RESULTS OF THE MEASUREMENT CAMPAIGN · The Swedish Energy Agency has financed the project, “End-use metering campaign in 400 ... Their consumption appear like wasted energy, and

End-use metering campaign in 400 households In Sweden

Assessment of the Potential Electricity Savings

Jean Paul Zimmermann

September 2009

CONTRACT 17-05-2743

E N E R T E C H Ingénierie énergétique et fluides

F - 26160 FELINES S/RIMANDOULE Tél. & Fax: (33) 4.75.90.18.54 Courriel: [email protected]

www.enertech.fr

Preface The Swedish Energy Agency has financed the project, “End-use metering campaign in 400 households in Sweden, assessment of the potential electricity savings”. The project is a part of the agencies’ program, “Improved energy statistics in buildings and industry”. In this program measurements and surveys of commercial buildings (STIL2), energy for water consumption in households and energy consumption in industry are carried out. A database, eNyckeln, of Swedish buildings from an energy perspective is also a part of the program. The electricity demand for households, excluding heating, has increased over a long period according to statistics based on surveys. This project has been initiated in order to deepen our understanding of what this increase consists of and how electricity is used in households. The report is written in English and is intended for decision makers, governmental agencies, researchers, consultants, utilities and other stakeholders, with an interest in this field. A database with all measured data and data from enquiries etc. will be made available on the agencies website, www.energimyndigheten.se In addition to the measurements, several research projects have been carried out. Some of these concerns behavioural aspects, with the aim to deepen the understanding of the user load patterns. The research projects are also available on the website. However, the data gathered will allow for more analysis and the agency invites researchers to utilise the database. Project leaders within the agency have been Peter Bennich, until summer 2008, and after that Egil Öfverholm. The agency would like to thank all participating households for their cooperation and patience. A project of this size involves many individuals. Zinaida Kadic (coordinator of the overall program), Heini-Marja Suvilehto (until February, 2009), Anette Persson (until August, 2008), Linn Stengård, Ester Veibäck, Dennis Solid (until August, 2009), Agnetha Leo, and Christina Sterneus have been involved in the work at the Swedish Energy Agency. All work by Elisabet Nilsson and Anna-Lena Johansson has been of great help. The agency also acknowledges Nils Windh and Rune Ståhl, from YIT-Sweden, who carried out the installation of metering equipment with a never ending enthusiasm and endurance. Finally the agency would like to thank Olivier Sidler and Jean-Paul Zimmermann from Enertech for their outstanding work and their endurance over a long period. Enertech is a French company with extensive experience of this type of measurements. They were responsible for measurements and analysis. Jean Paul Zimmermann is the principal author of the report as well as its contents and conclusions.

Eskilstuna, September 2009 Caroline Hellberg Head of unit Department of System Analysis

http://www.energimyndigheten.se/

Index

GENERALITIES ....................................................................................................................... 6

STAKES AND OBJECTIVES............................................................................................... 6 Context ............................................................................................................................... 6 Objectives of the project .................................................................................................... 6 Operationnal partners ......................................................................................................... 7

DESCRIPTION OF THE GENERAL METHODOLOGY ................................................... 7 Generalities......................................................................................................................... 7 General characteristics of the measurement campaigns..................................................... 7

THE MEASUREMENT SYSTEMS...................................................................................... 8 The Multivoies system ....................................................................................................... 9 The Serial wattmeter ........................................................................................................ 10 The Wattmeter with am pliers and Pulsmeter .................................................................. 11 The Lampmeter ................................................................................................................ 12 The Thermometer ............................................................................................................. 12 The Optical reader............................................................................................................ 13

TREATMENT OF THE COLLECTED DATA .................................................................. 14 DESCRIPTION OF THE SAMPLES.................................................................................. 14

Distribution of apartments and houses ............................................................................. 14 Number of inhabitants per household .............................................................................. 15 Sizes of the households .................................................................................................... 16 Inhabitants type ................................................................................................................ 16

RESULTS OF THE MEASUREMENT CAMPAIGN............................................................ 18 GENERAL ELECTRICITY CONSUMPTION................................................................... 18

Total annualized households electricity consumption ..................................................... 18 Maximum power demand drawn by the households........................................................ 40 Cumulative frequencies of power demands, from the grid point of view........................ 46 Structure of the average hourly load curve ...................................................................... 53 Relative contribution from the different loads ................................................................. 85

COLD DOMESTIC APPLIANCES .................................................................................. 117 Average possession of appliances .................................................................................. 117 Seasonality effect ........................................................................................................... 119 REFRIGERATORS ....................................................................................................... 120 REFRIGERATOR-FREEZERS..................................................................................... 123 VERTICAL FREEZERS................................................................................................ 126 OTHER COLD APPLIANCES ..................................................................................... 129

LAUNDRY, DISH-WASHING AND CLEANING APPLIANCES ................................ 133 Average possession of appliances .................................................................................. 133 CLOTHES-WASHERS ................................................................................................. 134 CLOTHES-DRYERS..................................................................................................... 149 DISHWASHERS ........................................................................................................... 161

COOKING ......................................................................................................................... 176 Average possession of appliances .................................................................................. 176 Seasonality effect .......................................................................................................... 177 Annualized consumptions .............................................................................................. 177 Hourly load curve........................................................................................................... 183 Annualized consumptionper appliance .......................................................................... 193

LIGHTING......................................................................................................................... 206 CHARACTERISTICS OF THE LIGHTING IN PLACE.............................................. 207 ANALYSIS OF THE INSTALLED LIGHTING WATTAGE ..................................... 212

Index

ANNUALIZED LIGHTING CONSUMPTION............................................................ 227 STRUCTURE OF THE ANNUALIZED LIGHTING CONSUMPTION..................... 235 AVERAGE HOURLY LOAD CURVE ........................................................................ 237

AUDIOVISUAL SITE....................................................................................................... 247 Description of the monitored equipment........................................................................ 247 Annualized consumption................................................................................................ 249 Hourly load curve per type of household ....................................................................... 254 Standby consumption .................................................................................................... 264 Analysis per type of equipment...................................................................................... 265

COMPUTER SITES .......................................................................................................... 274 Description of the monitored equipment........................................................................ 274 Annualized consumption................................................................................................ 274 Hourly load curve........................................................................................................... 278 Standby consumption .................................................................................................... 287 Analysis per type of equipment...................................................................................... 288

HEATING/WATER HEATER .......................................................................................... 290 Description of the monitored equipment........................................................................ 290 Seasonality effect .......................................................................................................... 290 Average consumption..................................................................................................... 291 Annual consumption per m² ........................................................................................... 298 Annual consumption per person..................................................................................... 304 Part of the electric heating consumption ........................................................................ 309 Analysis per type of equipment...................................................................................... 311

OTHER APPLIANCES ..................................................................................................... 312 Average consumption..................................................................................................... 312

ANALYSIS OF STANDBY POWERS IN THE HOUSEHOLDS .................................. 312 General methodology ..................................................................................................... 313 Standby power demand ................................................................................................. 315

SINGLE FAMILY HOUSES VS RESIDENTIAL BUILDINGS ..................................... 318 ASSESSMENT OF THE POTENTIAL ELECTRICITY SAVINGS ................................... 319

DOMESTIC COLD PRODUCTION................................................................................. 319 Methods for assessing the savings ................................................................................. 319 Refrigerator potential electricity saving......................................................................... 320 Vertical freezers potential electricity saving.................................................................. 320 Fridge freezers potential electricity saving .................................................................... 321 Table-top freezers potential electricity saving ............................................................... 322 American freezers potential electricity saving ............................................................... 322 Chest freezers potential electricity saving...................................................................... 323 Cold appliances potential electricity saving................................................................... 323

LIGHNING ........................................................................................................................ 324 Methods for assessing the savings ................................................................................. 324 Lightning potential electricity saving............................................................................. 324

WASHING/DRYING ........................................................................................................ 326 Methods for assessing the savings ................................................................................. 326 Clothes-washer potential electricity saving.................................................................... 326 Clothes dryers potential electricity saving ..................................................................... 327 Dishwasher potential electricity saving.......................................................................... 327

AUDIOVISUAL SITE....................................................................................................... 328 Methods for assessing the savings ................................................................................. 328 Potential electricity saving ............................................................................................. 329

Index

COMPUTER SITE............................................................................................................. 329 Methods for assessing the savings ................................................................................. 329 Potential electricity saving ............................................................................................. 330

POTENTIAL ENERGY SAVING PER TYPE OF HOUSEHOLD.................................. 331 Apartment, family, 26-64 years old ............................................................................... 332 Apartment, single person, 26-64 years old..................................................................... 333 Apartment, couples without children, 26-64 years old ................................................. 334 Apartment, couples without children, 64 years old and above ..................................... 335 Apartment, single person, 64 years old and above......................................................... 336 House, family, 26-64 years old ...................................................................................... 337 House, couples without children, 26-64 years old ........................................................ 338 House, couples without children, 64 years old and above ............................................ 339

CONCLUSION ...................................................................................................................... 340

Generalities

GENERALITIES

STAKES AND OBJECTIVES

Context The investigation field of this project is the Demand Side Management of the specific electricity end-uses, in the residential sector. These end-uses represent an increasing part of the European Community states energy balance. Moreover, their impacts in terms of environmental nuisance (CO2 emissions, radioactive wastes) require rapid actions.

It has already been shown for a long time that the household electricity consumption could be reduced without any change in the rendered service, or in the comfort. A first demonstration was done between 1995 and 1997 in France with the Ecodrome project, which was lead by « Cabinet O.SIDLER » (which later became ENERTECH) and financed by the European Community (contract number 4.1031/S/94-093) and the ADEME (French Agency for Environment and Energy Management). The results of this project showed that we could save up to 40 % of the electricity-specific appliance consumption of the households by using efficient appliances. On a household scale, 1,200 kWh/year were saved. By extrapolating the French and European savings from this value, one found that 26 TWh/year could be saved in France and 180 TWh/year in Europe. The latter value represents the annual Italian consumption. The assigned objective of this project is to confirm whether Ecodrome conclusions can be generalised to Sweden.

Objectives of the project The first objective of this campaign is to precisely describe the state and structure of

the specific-electricity uses in the residential sector and to give an overview of the consumption for the common area for residential buildings. This project will produce reference information that will allow research teams, and organisations that work in the modelling and forecasting of electrical consumptions, to base their works on reliable data and on sane basis. No pertinent action can save the cost of a sharp analysis of the initial situation. This study aims at describing as carefully as possible, the state of the electro-domestic appliances in Sweden. The descriptive approach is one of the most important contributions of this project. The second objective of this project is to evaluate the potential savings that can be achieved in the households by substituting efficient appliances for the appliances in place.

