building. To enable comparison between buildings the energy consumption can easily be divided by the heated area, Atemp.

Straight lines are drawn through the measured data points, one during the heating season (heating on, cooling off), the cooling season (cooling on, heating off) and intermediate season (both off), respectively. If there is no cooling only two lines are drawn. The crossing of the lines represents the set points or balance temperatures where heating is switched on and off. The same is true for cooling. The intermediate region will manifest itself as a horizontal line and displays the climate-independent energy use, e.g. tap hot water and losses in hot water circulation. Heating and cooling seasons will be represented with inclined lines. The slope of the line is a measure of the energy loss through the climate envelope through transmission and ventilation. A steep slope indicates a poorly insulated building and a slight inclination the opposite. A truly passive house would manifest itself as a horizontal line. The balance temperature is always lower than the indoor temperature and every building has its own balance temperature. Please note that a balance temperature only exists if there is a heating or cooling system.

Please note that energy signatures are drawn with data that hasn’t been climate normalized. Furthermore, an energy signature can be draw using the total energy usage. Here, the energy used for hot tap water is subtracted to visualise the performance of the building envelope.

5.3 Building energy performance indicators The measured energy is documented with two different indicators, i.e. final energy and primary energy. Furthermore, the climate impact of the energy consumption is calculated. The climate effect is calculated as equivalent emitted carbon dioxide in relation to the energy delivered to final customer.

The resulting energy performance indicators for the BuildSmart project are:

• annual primary climate normalised energy use / m2 • annual climate normalised CO2 emission equivalents / m2

The heated area, Atemp, will be used to normalise the indicators.

The transformation from energy consumption to primary energy is done with so called primary energy factors, see Table 2. Similarly, the CO2 emissions are found by multiplying with a CO2 emission factors. The latter are also listed in Table 2.


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Table 2 PE and GWP factors

PE factor [-] GWP factor [ton CO2/GWh] District heating 0.52 151 Electricity 2.1 160

The Roth building receives district heating from E.ON Värme Sverige AB’s net. Fuel statistics from 2015 are used to calculate the energy and emission factors, see Appendix B.

The primary energy and emission factors for bought electricity assume Nordic average mix [10].

To get comparable indicators within the BuildSmart project the following points must be considered:

• account for bought energy • no discount for on-site produced exported energy • exclude household/tenant electricity • account for bought energy supplied to the building for heating, cooling, hot water, common

laundry rooms, and for operating building installations (pumps, fans, etc.) and other electricity for the property (excluding household electricity, tenant specific electricity use and energy use strictly separated from the building such as car heaters and car battery loading).

For the Roth building this means that primary energy and environmental impact are calculated from bought electricity (EUM) and bought district heating (DHM) since user electricity, IE, is not included in EUM.

6 Energy use IVL has developed templates for reporting and comparing calculated and measured energy use, a CSV file and a yearly overview of the building energy use [4].

After collecting the monitored energy data the results should be analysed. They should be normalized, and compared to the predicted values.

Normalized data should in the end be recalculated to express values for the energy performance indicators.

6.1 Calculated energy performance Roth Fastigheter has employed Structor Bygg Malmö AB to perform the energy simulation of the building. The results are shown in Table 3. All values are calculated for a normal year.


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Table 3 The Roth building’s calculated energy performance for a normal year.

6.2 Monitored energy performance The measured energy performance is listed in Table 4. Extended meter information is listed in Table 5.

Table 4 Measured energy performance for the Roth building 2015.

Sold energy

Electricity utility meter

Fuel utility meter

District cooling utility meter

District heating utility meter

Sold electricity

Solar thermal

Locally produced electricity

Heat for domestic hot water use

Distributed cooling

Distributed space heating

Distributed electricity

User electricity

Excluded electricity

Electricity for heating in AHU or other local heater

Water volume for domestic hot water

Acronym EUM FM DCM DHM SE OST LPE TDHW DC DSH DE IE EXC AHU[kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [m3]