Standby powers are at the moment very particular, because there is no service at all associated with their demands. Their consumption appear like wasted energy, and most of them are probably avoidable, generally at a relatively low cost. This aspect is essential because Standby consumption seems to grow exponentially and its part in the household consumption grows in a worrying way. Therefore Standby power was monitored and analyzed with in order to define as precisely as possible the nature and the extent of the associated consumption. Finally, this project monitored every light source in every household. This allowed a very sharp precise of the lighting consumption, and therefore of the efficient solutions.

6

Generalities

Operationnal partners The measurement campaigns took place in Sweden and different teams were

involved;: The Swedish energy agency was the initiator of the project. They provided the

households and the residential buildings for the project. Enertech in France, because of its experience in the monitoring campaign field, was in

charge of providing the monitoring equipment, analysing the data. YIT Sverige AB was in charge of the installation and dismantling of the measurement

systems. Enertech provided training session to the YIT staff on the use and installation of the monitoring equipments.

DESCRIPTION OF THE GENERAL METHODOLOGY

Generalities The monitoring campaign was scheduled from August 2005 to December 2007. However, the time needed to achieve the required quality of data and the difficulty to find valid households extend the campaign by one year. Finally, the campaign went from August 2005 to December 2008.

General characteristics of the measurement campaigns The goal of the study was to monitor all main electric appliances for 400 households and 20 common areas in residential blocks:

- 40 households were measured for one year. All the main electrical appliances were monitored at a time step of 10 minutes, a direct measure was done for the rest. Most of the households were located in the Mälardalen region with one of these households located in the far north of Sweden, one other in the south of Sweden. Due to the number of metering devices, it was possible to monitor 20 households at the same time. Therefore this part was achieved in two years (first year: 20 households – second year: 20 households).

- 360 households were monitored for one month. All the main electrical appliances were monitored at a time step of 10 minutes, a direct measure was done for the rest. 9 of these households were located in the far north of Sweden, 9 in the south (Skåne region) and the rest in the Mälardalen region. 26 metering equipment sets were used for that part: the campaign was a succession of “installation of the monitoring equipment” / “recording the data for one month” / “dismantling the equipment”

7

Generalities

Table from figure 1.1 represent the equipment planned to be use per household. Uses Serial

Wattmeter Wattmeter with ammeter pliers

Lampmeter Temperature sensor

General meter 3 Heating 3 Water heater 1 Kitchen oven 3 Miscellaneous 3 Clothes-washer 1 Dishwasher 1 Clothes-drier 1 TV 3 Audiovisual site 2 Computer site 3 Cold appliances 2,5 Microwave 1 Car heating 1 Ventilation system 1 Lighting 1 25 Miscellaneous 2 Temperature 2

Total 17.5 15 25 2

Figure 1.1: planned equipment per household

The choice of the households was done by the Swedish energy agency. They had to be a good picture of the different type of households present in Sweden. The households were split in different categories (see chapter: Description of the sample).

THE MEASUREMENT SYSTEMS Several types of metering devices were used to achieve the monitoring campaign:

lampmeters were used to measure the consumption of the light sources that draw a constant electrical power (incandescent bulbs, CFL, etc.). All the light points with constant power were metered. The lampmeter measured the time during which the light source was switched on and the power was measured separately during the meter installation. From these two measurements, we were able to determine precisely the consumption’s of each light point in the households. We used Wattmeters connected in series with the lamp to determine the consumption’s of the halogen lights, for which the power drawn was not constant.

the consumption’s of most of the other types of appliances (cold, audiovisual,

computer site, etc.) were monitored using Wattmeters connected in series with the appliances. The serial wattmeter was directly plugged into the wall sockets. The household appliance to be monitored was then connected in the trailing socket of the wattmeter.

some appliances (mainly heating, water heating) were monitored directly from the main switchboard of the household. These measurements were done using the Multivoies system which was installed inside the breaker board (or fuse box).

8

Generalities

the internal and external temperatures were monitored using thermometers.

The Multivoies system The MULTIVOIEStm system from the french OmégaWatt company is designed for the

measurement of a large number of channels of power consumption and energies in electrical switch boxes. It includes a Din rail mounted concentrator to measure voltages and supply power to the system, and several modules equipped with current sensors.

Figure 1.2 : Multivoies system overview

The system interfaces with the user thanks to a Personal Digital Assistant, using

Infrared communication or low power radio (Bluetooth). The concentrator and the modules are connected to a high speed industrial data bus with factory assembled RJ11 connectors. The modules are fitted with standard closed miniature current transformers (0-45 Amps).

The main features include: • Simultaneous measurement of electric power in tens of lines per switch box, • Measurement of power ranging from 2 W to 230 kW per phase with a wide range of current sensors (Current jaws, miniatures current transformers, Rogowski coils). Typical accuracy: 2%. • Recording of active energy and voltages with periods of 1 second to 60 minutes (5 month memory for 10 minutes period – independent on the number of current modules) • Records power quality (voltage sags).

9

Generalities

Figure 1.3 : Concentrator and Module for the multivoie system

The Serial wattmeter The serial wattmeter developed by ENERTECH was designed with the aim of taking

measurements of active energy and voltage for single-phase appliances with power level lower than 2,6 kW. Placed in serial between the standard socket-outlet 230 V~ and the plug of the appliance to be measured, it does not require any intervention on the distribution system.

The serial wattmeter is entirely autonomous and can be left in place several months

according to the frequency of the selected data memorizing. At the end of the measurement period the memorized data are read using the Oscar software which transfer them to a PC for analysis.

Figure 1.4 : Serial wattmeter overview

The features for the serial wattmeter includes:

Voltage area: between 0 - 250 Vac (the power supply for the serial wattmeter is not taken on that entry - measurements continuous even in the absence of voltage sector)

Maximum load: 12 amps Serial wattmeter power supply by standard batteries: 2 X LR6 (AA) 1.5V (autonomy:

400 days) Current measurement with two automatic gauges Resolution: 0.1 Wh - the resolution decrease with the power (progressive coding) Working Led: a short impulse every 4 seconds.

10

Generalities

Period of measurement: adjustable from 1 to 60 minutes The drift of the clock is of approximately 10 minutes per year 65 KB of memory: 1,3 year of autonomy in term of memory size for recordings at

10mn.

The Wattmeter with am pliers and Pulsmeter The Wattmeter was designed by ENERTECH to be used mainly upstream electric

installation (Switch box, etc). Each Wattmeter is associated with a Pulse meter, a small electronic device in charge of data recording.

The function of the Wattmeter is to convert the active energy information into pulses recorded by the Pulse meter. The weight of one pulse is 0,5 Wh.

Pulse meters for the Wattmeter are electronic recorders of reduced size connected directly on the Wattmeter. The number of pulses is stored in its memory.

Pulse meters are entirely autonomous and can be left in place several months according to the frequency of selected data memorizing. At the end of the measurement period, the memorized data are transferred to a PC using the Oscar software.

Figure 1.5 : Wattmeter with am pliers and Pulsmeter

The features for the Wattmeter are:

Measurement range: 3W – 22kW Voltage range 180V - 250V Amp pliers: 100 A: cat III 640 V Pulse meter connector: max 10mA: 12 V

The features for the Pulse meter include:

a micro controller with very low electric consumption, a nonvolatile memory of large capacity (64Ko) allowing 65024 records, standard Lithium battery allowing an autonomy higher than 4 years, programmable period from 1 minute to one hour saving the pulses in memory: memorizing 0 to 2175 pulses per period with a

precision always better than 1,5%.

11

Generalities

The Lampmeter The lampmeter is an electronic recorder of reduced size. It can be installed in the

immediate proximity of the appliance to evaluate, without requiring connection with the electrical supply network.

An optical sensor ensures the detection of the durations of lighting for the equipments. This allows a very fast assembly without intervention on the electric circuits. You just have to fix it near the lamp to be analyzed and to direct the sensor towards the source of light. A LED flickering indicates then if the sensor is correctly positioned.

Entirely autonomous, they can be left in place several months according to the frequency of selected data memorizing. At the end of the period of measurement the data is recovered using the Oscar software which transfer the data on to a PC where they will be analyzed.

Figure 1.6 : Lampmeter

The design features include:

A micro controller with very low electric consumption, A nonvolatile memory of strong capacity (64Ko) allowing a recording going

until 32000 events, A standard Lithium battery allowing an autonomy higher than 4 years, An indicator of operating condition of the appliance. (The LED is active during

4 minutes after connection with the PC interface but it is not necessary to connect the interface to the PC.)

Events recording (lightings and extensions): o Resolution for duration is one second. o Precision for the dating of the events is 4 seconds.

The Thermometer The thermometer is an autonomous electronic data logger of reduced size provided

with a temperature sensor. It takes regularly measurements and stores at selected time steps

12

Generalities

the average of several measurements (2 minutes interval between each measurement except at the time step of 1 minute) (ex: carry out the average of 5 measurements for a 10 minutes step).

The thermometer has a very broad range of measurements (-50°C to 120°C).

Figure 1.7 : Thermometer – Indoor and Outdoor models

The data are stored in a non volatile memory of strong capacity (64Ko) allowing a recording going up to 65000 measurements (1 byte per data, for an autonomy of approximately 1 year and 3 months for recordings with the step of 10 minutes).

The recorder uses standard Lithium battery (standard CR 2032) allowing an autonomy equal to 2 years for a 10 minutes step and one year for a one minute step.

The Optical reader The optical reader is used for measuring the main electrical consumption by recording

the led flash that you will find on the “electronic type” electric meter only. There is no electric connection to provide as the sensor is an optical type. You only

need scotch to install logger. The optical reader consists of a sensor to place against the pane of the meter, of a

black box and a wire which connects these two elements. The box contains batteries which make it possible for the device to be autonomous during more than one year (alkaline batteries).

Memory autonomy for the device can reach 14 month for measurements at 10 minutes time.

Figure 1.8: Optical reader

13

Generalities

TREATMENT OF THE COLLECTED DATA

Once the data was received by Enertech, it was later on controlled by a software tool aimed at certifying the coherence of the transmitted records. This data was subsequently assembled in a database. The filtering and preparation work is very long and meticulous. But it is necessary to be sure that the data used is trustable. We decided to remove from the database any record that was doubtful or not reliable.

The data were stored in 4 different databases: appliances monitored one month (54 million data), lighting monitored one month (53 million data), appliances monitored one year (55 million data) and lighting monitored one year (54 million data).