January 848 0 0 30896 0 7 0 13929 0 0 0 22083 0 0 335.8February 767 0 0 28767 0 39 0 12969 0 0 0 22083 0 0 335.8March 895 0 0 20748 0 2319 0 9354 0 0 0 22083 0 0 335.8April 963 0 0 5277 0 6972 0 2379 0 0 0 22083 0 0 335.8May 1025 0 0 1231 0 8757 0 555 0 0 0 22083 0 0 335.8June 993 0 0 977 0 8577 0 440 0 0 0 22083 0 0 335.8July 1022 0 0 954 0 8923 0 430 0 0 0 22083 0 0 335.8August 1018 0 0 1534 0 8346 0 692 0 0 0 22083 0 0 335.8September 916 0 0 4734 0 4923 0 2134 0 0 0 22083 0 0 335.8October 854 0 0 11679 0 268 0 5265 0 0 0 22083 0 0 335.8November 821 0 0 18353 0 30 0 8274 0 0 0 22083 0 0 335.8December 848 0 0 26642 0 2 0 12011 0 0 0 22083 0 0 335.8Total 10970 0 0 151792 0 49163 0 68432 0 0 0 264996 0 0 4029.6

Bought energy

On site free flowing

produced energy

Distributed / used energy

Sold energy

Electricity utility meter

Fuel utility meter

District cooling utility meter

District heating utility meter

Sold electricity

Solar thermal

Locally produced electricity

Heat for domestic hot water use

Distributed cooling

Distributed space heating

Distributed electricity

User electricity

Excluded electricity

Electricity for heating in AHU or other local heater


Acronym EUM FM DCM DHM SE OST LPE TDHW DC DSH DE IE EXC AHU[kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [kWh] [m3]

January 6649 0 0 47855 0 150 0 8419 0 23743 0 9272 0 0 120February 5851 0 0 42517 0 440 0 6399 0 19779 0 7825 0 0 91March 5556 0 0 35762 0 1700 0 8982 0 15339 0 9334 0 0 128April 4931 0 0 24085 0 2920 0 8363 0 8001 0 8385 0 0 119May 4827 0 0 15533 0 2950 0 9091 0 6295 0 8615 0 0 130June 3977 0 0 10432 0 2970 0 8908 0 899 0 8060 0 0 127July 3826 0 0 9207 0 3175 0 8698 0 53 0 8353 0 0 124August 3872 0 0 8839 0 3075 0 8737 0 45 0 8209 0 0 125September 4004 0 0 10030 0 2280 0 7893 0 1374 0 8127 0 0 113October 4789 0 0 24158 0 1040 0 8406 0 10592 0 8515 0 0 120November 5026 0 0 29707 0 350 0 8167 0 14899 0 8663 0 0 117December 5124 0 0 35431 0 140 0 12991 0 16869 0 8993 0 0 119Total 58432 0 0 293555 0 21190 0 105052 0 117890 0 102350 0 0 1434

Bought energy

On site free flowing

produced energy

Distributed / used energy


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Table 5 Roth building: energy meter explanations and clarification/specification regarding associated energy use, if necessary.

6.3 Discrepancy between calculated and monitored energy performance The BuildSmart project defines a strategy for evaluating the building energy performance [7]. An important part of this strategy is to analyse the discrepancy between calculated and measured energy performance.

6.3.1 Energy signature The diagram in Figure 3 displays the energy signatures for heating energy used per month versus average outside temperature. Heating energy is here the sum of bought district heating and heating from solar panels minus the energy used for hot tap water. The blue markers show the measured data points and grey markers simulated values. The respective signatures are indicated with blue and grey lines.

The match between measurements and simulations is poor. The measured slope is steeper than the corresponding simulated one, indicating that the insulating capability of the envelope has been over predicted in the simulations. Furthermore, the measured balance temperature is found to be approximately 14°C while it is 7°C in the simulations.

The measured climate-independent losses are lower than simulated. The reason is under investigation.

Measured energy useElectricity utility meter One unit measuring total building use excluding tenants subscriptions.Fuel utility meter N/ADistrict cooling utility meter N/ADistrict heating utility meter One unit measuring total lbuilding use of heating, each apartment also measures it´s use

of heat individually.Sold electricity N/ASolar thermal One unit measureing the production of kWh of the thermal installation.Locally produced electricity N/AHeat for domestic hot water use The part used from district heating that adds on heat to hot water is measured

seperately.Distributed cooling N/ADistributed space heating N/ADistributed electricity N/AUser electricity Each aprtment has a specific meter device which gives the kWh used, available also to

the owner of the building.Excluded electricity N/AElectricity for heating in AHU or other local heater

N/A


Total use of m3 water is measured in each apartment

Energy meter description


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Figure 3 The building’s energy signatures, calculated and measured, for heating energy.

6.3.2 Electricity, EUM Electricity is used to light stairwells, lifts, etc. The diagram in Figure 4 displays estimated and measured electricity for common usage, i.e. excluding the electricity used by the tenants in their own apartments (IE). The common energy usage is clearly underestimated in the simulation.

0

1

2

3

4

5

6

7

8

9

10

0 5 10 15 20 25

Heat

ing

ener

gy u

sed

[kW

h/m

2 ]

Average monthly outside temperature [°C]

Calculated data

Calculated e-signature

Measured data

Measured e-signature


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Figure 4 The building’s calculated and measured electricity.

6.3.3 District heating, DHM District heating is used for heating and to heat the hot tap water. The diagram in Figure 5 displays estimated and measured district heating. As can be seen the need for use of district energy has been underestimated in the simulations. Please note that the measured data shown in Figure 5 has not been climate normalised.

The measurements (Table 4) show that energy used for hot tap water is climate-independent. This means that energy use for a normal year can be written as

THDWnorm = TDHW2015

Assuming that losses are also climate-independent, e.g. hot water circulation losses, the losses can be written

Lossnorm = Loss2015

Heating and solar thermal is obviously depending on the climate. Here, it is assumed that these measures for a normal year can be estimated by

DSHnorm = DSH2015 HDDnorm/HDD2015

OSTnorm = OST2015 HDDnorm/HDD2015

Where HDD denotes heating degree days, cf. section 5.1.

0

1000

2000

3000

4000

5000

6000

7000

EUM

[kW

h]

Estimated

Measured


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With these relations, the climate normalised district heating can be written as:

DHM* = (DHM + OST - DSH)2015 + (DSH - OST)2015 HDDnorm/HDD2015

The climate normalised district heating is also included in Figure 5.

Figure 5 The building’s simulated and measured district heating.

6.3.4 Solar thermal, OST The diagram in Figure 6 displays estimated and measured heating energy from the solar panels. The efficiency of the panels is approximately three times lower than predicted.

0

10000

20000

30000

40000

50000

60000

DHM

[kW

h]

Estimated

Measured

Normalised


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Figure 6 The building’s simulated and measured heating energy from the solar panels.

6.3.5 Heat for domestic water, TDHW The diagram in Figure 7 displays measured and simulated heat for domestic water. The simulations have used a model where the hot water usage is depending on the heating used (45%). These measurements show that this parameter is indeed climate-independent.

0

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2000

3000

4000

5000

6000

7000

8000

9000

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OST

[kW

h]

Estimated

Measured


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Figure 7 The building’s simulated and measured heat for domestic water.

6.3.6 Final energy Figure 8 displays measured and corrected final energy usage. Final energy is defined as the sum of bought energy. For the Roth building this reduces to the sum of DHM and EUM.

0

2000

4000

6000

8000

10000

12000

14000

16000

TDHW

[kW

h]

Estimated

Measured


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Figure 8 The building’s simulated and measured energy usage

6.4 Indicators The measured energy is documented with two different indicators, i.e. final energy and primary energy. Additionally, the climate impact is given as equivalent emitted carbon dioxide. These three measures are listed in Table 6.

Table 6 Energy and climate impact indicators

Month Final energy [kWh/m2] PE [kWh/m2] CO2 [ton/m2]

Jan 11.19 8.00 2.95 Feb 9.98 7.11 2.59 Mar 8.55 6.27 2.46 Apr 6.01 4.75 2.19 Maj 4.08 3.72 2.14 Jun 3.19 2.97 1.76 Jul 3.02 2.84 1.70

Aug 2.22 2.44 1.72 Sep 2.14 2.88 1.77 Okt 4.75 4.57 2.12 Nov 6.28 5.46 2.23 Dec 7.89 6.34 2.27 Year 69 57 26

0

10000

20000

30000

40000

50000

60000

Fina

l ene

rgy

usag

e [k

Wh]

Estimated

Measured

SCIS Normalised


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7 References [1] European commission, “Communication from the commission to the European parliament,

the council, the European economic and social committee and the committee of the regions. On resource efficiency opportunities in the building sector”, COM(2014) 445 final, Brussels, 1/7-2014.

[2] European commission, “Europe 2020: A strategy for smart, sustainable and inclusive growth“, COM(2010) 2020 final.

[3] EPDB II, "om byggnaders energiprestanda (omarbetning)", Europaparlamentets och rådets direktiv 2010/31/EU, 19/5-2010, Europeiska unionens officiella tidning 18/6-2010, L 153/13-35.