The sums per families of appliances (cold, audiovisual, etc) and per type of room for lighting (bedroom, kitchen, etc) were also calculated and introduced into new databases. This allowed an easier approach to the appliance analysis.

DESCRIPTION OF THE SAMPLES

Distribution of apartments and houses As we can see in figure 1.9 the distribution between apartments and houses is very well balanced. The sample includes one less house than apartments.

Characteristics of the sampleDistribution of apartments and houses

Houses49%Apartments

51%

Swedish energy agency Enertech

Figure 1.9: Distribution of apartments and houses

14

Generalities

Number of inhabitants per household Figure 1.10 shows the distribution of the number of persons per household. 35% of the houses have two inhabitants (couples without children or one adult with one child), 32% of the houses have four inhabitants (couples with two children). 37% of the apartments have two inhabitants (couples without children or one adult with one child), 28% of the apartments are for single persons.

Characteristics of the sampleDistribution of the number of persons per type of household

0%

5%

10%

15%

20%

25%

30%

35%

40%

1 pers

on

2 pers

ons

3 pers

ons

4 pers

ons

5 pers

ons

6 pers

ons

1 pers

on

2 pers

ons

3 pers

ons

4 pers

ons

5 pers

ons


Houses Apartments

Figure 1.10: Distribution of the number of persons per type of household

15

Generalities

Sizes of the households Figure 1.11 shows the average area per type of household. The houses are 1.67 greater than the apartments.

Characteristics of the sampleAverage surface area of the households

0

20

40

60

80

100

120

140

Houses Apartments

Mea

n ar

ea (m

²)

Mean : 127 m²

Mean : 76 m²


Figure 1.11: Average surface area for the households

Inhabitants type Figure 1.12 represent the number of households per categories of inhabitant:

For the two types of household, the first category is “family between 26 and 64 years old”. For the families, we include couples with a child (or children) or a single person with a child (or children),

There are far less single persons in houses than in apartments, “Single person less than 25 years old” are only present for apartments.

16

Generalities

Characteristic of the sampleNumber of households per categories of inhabitants

0

20

40

60

80

100

120

140

Singleperson,26-64

years old

Singleperson,64 yearsold andabove

Couplewithout

children,26-64

years old

Couplewithout

children,64 yearsold andabove

Family,26-64

years old

Singleperson,

less than25 years

old

Singleperson,26-64

years old

Singleperson,64 yearsold andabove

Couplewithout

children, less than25 years

old

Couplewithout

children,26-64

years old

Couplewithout

children,64 yearsold andabove

Family,26-64

years old


Houses Apartments

3 4

46

21

125

2

41

101

41

14

81

Figure 1.12: Number of households per categories of inhabitant

17

Results of the monitoring campaign

RESULTS OF THE MEASUREMENT CAMPAIGN

GENERAL ELECTRICITY CONSUMPTION

Total annualized households electricity consumption Figure 2.1 to 2.31 represents the distribution of the total household electricity consumption for the different type of households. The total electricity consumption was always monitored for the household from the main electric switchboard and contains the specific consumption like cold appliances, lighting etc but also heating and water heating. There are different types of heating depending on the energy used: direct electric heating, heat pump, gas, wood, district heating. Each type of heating needs different devices to work properly: electric radiators, heat pump, circulation pump for hot water etc. In this monitoring campaign, all the consumption involved in the heating production were monitored, generally directly from the switchboard. According to the questionnaire that each household owner had to fill in, the households were split in two categories: the ones “with direct electric heating” (radiators or electric furnace) and the ones “without direct electric heating” (district heating, heat pump or other types of energy). Refer to the Heating/Water heating chapter for more information about the systems. For the houses, there are also graphs for the specific consumption (all consumption minus heating and water heating). The specific consumption lets us compare the houses with the apartments. The graphs with the consumption per m² and per persons are also presented and give us good indicators to compare the households:

the average consumption is maximum for houses with electric heating where families or couples without children between 26 and 64 years old are living: 18558 kWh/year and 17173 kWh/year respectively.

the consumption per m² for families and couples without children between 26 and 64 years old are very close: 136 and 139 kWh/m²/years for houses with electric heating, 76 kWh/m²/year for houses without electric heating and 44 and 36 kWh/m²/year for the apartments.

for the houses, the couples without children between 26 and 64 years old have an annual consumption per person that is far more important than for families. As the consumption per m² is equivalent (see point above), the consumption per person is automatically higher. One explanation is that the consumption for cold appliances or heating are less dependant of the number of persons in the household than cooking or lighting for example.

the minimum to maximum ratio is always greater then 5. The type of household allow us to split the data in different categories but the number of parameters that can explain the consumption level are too high to be taken into account.

18


Table of figure 2.32 list all the results contained in the graphs.

Family, 26-64 years old

Figures 2.1: Total annualized electricity consumption – Houses with electric heating

Figures 2.2: Total annualized electricity consumption per m² – Houses with electric heating

Annual consumption per household

0

10000

20000

30000

40000

50000

60000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

House, Family, 26-64 years old - Electric heating

Mean value : 18558 kWh/year

STEM ENERTECH

Annual consumption per m²

0

100

200

300

400

500

600

700

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHHouse, Family, 26-64 years old - Electric heating

Mean value : 136 kWh/m².year

19


Figures 2.3: Total annualized electricity consumption per person – Houses with electric heating

Figures 2.4: Total annualized electricity consumption – Houses without electric heating


0

5000

10000

15000

20000

25000

30000

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Households

)

House, Family, 26-64 years old - Without Electric direct heating


STEM ENERTECH

Annual consumption per person

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHHouse, family, 26-64 years old, with electric heating

Mean value : 4820 kWh/person.year

20


Figures 2.5: Total annualized electricity consumption per m² – Houses without electric heating

Figures 2.6: Total annualized electricity consumption per person – Houses without electric heating


0

50

100

150

200

250

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHHouse, Family, 26-64 years old - Without Electric direct heating



0

1000

2000

3000

4000

5000

6000

7000

8000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHHouse, family, 26-64 years old, without direct electric heating


21


House, family, 26-64 years oldAnnual consumption per household

for all the specific loads

0

2000

4000

6000

8000

10000

12000

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

Mean-Value : 4143 kWh/year

Energimyndigheten Enertech

Figures 2.6-B: Total annualized electricity consumption per household – Specific consumption only - Houses

Figures 2.6-C:

House, family, 26-64 years oldAnnual consumption per person


0

500

1000

1500

2000

2500

3000

3500

4000

Ann

ual c

onsu

mpt

ion

per p

erso

n (k

Wh/

pers

on.y

ear)

Mean-Value : 1109 kWh/person.year


Total annualized electricity consumption per person – Specific consumption only - Houses

22


House, family, 26-64 years oldAnnual consumption per m²


0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

Ann

ual c

onsu

mpt

ion

per m

² (kW

h/m

².yea

r)

Mean-Value : 32 kWh/m².year


Figures 2.6-D: Total annualized electricity consumption per m² – Specific consumption only - Houses


0

5000

10000

15000

20000

25000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

Apartment, family, 26-64 years old


STEM ENERTECH

Figures 2.7: Total annualized electricity consumption – Apartments

23



0

20

40

60

80

100

120

140

160

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHApartment, family, 26-64 years old


Fig ts

Figures 2.9: Total annualized electricity consumption per person - Apartments

ures 2.8: Total annualized electricity consumption per m² – Apartmen


0

1000

2000

3000

4000

5000

6000

7000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHApartment, family, 26-64 years old


24


Couples without children, 26-64 years old

Figures 2.10: Total annualized electricity consumption– Houses with electric heating

Figures 2.11: Total annualized electricity consumption per m² – Houses with electric heating


0

5000

10000

15000

20000

25000

30000

35000

40000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

House, couple without children, 26-64 years old, with electric heating


STEM ENERTECH


0

50

100

150

200

250

300

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM House, couple without children, 26-64 ye ENERTECHars old, with electric heating


25


Figures 2.12: Total annualized electricity consumption per person – Houses with electric heating

Figures 2.13: Total annualized electricity consumption – Houses without direct electric heating


0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Households

)

STEM ENERTECHHouse, couple without children, 26-64 years old, with electric heating



5000

10000

15000

20000

25000

30000

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

0Households

)

House, couple without children, 26-64 years old, without direct electric heating


STEM ENERTECH

26


Figures 2.14: Total annualized electricity consumption per m² – Houses without direct electric heating

Figures 2.15: Total annualized electricity consumption per person – Houses without direct electric heating


0

20

40

60

80

100

120

140

160

180

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Households

)

STEM ENERTECHHouse, couple without children, 26-64 years old, without direct electric heating



0

2000

4000

6000

8000

10000

12000

14000

16000

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Households

)

STEM ENERTECHHouse, couple without children, 26-64 years old, without direct electric heating


27


House, couple without children, 26-64 years oldAnnual consumption per household


1000

2000

3000

4000

5000

6000

7000

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)


Figures 2.15-C: Total annualized electricity consumption per m² – Specific consumption only - Houses

0



House, couple without children, 26-64 years oldAnnual consumption per m²


0,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

45,0

50,0

Ann

ual c

onsu

mpt

ion

per m

² (kW

h/m

².yea

r)

5,0



28


House, couple without children, 26-64 years oldAnnual consumption per person


0

500

1000

1500

2000

2500

3000

3500

Ann

ual c

onsu

mpt

ion

per p

erso

n (k

Wh/

pers

on.y

ear)



Figures 2.15-D: Total annualized electricity consu er person – Specific consumption only - Houses mption p


0

2000

4000

6000

8000

10000

12000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

Apartment, couple without children, 26-64 years old


STEM ENERTECH

Figures 2.16: Total annualized electricity consumption – Apartment

29



0

10

20

30

40

50

60

70

80

90

100

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHApartment, couple without children, 26-64 years old


Figures 2.17: Total annualized electricity consumption per m² – Apartment

Figures 2.18: Total annualized electricity consumption per person – Apartment


0

1000

2000

3000

4000

5000

6000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHApartment, couple without children, 26-64 years old


30


Couples without children, 64 years old and above

Figures 2.19: Total annualized electricity consumption– Houses with electric heating

Figures 2.20 Total annualized electricity consumption per m²– Houses with electric heating


0

50

100

150

200

250

300

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHHouse, couple without children, 64 years old and above, Electric heating



0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

House, couple without children, 64 yeras old and above, with electric heating


STEM ENERTECH

31


Figures 2.21: Total annualized electricity consumption per person– Houses with electric heating

Figures 2.22: Total annualized electricity consumption – Houses without direct electric heating


0

5000

10000

15000

20000

25000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

House, couple without children, 64 years old and above, without direct electric heating


STEM ENERTECH


0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM House, couple without children, 64 years old and abov ENERTECHe, with electric heating


32



0

20

40

60

80

100

120

140

160

180

200

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHHouse, couple without children, 64 years old and above, without direct electric heating


Fi g gures 2.23: Total annualized electricity consumption per m² – Houses without direct electric heatin

Figures 2.24: Total annualized electricity consumption per person – Houses without direct electric heating


0

2000

4000

6000

8000

10000

12000

14000

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHHouse, couple without children, 64 years old and above, without direct electric heating


33


House, couple without children, 64 years old and aboveAnnual consumption per household


0

500

1000

1500

2000

2500

3000

3500

4000

4500

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)




Figures 2.24-C:

House, couple without children, 64 years old and aboveAnnual consumption per m²


0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

Ann

ual c

onsu

mpt

ion

per m

² (kW

h/m

².yea

r)



Total annualized electricity consumption per m² – Specific consumption only - Houses

34


House, couple without children, 64 years old and aboveAnnual consumption per person


0

500

1000

1500

2000

2500

Ann

ual c

onsu

mpt

ion

per p

erso

n (k

Wh/

pers

on.y

ear)



Fi s

gures 2.24-D: Total annualized electricity consumption per person – Specific consumption only - House



0

500

1000

1500

2000

2500

3000

3500

4000

4500

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEMApartment, couple without children, 64 years old and above


ENERTECH

35



Figures 2.27: Total annualized electricity consumption per person – Apartment


0

10

20

30

40

50

60

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHApartment, couple without children, 64 years old and above



0

500

1000

1500

2000

2500

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHApartment, couple without children, 64 years old and above


36


Single person, 26-64 years old

Figures 2.28: Total annualized electricity consumption– Apartment



1000

2000

3000

4000

5000

6000

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

0Households

)

Apartment, Single person, 26-64 years old


STEM ENERTECH


30

40

50

60

70

80

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

0

10

20

Households

)

STEM ENERTECHApartment, Single person, 26-64 years old


37


Single person, 64 years old and above




0

500

1000

1500

2000

2500

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

Apartment, Single person, 64 years old and above


STEM ENERTECH


0

5

10

15

20

25

30

35

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHApartment, Single person, 64 years old and above


38



House, with

electric heating

House without electric heating

House, specific consumption

only Apartment

per household 18558 8416 4143 3710 per m² 136 76 32 76

per person 4820 2523 1109 1187 Couples without children, 26-64 years old

House, with

electric heating


House, specific consu

onlymption

Apartment


per person 8323 4831 1619 1202 Couples without children,64 years old and above

House, with

electric House without

electric House, specific consumption Apartment

heating heating only


per person 6965 2390 1459 1070 Single person, 26-64 years old

House, with

electric heating


House, specific consumption

only Apartment

per household 1742 per m² 27

per person Single person, 64 years old and above

House, with electric heating

House without electric heating Apartment

per household 1682 per m² 22

per person

Figure 2.32: Annual consumption per type of household, per m² and per person. Houses without electric heating include water heating and specific consumption. Specific consumption is all loads except heating and water heating.

39


Maximum power demand drawn by the households The maximal power demand reached is an interesting indicator, as it fixes the power level to be subscribed from the electricity distributor. We calculated it hereafter, by using the monitored consumption during 10 minutes. It is therefore not a proper instantaneous power demand. But experience shows that power measured every 10 minutes, and powers calculated by using the 10 minutes consumption are very similar (the difference is generally under 2 %). From the grid point of view, this calculation method is right and is used by most of the electricity distributors. Figure 2.33 to 2.43 represents the maximum power demand for different household types.


.33: M power demand – Houses with e ectric heatin

Maximum power demand during the monitoring period

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

holds

Pow

er (W

)

Figure 2 aximum l g

House

STEM

House, family, 26-64 years old, with electric heating

ean value : atts

ENERTECH

5826 WM

40


Figure 2.34: Maximum power demand – Houses without direct electric heating

Figure 2.35: Maximum power demand – Apartment

Maximum er dem

2000

3000

4000

5000

6000

7000

8000

9000

Households

Pow

er (W

)

pow and during the monitoring period

0

1000

STEM

family ears ol ithout direct el c heatiHouse, , 26-64 y d, w ectri ng

Mean value : 4334 Watts

ENERTECH


0

2000

800

12000

Households

4000

6000

Pow

er (W

0

)

10000

STEM



ENERTECH

41



Figure 2.36: Maximum power demand – Houses with electric heating



0

2000

4000

6000

8000

10000

12000

14000

Pow

er (W

)

Households

STEM

House, couple without children, 26-64 years old, with electric heating


ENERTECH


0

1000

2000

3000

4000

5000

6000

7000

8000

9000

Households

Pow

er (W

)

STEM



ENERTECH

42



0

1000

2000

3000

4000

5000

6000

Households

Pow

er (W

)STEM



ENERTECH




0

2000

4000

6000

8000

10000

12000

Households

Pow

er (W

)

Figure 2.39: Maximum power demand – Houses with electric heating

STEM

House, couple without children, 64 years old and above, with electric heating


ENERTECH

43



0

1000

2000

3000

4000

5000

6000

7000

8000

Households

Pow

er (W

)STEM



ENERTECH



0

1000

2000

3000

4000

5000

6000

Households

Pow

er (W

)

STEM

Apartment, couple without children, 64 years old and above


ENERTECH


44







0

500

1000

1500

2000

2500

3000

3500

Households

Pow

er (W

)

STEMApartment, single person, 26-64 years old


ENERTECH


0

500

1000

1500

2000

2500

3000

Households

Pow

er (W

)

STEMApartment, single person, 64 years old and above


ENERTECH

45


Table of figure 2.44 completes the information given in figure 2.33 to 2.43

Maximum (W) Average (W)

Ratio Average/Maximum

With direct electric heating 11782 5498 1: 2,1

House, couples without children, 26-64 years old Without direct electric

heating 7872 4748 1: 1,7


House, couples without children, 64 years old and above Without direct electric

heating 7098 3582 1: 2,0


House, family, 26-64 years old Without direct electric

heating 7749 4334 1: 2,8

Apartment, couples without children, 26-64 years old 5324 2775 1: 1,9 Apartment, couples without children, 64 years old and

above 4984 2494 1: 2,0

Apartment, family, 26-64 years old 9770 3139 1: 3,1 Apartment, single person, 26-64 years old 3108 1835 1: 1,7

Apartment, single pe 1700 1: 1,6 rson, 64 years old and above 2786

Figure 2.43: Extreme values of maximum power demands

grid » because this is t and supplies to each household of the sample.

General observations: the maximum to average ratio is always between 1,6 and 2, except in certain cases: House, family, 26-64 years old - Apartment, family, 26-64 years old where disparities are higher, the power demand level is greater then 10000 for all the houses with electric heating and in the range 7000-8000 for the ones without direct electric heating, families will always have the maximum power demand for houses and apartments.

Cumulative frequencies of power demands, from the grid point of view Figures 2.44 to 2.54 shows for each type of household, the cumulative frequency curves of the average power demand reached in the households, from the grid point of view. This results have not to be mixed up with the maximum power demand as calculated in the previous chapter: the max. power was calculated for each house separately - the powers from this chapter are an average value between all the household of a specific categorie. To get this kind of curve, we calculated every ten minutes from the 1st of January to the 31st of December, the average power demand for each type of household that drew power at this precise time.

Then, we classified all these values. The obtained power is told to be seen « from the he average power that the distributor observes

46



General consumptionCumulative frequency of the power demand over the year

House, family, 26-64 years oldWith direct electric heating

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er p

er h

ouse

hold

(W)

STEM ENERTECH

Figure 2.44: General consumption – the year, from the grid point of view – House, family, 26-64 years old - With direct electric heating

Figu y of the p emand e year, fromgrid point of tric heating

Cumulative frequency of the power demand over

General consumptionCumulative frequency of the power de a

House, fam ly, 26-64 yearWithout direct electric heating

0

2000

4000

6000

0 0% 60% 80 90% 10

Pow

er p

er h

ouse

hold

(W)

re 2.45: General consumption – Cumulative frequenc ower d over th the view – House, family, 26-64 years old - Without direct elec

mand over the yes old

ri

1000

3000

5000

7000

% 10% 20% 30% 40% 5 70% % 0%

S ENERTECHTEM

47


Figure 2.46: General consumption – Cumulative frequency of the power demand over the year, from the grid point of view – Apartment, family, 26-64 years old


Figure 2.47: General consumption – Cumulative frequency of the power demand over the year, from the grid point of view – House, couples without children, 26-64 years old – With direct electric heating

General consumptionumulative frequency of the power demand over the year

1500

2500

3000

h

CApartment, family, 26-64 years old

4000

0

500

1000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er

2000

use

3500

per

ho

old

(W)

STEM ENERTECH


House, couple without children, 26-64 years oldWith direct electric heating

0

2000

4000

6000

8000

10000

12000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er p

er h

ouse

hold

(W)

STEM ENERTECH

48



House, couple without children, 26-64 years oldWithout direct electric heating

0

2000

4000

6000

8000

10000

12000

14000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er p

er h

ouse

hold

(W)

STEM ENERTECH

Figure 2.48: General consumption – Cumulative frequency of the power demand over the year, from the grid point of view – House, couples without children, 26-64 years old – Without direct electric heating

Figure 2.4 from the grid point of view – Apartment, couples without children, 26-64 years old



0

500

1000

1500

2000

2500

3000

3500

4000

4500

Pow

er p

er h

ouse

hold

(W)

9: General consumption – Cumulative frequency of the power demand over the year,

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

STEM ENERTECH

49


Couples without children, 64 years old and above Figure 2.50: General consumption – Cumulative frequency of the power demand over the year, from the

General consumptionCumulative frequency of the power demand over the yearHouse, couple without children, 64 years old and above

With direct electric heating

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

Pow

er p

er h

ouse

hold

(W)

grid point of view – H With direct electric heating

ouse, couples without children, 64 years old and above –

Figure 2.51: General consumption – Cumulative frequency of the power demand over the year, from the grid point of view – House, couples without children, 64 years old and above – Without direct electric

heating

General consumptionCumulative frequency of the power demand over the yearHouse, couple without children, 64 years old and above

Without direct electric heating

0

1000

2000

3000

4000

5000

6000

7000

8000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er p

er h

ouse

hold

(W)