[4] Jacob Lindblom, Ivana Kildsgaard, Johanna Andersson, Víctor Sánchez Zabala and Joe Hayden, “D5.2. Specification of the monitoring systems for two building types”, Report “BuildSmart – Energy efficient solutions read for the market”, 7th framework programme, 2012.

[5] Roland Zinkernagel (Ed.), “BuildSmart – energy efficient solutions ready for the market”, Annex I – “Description of Work”, 7th energy programme, 2011-10-28.

[6] Boverkets Författningssamling BFS 2014:3 BBR 21, 2014-06-17. [7] Ivana Kildsgaard, Jacob Lindblom, Johanna Andersson, Víctor Sánchez Zabala and Joe

Hayden, “D5.1 Monitoring and evaluation strategies of building’s energy performance”, Report “BuildSmart – Energy efficient solutions read for the market”, 7th framework programme, 30 November 2012.

[8] Chair of Sustainable Management of Housing & Real Estate (ÖÖW), Institute for Technology Assessment and Systems Analysis (ITAS), French-German Institute for Environmental Research (DFIU), Renewable Energies Program (EE), Building Science Group (FBTA), “Evaluation of (Smart) Solutions –Guidebook for Assessment Part I –Methodology, CONCERTO Premium, Karlsruhe Institute of Technology, Karlsruhe, Germany, November 2013.

[9] http://smartcities-infosystem.eu/concerto/concerto-archive, 2016-10-31. [10] Carolina Lijenström, Tove Malmqvist, Martin Erlandsson, Johanna Fredén, Ida Adolfsson och

Gustav Larsson, ”Byggproduktionens miljöpåverkan i förhållande till driften. Livscykelberäkning av klimatpåverkan och energianvändning av ett nyproducerat flerbostadshus i beting med lågenergiprofil”, IVL Rapport C32, ISBN 978-91-7595-218-5.

[11] Gunnel Forslund, Jan Forslund, ”Bästa inneklimat till lägsta energikostnad.”, AB Svensk byggtjänst, 2016, ISBN 978-91-7333-768-7.

[12] Jenny Gode, Fredrik Martinsson, Linus Hagberg, Andreas Öman, Jonas Höglund, David Palm ”Miljöfaktaboken 2011. Estimated emission factors for fuels, electricity, heat and transport in Sweden”, VÄRMEFORSK Service AB, 2011, ISSN 1653-1248.

[13] “Fjärrvärmens bränslen och produktion 2015 xlsx”, http://www.svenskfjarrvarme.se/Statistik--Pris/Fjarrvarme/Energitillforsel/, 2011-10-15

http://smartcities-infosystem.eu/concerto/concerto-archive

http://www.svenskfjarrvarme.se/Statistik--Pris/Fjarrvarme/Energitillforsel/


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Appendix A Heating degree days The table lists the heating degree days according to SCIS calculated using data from a weather station in Malmö. The data for a normal year are found by averaging from all days since 1990.

Table 7 SCIS heating degree days

Month Normal year Year 2015

Jan 439.6 468.5 Feb 419.7 443.9 Mar 378.3 402.1 Apr 265.3 296.8 Maj 151.9 218.8 Jun 72.3 108.8 Jul 23.2 39.3

Aug 26.0 15.1 Sep 102.8 119.7 Okt 221.0 266.9 Nov 327.8 326.9 Dec 411.7 368.5


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Appendix B District heating statistics for E.ON Malmö värme 2015 The table lists the fuel mix for district heating produced by E.ON Malmö during 2015 [12][13]. Furthermore, the primary energy factors and carbon equivalents are listed.

Table 8 Fuel mix for district heating

Fuel/energy carrier Fuel for heating [GWh] PEF [-] CO2eq [g/MJ] Fraction

Fuel/heating oil (EO1) 0.5 1.1 82.0 0% Fuel/heating oil (EO3-5) 3.5 1.1 84.0 0% Natural gas 823.6 1.1 69.0 40% Waste 732.1 0.0 38.0 36% Stemwood chips 71.2 1.0 2.0 3% Electricity for heat pumps 0.6 2.1 44.4 0% Delivered heat from the heat pump 1.3 0.0 9.0 0% Flue gas condensation 28.0 0.0 0.0 1% Waste heat 99.0 0.0 0.0 5% Total help electricity 25.5 2.1 44.4 1%

The total heating energy delivered from district heating plant is 2052 GWh.

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