STEM ENERTECH

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

STEM ENERTECH

50




0

1000

2000

3000

4000

5000

6000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er p

er h

ouse

hold

(W)

STEM ENERTECH

Figure 2.52: General consumption – Cumulative frequency of the power demand over the year, from the grid point of view – Apartment, couples without children, 64 years old and above



Apartment, single person, 26-64 years old

0

500

1000

1500

2000

2500

3000

3500

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er p

er h

ouse

hold

(W)

STEM ENERTECH

Figure 2.53: G year, from the grid point of view – Apartment, single person, 26-64 years old

eneral consumption – Cumulative frequency of the power demand over the

51



Fig e grid point of view – Apartmen erson, 64 years old and above

ure 2.54: General consumption – Cumulative frequency of the power demand over the year, from tht, single p

Table 2.55 gives precision about figure 2.44 to 2.54, by showing the average powerdrawn during 20 % and 80 % of the time for each type of household:

Average maximum power demand reached during

20 % of the time

Average maximum power demand reached during

80 % of the time Average power exceeded

during 1% of the time

Apartment, couples without ren, 26-64 years old 207 422 child 2672

Apartment, couples without ren, 64 years old and above 128 273 child 3205

Apartment, family, 26-64 years old 295 558 3131

Apartment, single person, 26-64 years old 163 267 2260

Apartment, si 2347 ngle person, 64 years old and above 142 227

Hous26-64 8029

e, couples without children, years old without direct

electric heating 365 1265

House,26-64 y

couples without children, ears old with direct electric

heating 510 1991 8103

House, couples without children, 64 years old and above without

direct electric heating 267 895 5262


Apartment, single person, 64 years old and above

0

500

1000

1500

2000

2500

3000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pow

er p

er h

ouse

hold

(W)

STEM ENERTECH

52


Hou6753

se, couples without children, 64 years old and above with direct

electric heating 652 1901

Hou 5063 se, family, 26-64 years old without direct electric heating 668 1330

Hous 6911 e, family, 26-64 years old with direct electric heating 1415 2491

Figure 2.55: specific values of the cumulative frequency curve of the reached average power demand, from the grid point of view

It is interesting to note that the average power exceeded during 1% of the time is maximum for houses with couples without children between 26-64 years old. There is no big difference between the houses with direct electric heating and the one’s without.

Structure of the average hourly load curve Figures 2.56 to 2.121 shows, for different type of households, the split between holidays (Saturday and Sunday) workdays (Monday-Friday) and the sum of the two, the structure of the ‘load curves’, which shows the average hourly energy demand. These curves were calculated by averaging the individual load curves for each household. The 10 minute values are merged per hour in order to obtain 24 values (one per hour) given in Watt. This structure was obtained using all the monitored devices merged per type of a h

ptions.

Figure 2.56: Structure of the average hourly load curve – Houses with direct electric heating - All days

ppliance (cold appliances, lighting, audiovisual sites, computer sites, cooking, washing,eating etc.). The graphs are split in two: a first set with all the different consumptions

ting, a second set displaying only the specific consumincluding heating and water hea


Structure of the average hourly load curve

0

500

1000

1500

2000

2500

3000

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hours

Pow

er (W

att)

Lightning Cold appliances Cooking Dishwasher Washing dryingAudio site TV Visual site excl. TV Computer site MiscellaneousHeating Water heating Not known

ENERTECHHouse, family, 26-64 years old, with direct electric heatingEnergimyndigheten

All days

53



0

500

1000

1500

2000

2500

3000

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hours

Pow

er (W

att)


ENERTECHEnergimyndigheten House, family, 26-64 years old, with direct electric heating

Holidays

Figure 2.57: Structure of the average hourly load curve – Houses with direct electric heating - Holidays


0

500

1000

1500

2000

2500

3000

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hours

Pow

er (W

att)

Figure 2.58: Structure of the average hourly load curve – Houses with direct electric heating – Workdays


Energimyndigheten House, family, 26-64 years o ENERTECHld, with direct electric heating

Workdays

54


Figure 2.59: Structure of the average hourly load curve for the specific consumption– Houses with direct - All days

electric heating

Figure 2.60: Structure of the average hourly load curve for the specific consumption– Houses with direct electric heating - Holidays

Structure of the average hourly load curve for the specific consumptions

300

800

900

1000

[5,6[

[6,7[

[7,8[ [

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[1 [17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22

Hours

0

100

200

400

500

Pow

er (W

att) 600

700

[0,1[

[1,2[

[2,3[

[3,4[

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electric heating – Workdays Figure 2.61: Structure of the average hourly load curve for the specific consumption– Houses with direct

Figure 2.62: Structure of the average hourly load curve – Houses without direct electric heating - All days


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ENERTECHEnergimyndigheten House, family, 26-64 years old, with direct electric heating

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ENERTEnergimyndigheten House, family, 26-64 years old, without direct electric heating CHE

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ENERTECHEnergimyndigheten House, family, 26-64 years old, without direct electric heating

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Figure 2.63: Structure of the average hourly load curve – Houses without direct electric heating - Holidays


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Figure 2.64: Structure of the average hourly load curve – Houses without direct electric heating – Workdays



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Figure 2.65: Structure of the average hourly load curve for the specific consumption– Houses without ect electric heating - All dadir ys

Figure 2.66: Structure of the average hourly load curve for the specific consumption– Houses without direct electric heating - Holidays


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Figure 2.67: Structure of the average hourly load curve for the specific consumption– Houses without ect electric heating – Workdact electric heating – Workdadir ys

Figure 2.68: Structure of the average hourly load curve – Apartments - All days

ys

Figure 2.68: Structure of the average hourly load curve – Apartments - All days


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ENERTECHEnergimyndigheten Apartment, family, 26-64 years old

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Figure 2.69: Structure of the average hourly load curve – Apartments - Holidays


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Figure 2.70: Structure of the average hourly load curve – Apartments - Workdays



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Figure 2.71: Structure of the average hourly load curve for the specific consumption– Apartments - All days

l days

Figure 2.72: Structure of the average hourly load curve for the specific consumption– Apartments -

Figure 2.72: Structure of the average hourly load curve for the specific consumption– Apartments -


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Holidays Holidays

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Figure 2.73: Structure of the average hourly load curve for the specific consumption– Apartments - Workdays

Figure 2.74: Structure of the average hourly load curve – Houses with direct electric heating – All days



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ENERTECHEnergimyndighetenHouse, couple without children, 26-64 years old, with direct electric heating

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Holidays

Figure 2.7 Holidays

2.76: Structure of the average hourly load curve – Houses with direct electric heating – Workdays

Holidays


5: Structure of the average hourly load curve – Houses with direct electric heating –age hourly load curve – Houses with direct electric heating –


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Figure Figure

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Figure

2.78: Structure of the average hourly load curve for the specific consumption– Houses with direct electric heating – Holidays

2.77: Structure of the average hourly load curve for the specific consumption– Houses with direct electric heating – All days


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F ct electric h rkdays

igure 2.79: Structure of the average hourly load curve for the specific consumption– Houses with direeating – Wo

Structure of the average h1800

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Figure 2.80: Structure of the average hourly load curve – Houses without direct electric heating – All days


ENERTECHEnergimyndigheten old, without direct electric heatingHouse, couple without children, 26-64 years

All days



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ENERTECHEnergimyndighetenHouse, couple without children, 26-64 years old, without direct electric heating

Holidays

Figure 2.81: Structure of the average hourly load curve – Houses without direct electric heating – Holidays

Workdays


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Figure 2.82: Structure of the average hourly load curve – Houses without direct electric heating –



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Figure 2.83: Structure of the average hourly load curve for the specific consumption– Houses without direct electric heating – All days

Figure 2.84: Structure of the average hourly load curve for the specific consumption– Houses without direct electric heating – Holidays


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Figure 2.85: Structure of the average hourly load curve for the specific consumption– Houses without ct electric heating – Workdat electric heating – Workdadire ys

Figure 2.86: Structure of the average hourly load curve – Apartments – All days

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ENERTECHEnergimyndigheten Apartment, couple without children, 26-64 years old

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Figure 2.87: Structure of the average hourly load curve – Apartments – Holidays


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[8,9[

[9,10

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[10,11

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[11,12

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[

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[

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[

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[

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Figure 2.88: Structure of the average hourly load curve – Apartments – Workdays



Workdays

69



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[0,1[

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[8,9[

[9,10

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[

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All days

Fi ll

Figure 2.90: Structure of the average hourly load curve for the specific consumption– Apartments –

ll


gure 2.89: Structure of the average hourly load curve for the specific consumption– Apartments – Adays

nts – Adays


0

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[

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[

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[

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[

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[

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Holidays

Holidays Holidays

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Workdays

Figure 2.91: Structure of the average hourly load curve for the specific consumption– Apartments – Workdays

Figure 2.92: Structure of the aver direct electric heating – All days



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[0,1[

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age hourly load curve – Houses with


ENERTECHEnergimyndighetenHouse, couple without children, 64 years old and above, with direct electric heating

All days

71



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Holidays

Figure 2.93 Holidays


Holidays


: Structure of the average hourly load curve – Houses with direct electric heating –age hourly load curve – Houses with direct electric heating –


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[

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[

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[

[14,15

[

[15,16

[

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[

[17,18

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Workdays

Figure Figure

72



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[6,7[

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[

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[

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[

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[

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[

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All days

Figure 2.9 ith direct electric heating – All days

ith direct electric heating – All days

5: Structure of the average hourly load curve for the specific consumption– Houses wcurve for the specific consumption– Houses w

Figure 2.96: Structure of the average hourly load curve for the specific consumption– Houses with direct electric heating – Holidays

Figure 2.96: Structure of the average hourly load curve for the specific consumption– Houses with direct electric heating – Holidays


0

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[0,1[

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[3,4[

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[9,10

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[

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[

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Holidays

73



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[8,9[

[9,10

[

[10,11

[

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[

[12,13

[

[13,14

[

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[

[16,17

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Workdays

F t electric h orkdays

Figure 2.98: Structure of the average hourly load curve – Houses without direct electric heating – All

t electric h orkdays

Figure 2.98: Structure of the average hourly load curve – Houses without direct electric heating – All

igure 2.97: Structure of the average hourly load curve for the specific consumption– Houses with direceating – W

ecific consumption– Houses with direceating – W


0

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1400

[0,1[

[1,2[

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[8,9[

[9,10

[

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ENERTECHEnergimyndighetenHouse, couple without children, 64 years old and above, without direct electric heating

All days

days days

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[7,8[

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[9,10

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[10,11

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75

Holidays Figure 2.99: Structure of the average hourly load curve – Houses without direct electric heating –

Figure 2.100: Structure of the average hourly load curve – Houses without direct electric heating – Workdays



Holidays

Structure of the average hourly load curve1400

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1200

[0,1[

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[2,3[

[3,4[

[4,5[

[5,6[

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[8,9[

[9,10

[

[10,11

[

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[

[12,13

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Workdays



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All days

Figure 2.101: Structure of the average hourly load curve for the specific consumption– Houses without direct electric heating – All days

Figure 2.102: Structure of the average hourly load curve for the specific consumption– Houses without direct electric heating – Holidays


0

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[0,1[

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Holidays

76



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Workdays

Figure 2.103: Structure of the average hourly load curve for the specific consumption– Houses without ct electric heating – Workdadire ys


0

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[0,1[

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[2,3[

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[

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ENERTECHEnergimyndigheten Apartment, couple without children, 64 years old and above

All days

77



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[7,8[

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[

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Holidays



0

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Workdays

78



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[8,9[

[9,10

[

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[

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[

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[

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All days

Fig ll


ll


ure 2.107: Structure of the average hourly load curve for the specific consumption– Apartments – Adays

– Adays


0

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[0,1[

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Holidays

Holidays Holidays

79



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Workdays


Figure 2.110: Structure Apartments – All days



0

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of the average hourly load curve –


ENERTECHEnergimyndigheten Apartment, single person, 26- 64 years old

All days

80



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Holidays



0

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Workdays

81



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[7,8[

[8,9[

[9,10

[

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[

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[

[12,13

[

[13,14

[

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[

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[

[16,17

[

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All days

Figure 2.1 ents – All days

Figure 2 ents –

ents – All days

Figure 2 ents –

13: Structure of the average hourly load curve for the specific consumption– Apartmve for the specific consumption– Apartm

.114: Structure of the average hourly load curve for the specific consumption– ApartmHolidays

.114: Structure of the average hourly load curve for the specific consumption– ApartmHolidays


0

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[0,1[

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[2,3[

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Holidays

82



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Workdays

Figure 2.115: Structure of the average hourly load curve for the specific consumption– Apartments – orkdaykdayW s

Figure 2.119: Structure of the average hourly l or the specific consumption– Apartments – All days

s


Figure 2.119: Structure of the average hourly l or the specific consumption– Apartments – All days


oad curve foad curve f


0

50

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350

[0,1[

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ENERTECHEnergimyndigheten Apartment, single person, 64 years old and above

All days

83



0

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[

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[

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er (W

att)




Holidays

Figure 2.120: Structure of the average hourly load curve for the specific consumption– Apartments – Holidays

84


Structure of the average h350

ourly load curve for the specific consumptions

0

50

100

150

200

250

300

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hours

Pow

er (W

att)




Workdays


Relative contribution from the different loads Figures 2.122 to 2.187 shows for type of household, the split between holidays (Saturday and Sunday) workdays (Monday-Friday) and the sum of the two, the relative contribution from the different loads. These figures were calculated by averaging the individual consumption for each household. The individual monitored devices were merged per type of appliances (cold appliances, lighting, audiovisual sites, computer sites, cooking, washing, heating etc.).

The graphs are split in two: a first set with all the different consumptions including heating and water heating, a second set displaying only the specific consumptions.


Figure 2.122: Relative contribution from the different loads – Houses with direct electric heating - All days

Relative contribution from the different loads

6%4%

2%1%

2%0%1%

1%3%

2%

65%

8%5%

LightningCold appliances

CookingDishwasher

Washing dryingAudio site

TVVisual site excl. TV

Computer siteMiscellaneous

HeatingWater heating

Not known

ENERTECH

House, family, 26-64 years old, with direct electric heatingAll days

Energimyndigheten

85



7%4%

3%2%

3%0%1%1%3%2%

62%

7%5%


CookingDishwasher





Not known

ENERTECH

House, family, 26-64 years old, with direct electric heating

Holidays

Energimyndigheten

Figure ting - Holidays

W s

2.123: Relative contribution from the different loads – Houses with direct electric hea


6%4%

2%1%

2%0%1%

1%3%

2%

66%

7%5%

Figure 2.124: Relative contribution from the different loads – Houses with direct electric heating – orkday


CookingDishwasher





Not known

ENERTECH

House, family, 26-64 years old, with direct electric heatingWorkdays

Energimyndigheten

86


Relative contribution from the different loads - Specific consumption

26%

17%

10%6%

9%

2%

6%

4%

11%

9%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV

Visual site excl. TV

Computer site

Miscellaneous

ENERTECH

House, family, 26-64 years old, with direct electric heatingAll days

Energimyndigheten

Figure

Figure 2.126: Relative contribution from the different loads for the specific consumption– Houses with

2.125: Relative contribution from the different loads for the specific consumption– Houses with direct electric heating - All days


26%

16%

11%7%

11%

1%

6%

4%

10%

8%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, family, 26-64 years old, with direct electric heatingHolidays

Energimyndigheten

direct electric heating - Holidays

87



26%

18%

10%6%

8%

2%

6%

4%

11%

9%

88

direct electric heating – Workdays Figure 2.127: Relative contribution from the different loads for the specific consumption– Houses with

Figure 2.128: Relative contribution from the different loads – Houses without direct electric heating - All days


10%

8%

4%

2%

3%1%2%

2%

6%

5%

46%

3%8%


CookingDishwasher





Not known

ENERTECEnergimyndigheten H

House, family, 26-64 years old, without direct electric heatingAll days

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, family, 26-64 years old, with direct electric heatingWorkdays

Energimyndigheten



10%

7%

4%

3%

3%1%2%

2%

6%

5%

46%

3%8%


CookingDishwasher





Not known

ENERTECH

House, family, 26-64 years old, without direct electric heating

Holidays

Energimyndigheten

Figure 2.129: Relative contribution from the different loads – Houses without direct electric heating - Holidays


10%

8%

4%

2%2%1%2%2%

6%

5%

46%

3%

9%

Figure 2.130: Relative contribution from the different loads – Houses without direct electric heating – Workdays


CookingDishwasher





Not known

ENERTECH

House, family, 26-64 years old, without direct electric heatingWorkdays

Energimyndigheten

89


Figure 2.131: Relative contribution from the different loads for the specific consumption– Houses without direct electric heating - All days

Figure 2.132: Relative contribution from the different loads for the specific consumption– Houses without direct electric heating - Holidays


19%

9%6%

6%

1%

5%

4%

24%

12%

14%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

tric heating

Energimyndigheten

House, family, 26-64 years old, without direct elecAll days


22%

17%

10%7%

8%

1%

5%

14%

12%

4%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, family, 26-64 years old, without direct electric heatingHolidays

Energimyndigheten

90



22%

19%

9%6%6%

1%

5%

4%

15%

13%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, family, 26-64 years old, without direct electric heatingWorkdays

Energimyndigheten

Fig ut direct electr Workdays

Figure 2.134: Relative contribution from the different loads – Apartments - All days

ut direct electr Workdays

Figure 2.134: Relative contribution from the different loads – Apartments - All days

ure 2.133: Relative contribution from the different loads for the specific consumption– Houses withoic heating –

for the specific consumption– Houses withoic heating –


18%

15%

9%

4%4%1%5%

3%

11%

3%

16%

1%

10%


CookingDishwasher





Not known

ENERTECH

Apartment, family, 26-64 years oldAll days

Energimyndigheten

91



18%

14%

10%

4%5%1%5%

2%

10%

3%

17%

1%

10%


CookingDishwasher





Not known

ENERTECH


Holidays

Energimyndigheten

Figure 2.135: Relative contribution from the different loads – Apartments - Holidays

Figure 2.136: Relative contribution from the different loads – Apartments - Workdays


17%

16%

9%

4%3%1%5%3%

11%

3%

17%

1%

10%


CookingDishwasher





Not known

ENERTECH

Apartment, family, 26-64 years oldWorkdays

Energimyndigheten

92



25%

21%

13%

6%

5%

2%

7%

3%

14%

4%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, family, 26-64 years oldAll days

Energimyndigheten

Figure 2.137: Relative contribution from the different loads for the specific consumption– Apartments - All days

s - All days

Figure 2.138: Relative contribution from the different loads for the specific consumption– Apartments -

Figure 2.138: Relative contribution from the different loads for the specific consumption– Apartments -


23%

20%

14%

6%

7%

2%

7%

3%

14%

4%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, family, 26-64 years oldHolidays

Energimyndigheten

Holidays Holidays

93



24%

21%

13%

5%

5%

2%

7%

4%

15%

4%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, family, 26-64 years oldWorkdays

Energimyndigheten

Figure 2.140: Relative contribution from the – Houses with direct electric heating – All days


Figure 2.140: Relative contribution from the – Houses with direct electric heating – All days

Figure 2.139: Relative contribution from the different loads for the specific consumption– Apartments -Workdays

mption– Apartments -Workdays



5%5%

2%1%

2%1%1%1%

1%

10%

57%

10%4%

different loads different loads


CookingDishwasher





Not known

ENERTECH

House, couple without children, 26-64 years old, with direct electric heatingAll days

Energimyndigheten

94



5%5%

3%2%

2%1%1%1%1%

10%

54%

10%

5%

95

Holidays Figure 2.141: Relative contribution from the different loads – Houses with direct electric heating –

Figure 2.142: Relative contribution from the different loads – Houses with direct electric heating – Workdays


CookingDishwasher





Not known

ENERTECH

House, couple without children, 26-64 years old, with direct electric heating

Holidays

Energimyndigheten


5%5%

2%1%1%1%1%1%1%

10%

59%

9%4%


CookingDishwasher





Not known

ENERTECH


Energimyndigheten

Workdays



17%

16%

10%

5%8%2%

4%3%

4%

31%Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


Holidays

Energimyndigheten

Figure 2.143: Relative contribution from the different loads for the specific consumption– Houses with direct electric heating – All days

Figure 2.144: Relative contribution from the different loads for the specific consumption– Houses with direct electric heating – Holidays


17%

16%

10%

5%8%2%

4%3%

4%

31%Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, couple without children, 26-64 years old, with direct electric heatingHolidays

Energimyndigheten

96



18%

18%

7%3%5%3%3%

3%

5%

35%

Figure 2.145: Relative contribution from the different loads for the specific consumption– Houses with direct electric heating – Workdays

days

Figure 2.146: Relative contribution from the different loads – Houses without direct electric heating – All


10%

6%

3%1%2%1%2%2%2%

6%

51%

6%

8%


CookingDishwasher





Not known

ENERTECHEnergimyndigheten


All days

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, couple without children, 26-64 years old, with direct electric heatingWorkdays

Energimyndigheten

97



9%

6%

4%

2%

3%1%2%2%

2%

6%

49%

6%

8%

Figure 2.147: Relative contribution from the different loads – Houses without direct electric heating – Holidays

Workdays

Figure 2.148: Relative contribution from the different loads – Houses without direct electric heating –


CookingDishwasher





Not known

ENERTECH


Holidays

Energimyndigheten


9%

7%

3%1%2%1%2%2%2%

7%

50%

6%

8%


CookingDishwasher





Not known


House, couple without children, 26-64 years old, without direct electric heatingWorkdays

98



28%

18%

8%4%

6%

2%

5%

5%

6%

18%

99

Figure 2.149: Relative contribution from the different loads for the specific consumption– Houses without direct electric heating – All days

Figure 2.150: Relative contribution from the different loads for the specific consumption– Houses without direct electric heating – Holidays

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


All days

Energimyndigheten


27%

17%

10%5%

8%

1%

5%

5%

5%

17%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECHEner

House, couple without children, 26-64 years old, without direct electric heatingHolidays

gimyndigheten



29%

19%

7%4%

5%

2%

5%

5%

6%

18%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, couple without children, 26-64 years old, without direct electric heatingWorkdays

Energimyndigheten

direct electr Workdays

Figure 2.152: Relative contribution from the different loads – Apartments – All days

Figure 2.151: Relative contribution from the different loads for the specific consumption– Houses withoutic heating –


16%

21%

10%3%3%1%

5%4%

10%

5%

12%

1%9%


CookingDishwasher





Not known

ENERTECH


All days

Energimyndigheten

100



15%

19%

12%

4%4%1%5%

4%

9%

5%

12%

1%9%

101

Figure 2.153: Relative contribution from the different loads – Apartments – Holidays

Figure 2.154: Relative contribution from the different loads – Apartments – Workdays


CookingDishwasher





Not known

ENERTECH

Apartment, couple without children, 26-64 years oldHolidays

Energimyndigheten


16%

21%

9%3%3%1%5%

4%

10%

5%

13%

1%9%


CookingDishwasher





Not known

ENERTECH

Apartment, couple without children, 26-64 years oldWorkdays

Energimyndigheten



20%

26%

13%

4%

4%

2%

7%

5%

13%

6%

Fi –

Figure 2.156: Relative contribution from the differe t loads for the specific consumption– Apartments –

gure 2.155: Relative contribution from the different loads for the specific consumption– ApartmentsAll days

nHolidays

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


All days

Energimyndigheten


19%

24%

15%

5%

6%

2%

6%

5%

12%

6%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


Energimyndigheten

102



21%

26%

12%

4%

3%

2%

7%

5%

13%

7%

103

days

Figure 2.157: Relative contribution from the different loads for the specific consumption– Apartments – Workdays


Figure 2.158: Relative contribution from the different loads – Houses with direct electric heating – All


6%6%

3%1%1%0%1%

1%1%3%

52%

15%

10%


CookingDishwasher





Not known

ENERTECH

House, couple without children, 64 years old and above, with direct electric heating

All days

Energimyndigheten

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, couple without children, 26-64 years oldWorkdays

Energimyndigheten



6%6%

3%1%1%0%1%

1%1%3%

52%

16%

9%


CookingDishwasher





Not known

ENERTECH


Holidays

Energimyndigheten

Figure 2.159: Relative contribution from the different loads – Houses with direct electric heating – Holidays

Figure 2.160: Relative contribution from the different loads – Houses with direct electric heating –


6%6%

3%1%2%0%1%

1%1%3%

51%

15%

10%


CookingDishwasher





Not known

ENERTECH

House, couple without children, 64 years old and above, with direct electric heatingWorkdays

Energimyndigheten

Workdays

104



25%

26%

11%

4%

6%

1%

5%

4%

6%

12%

Figure 2.161: Relative contribution from the different loads for the specific consumption– Houses with ric heating direct elect – All days


direct electric heating – Holidays

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


All days

Energimyndigheten


24%

27%

12%

4%

4%

1%

6%

4%

6%

12%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, couple without children, 64 years old and above, with direct electric heatingHolidays

Energimyndigheten

105



25%

28%10%

3%

7%

1%

5%

4%

5%

12%

106

direct electric heating – Workdays


Figure 2.164: Relative contribution from the different loads – Houses without direct electric heating – All days


8%

9%

5%

1%2%0%2%1%

2%1%

3%

9%

57%


CookingDishwasher





Not known

ENERTECH


All days

Energimyndigheten

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, couple without children, 64 years old and above, with direct electric heatingWorkdays

Energimyndigheten



8%

10%

5%

1%1%0%2%1%

2%2%

55%

4%

9%


CookingDishwasher





Not known

ENERTECH


Holidays

Energimyndigheten

Figure 2.165: Relative contribution from the different loads – Houses without direct electric heating – Holidays

Figure 2.166: Relative contribution from the different loads – Houses without direct electric heating –


8%

9%

5%

1%2%0%2%1%

2%1%

57%

3%

9%


CookingDishwasher





Not known

ENERTECH

House, couple without children, 64 years old and above, without direct electric heatingWorkdays

Energimyndigheten

Workdays

107



24%

30%15%

3%

7%

1%

6%

4%

6%4%

Figure 2.167: Relative contribution from the different loads for the specific consumption– Houses without direct electric heating – All days

igure 2.168: Relative contribution from the different loads for the specific consumption– Houses without direct electric heating – Holidays

F

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


All days

Energimyndigheten


24%

30%16%

4%

3%1%

7%

4%

6%5%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, couple without children, 64 years old and above, without direct electric heatingHolidays

Energimyndigheten

108



24%

28%15%

3%

8%

1%

6%

4%

7%4%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

House, couple without children, 64 years old and above, without direct electric heatingWorkdays

Energimyndigheten

Figure 2 without direct electric heating – Workdays

.169: Relative contribution from the different loads for the specific consumption– Houses


23%

26%

16%

3%1%

0%

5%

2%

6%

3%0%0%

15%

Figure 2.170: Relative contribution from the different loads – Apartments – All days


CookingDishwasher





Not known

ENERTECH


All days

Energimyndigheten

109



22%

27%

14%

3%1%1%

5%

3%

6%

3%1%0%

14%


CookingDishwasher





Not known

ENERTECH


Holidays

Energimyndigheten

Figure 2.171: Relative contribution from the different loads – Apartments – Holidays


23%

26%

15%

3%2%0%

5%

2%

6%

3%0%0%

15%


CookingDishwasher





Not known


Apartment, couple without children, 64 years old and aboveWorkdays


110



26%

29%

18%

4%

2%1%

6%

3%

7%4%

Figure 2.173: Relative contribution from the different loads for the specific consumption– Apartments – All days

Figure 2.174: Relative contribution from the different loads for the specific consumption– Apartments – Holidays

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


All days

Energimyndigheten


25%

32%

17%

3%1%1%

6%

3%

8%4%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

Energimyndigheten ENERTECH

s

Apartment, couple without children, 64 years old and aboveHoliday

111



27%

28%

18%

4%

2%1%

6%

3%

7%4%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, couple without children, 64 years old and aboveWorkdays

Energimyndigheten

Fi –


Figure 2.176: Relative contribution f erent loads – Apartments – All days

–


Figure 2.176: Relative contribution f erent loads – Apartments – All days

gure 2.175: Relative contribution from the different loads for the specific consumption– ApartmentsWorkdays

mption– ApartmentsWorkdays


17%

27%

9%2%2%2%8%

4%

7%

5%

5%

2%

10%

rom the diffrom the diff


CookingDishwasher





Not known

ENERTECH

Apartment, single person, 26- 64 years old

All days

Energimyndigheten

112



17%

27%

10%2%1%2%

8%

4%

7%

5%

4%2%

11%

Figure 2.177: Relative con – Apartments – Holidays


different loads – Apartments – Workdays

tribution from the different loads


CookingDishwasher





Not known

ENERTECH


Holidays

Energimyndigheten


17%

28%

8%1%2%2%7%

4%

7%

6%

6%

2%

10%


CookingDishwasher





Not known

ENERTECH

Apartment, single person, 26-64 years oldWorkdays

Energimyndigheten

113



20%

34%10%

2%2%

2%

9%

5%

9%

7%


All days



nnHolidays Holidays

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, single person, 26- 64 years old

All days

Energimyndigheten


20%

31%

12%

3%2%

2%

10%

5%

9%

6%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, single person, 26-64 years oldHolidays

Energimyndigheten

114



20%

34%10%

2%2%

2%

9%

5%

9%

7%

115

Workdays

ingle person, 64 years old and above


Figure 2.181: Relative contribution from the different loads for the specific consumption– Apartments –

S


23%

37%

16%

2%2%2%

9%

5% 2%2%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


All days

Energimyndigheten

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH

Apartment, single person, 26-64 years oldWorkdays

Energimyndigheten



23%

37%

16%

2%2%2%

9%

5% 2%2%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


Holidays

Energimyndigheten

116

Figure 2.186: Relative contribution from the different loads for the specific consumption– Apartments –Holidays


23%

37%

16%

2%2%2%

9%

5% 2%2%

Lightning

Cold appliances

Cooking

Dishwasher

Washing drying

Audio site

TV


Computer site

Miscellaneous

ENERTECH


Workdays

Energimyndigheten

Figure 2.187: Relative contribution from the different loads for the specific consumption– Apartments – Workdays


COLD DOMESTIC APPLIANCES

Average possession of appliances Figure 2.188-A and 2.188-B show the average number of cold appliances for houses and apartments. There are more cold appliances in the houses than in apartments: 1,89 and 1,33 respectively. Fridges and vertical freezers are most installed in the houses, fridge-freezers are more present in apartments. The table from figure 2.188-C show the same type of results but per type of household. The number between brackets indicates the number of households used to calculate the average possession so the results for the last two categories has to be treated with care as only 3 and 4 households were analysed.

Figure 2.188-A: Average number of cold appliances – All houses

Cold appliancesAverage number of appliances per household

All houses

Fridge : 0,62

Wine cooler : 0,02

American freezer : 0,05

Chest freezer : 0,02

Fridge freezer : 0,38

Table top freezer : 0,15

Vertical freezer : 0,66

Energymindigheten ENERTECH

Average number of appliances per house :

1,89

117


Figure 2.188-B: Average number of cold appliances – All apartments

Am

eric

an fr

eeze

r

Frid

ge

Che

st fr

eeze

r

Frid

ge fr

eeze

r

Tabl

e to

p fr

eeze

r

Vert

ical

free

zer

Win

e co

oler

Ave

rage

num

ber o

f app

lianc

es

Apartment, couples without children, 26-64 years old (41) 0,00 0,34 0,02 0,61 0,02 0,34 0,00 1,3

Apartment, couples without children, 64 years old and above (14) 0,00 0,43 0,00 0,57 0,07 0,50 0,00 1,6

Apartment, family, 26-64 years old (81) 0,05 0,35 0,00 0,54 0,04 0,42 0,01 1,4

Apartment, single person, 26-64 years old (41) 0,12 0,22 0,00 0,63 0,00 0,15 0,00 1,1

Apartment, single person, 64 years old and above (10) 0,20 0,20 0,00 0,60 0,00 0,20 0,00 1,2

House, couples without children, 26-64 0,04 0,74 0,04 0,33 0,11 0,74 0,02 2,0 years old (46)

Cold appliancesAverage number of appliances per household

All apartments

Vertical freezer : 0,34 Table top freezer :

0,03

Fridge freezer : 0,58

Chest freezer : 0,01

American freezer : 0,06

Wine cooler : 0,01

Fridge : 0,32


Average number of appliances per apartments

: 1,33

118


House, couples without children, 64 years old and above (21) 0,05 0,48 0,05 0,57 0,14 0,52 0,00 1,8

House, family, 26-64 years old (125) 0,06 0,62 0,00 0,37 0,18 0,66 0,02 1,9

House, single person, 26-64 years old (3) 0,00 0,67 0,00 0,33 0,00 1,00 0,00 2,0

House, single person, 64 years old and above (4) 0,00 0,25 0,00 0,50 0,00 0,25 0,00 1,0

Figure 2.188-C: Average number of cold appliances – Per type of household

* The number between brackets represents the number of households

Seasonality effect The consumption of cold appliances is strongly seasonal, but most of the households

were only monitored for one month. The seasonality effect was calculated using the 40 households monitored for one year. For each household, we calculated the weekly consumption by adding all the data per week. The result output consists of 52 values per household corresponding to the number of weeks in one year. This set of values were then normalized to 1 (the average value gives one for each set). An average value per week was then calculated using all the data sets. Figure 2.188 represents the seasonality curve calculated by this method. This curve was used to calculate the annual consumption for the appliances

onitored for less than six month. m

Cold appliancesSeasonnality effect on the consumption

0

0,2

0,4

0,6

0,8

1

1,2

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51

Weeks

STEM ERTECHEN

Figure 2.188: Cold appliances: seasonality effect

119


120

REFRIGERATORS

Annualized consumption Figures 2.189 and 2.190 shows the annual consumption per type of household. The

consumption goes from 196 to 231 kWh/year for the houses and from 135 to 260 kWh for the apartments. The value of 135 kWh/year can be explained by the small number of appliances (5) used to calculated the mean value. In France, the Remodece+ monitoring campaign (100 household monitored during one year in 2007) gives us an annual consumption of 253 kWh/year. In Sweden we are near this value in the apartments for families and “couples without children between 26-64 years old” but below in the other types of household. One of the most significant parameters that can explain this difference is the inside temperature of the different cold appliances but this parameter wasn’t measured during the monitoring campaign.

Figure 2.189: Fridges: annual consumption for houses

FridgesAnnual consumption per type of houses

800

1000

1200

1400

0

200

400

600

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH

House, couple without children, 26-

64

Mean Value : 231 kWh/year

Mean Value : 212 kWh/year Mean Value :

196 kWh/year

years old

House, couple without children, 64 years old

and aboveHouse, family, 26-64 years old


FridgesAnnual consumption per type of apartments

0

200

400

600

800

1000

1200

Ann

ual c

onsu

mpt

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(kW

h/ye

ar)


Apartment, family, 26-64 years oldApartment,

single person, 26-64 years old

Apartment, couple without children, 64

years old and above


259 kWh/yearMean Value : 194 kWh/year


STEM ENERTECH

Figure 2.190: Fridges: annual consumption for apartments

Hourly load curve Figures 2.191 and 2.192 shows the average hourly load curve for houses and apartments. This type of representation allows, for that type of appliance, to determine when it is mostly used over the day by searching for the peak value. The maximum peak is between 18:00 and 20:00 corresponding to the meal time and the presence of the persons in the household.

121


FridgeDaily average load curve for houses

0

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[0,1[

[1,2[

[2,3[

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[

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[22,23

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[

Hour

Pow

er (W

)STEM ENERTECH

Figure 2.191: Fridges: daily average load curve for houses

FridgeDaily average load curve for apartments

0

5

10

15

20

25

30

35

40

45

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

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[13,14

[

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[

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[17,18

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[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH

Figure 2.192: Fridges: daily average load curves for apartments

122


REFRIGERATOR-FREEZERS

Annualized consumption Figures 2.193 and 2.194 shows the annual consumption per type of household for the

fridge-freezers. The consumption goes from 413 to 525 kWh/year for the houses and from 447 to 497 kWh for the apartments. For France, in the Remodece+ project, the annual consumption was 460 kWh/year. This value is in the average of what we calculated for Sweden.

Figure 2.193: Fridge-freezer: annual consumption for houses

Fridge-freezerAnnual consumption per type of houses

400

600

800

1000

1200

1400

1600

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

0

200

STEM ENERTECH

Family, 26-64 years old Couple without

children, 64 years old and above

Couple without children, 26-64

years old




123


Fridge-FreezerAnnual consumption per type of apartments

0

200

400

600

800

1000

1200

1400

Ann

ual c

onsu

mpt

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(kW

h/ye

ar)

STEM ENERTECH

Couple without children, 26-64 years old


Couple without children, 64 years

old and above

Single person, 26-64 years

old

Single person, 64 years old

and above






Figure 2.194: Fridge-freezer: annual consumption for apartments

Hourly load curve Figures 2.195 and 2.196 shows the average hourly load curve for houses and apartments for the fridge freezers. The maximum peak can be found in the evening but is less visible than for refrigerators as the consumption during the day is more stable.

124


Figure 2.195: Fridge-freezer: daily average load curves for houses

Figure 2.196: Fridge-freezer: daily average load curves for apartments

Fridge-freezerDaily average load curve for houses

0

10

20

30

40

50

60

70

80

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

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[

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[

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[

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[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)STEM ENERTECH

Fridge-fDaily average load cu

reezerrve for apartments

0

10

20

30

40

50

60

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

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[

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er (W

)

70

STEM ENERTECH

125


VERTICAL FREEZERS

Annualized consumption Figures 2.193 and 2.194 shows the annual consumption per type of household for the

fridge-freezers. The consumption goes from 372 to 585 kWh/year for the houses and from 326 to 438 kWh for the apartments. For France, in the Remodece+ project, the annual consumption was 556 kWh/year. The consumption in Sweden is lower (except for the “houses - couples without children, 64 years old and above” which represents only a small part of the monitored appliances).

Figure 2.197: Vertical freezer: annual consumption for houses

Fridge freezerAnnual consumption per type of houses

0

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400

600

1000

1200

1400

1600

1800

800

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH



372 kWh/year

Couple without children, 64 years

old and above

Couple without children, 26-64 years

oldFamily, 26-64 years old

126


Figure 2.198: Vertical freezer: annual consumption for apartments

Hourly load curve Figures 2.199 and 2.200 shows the average hourly load curve for houses and apartments for the vertical freezers. The consumption during the day is very stable.

VerticAnnual consumption

al freezer per type of apartments

1000

0

200

400

600

800

Ann

ual c

onsu

mpt

ion

(kW

1200

1400

h/ye

ar)

1600

STEM ENERTECH






Family, 26-64 years oldCouple without children, 26-64

years old

Couple without children, 64

years old and above

127


Vertical freezerDaily average load curve for houses

0

10

20

30

40

50

60

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

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[

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[18,19

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[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)STEM ENERTECH

Figure 2.199: Vertical freezer: daily average load curves for houses

Vertical freezerDaily average load curve partments

30

40

50

60

0, , 2, , , , 6, 7, 8, ,10[

11,12

[,13

[

13,14

14,15

[

15,16

[

[16,17

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17,18

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18,19

[

19,20

20,21

[

21,22

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22,23

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[23,24

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Ho

Pow

er (W

)

128

e

Figure 2.200: Vertical freezer: daily av rage load curves for apartments

for a

01[ 2[ 3[ 4[ 5[ 6[ 7[ 8[ 9[ 1[

10

20

[ [1 [ [3 [4 [5 [ [ [ [9 [10,1

[ [12 [ [

ur

[

[ [ [ [

[

[ [ [

STEM ENERTECH


O In this l the other cold appliances th e campaign but for which the size of the panel was less im

Table To ha uThere is only a difference in height between a standard vertical freezer and a table top.

nnualized consumption Figure 2.201 shows the annual consumption for the table top freezers. It seems that the

in the same range as for the standard vertical freeers.

THER COLD APPLIANCES chapter, we will list al at were monitored during th

portant.

p Freezer Table top freezers are vertical freezers t t can be installed nder kitchen work plans.

A

average consumption is

Figure 2.201: TableTop freezer: annual consumption – all households

Hourly load curve The average hourly load curve from figure 2.202 shows us a power demand of 55 Watt that is very near to the one for vertical freezers (52 Watt).

TableTop freezerAnnual consumption - All households

1000

1200

0

200

400

600

800

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH


129


Figure 2.202: TableTop freezer: daily average load curves – all households

American Freezer American freezers are two doors cold appliances with a fridge and a freezer part. The volume for each part is rather large with the freezer part having a cold water and ice disposer.

Annualized consumption Figure 2.203 shows us the average annual consumption for the american freezers monitored during the campaign. This value of 454 kWh/year can be compared to the 796 kWh/year measured in the french Remodece+ campaign. One more time we see that the consumption for the Swedish appliances are smaller.

TableTop freezerDaily average load curve for houses

0

10

20

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

30

40

50

60

Pow

er (W

)STEM ENERTECH

130


American freezerAnnual consumption - All households

0

100

200

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500

600

700

800

900

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH


Figur olds

Figure 2.204: American freezer: daily average load curves – all households

e 2.203: American freezer: annual consumption – all househ

Hourly load curve Figure 2.204 shows us the daily average load curve for the american freezers.

American freezerDaily average load curve for houses

0

10

20

30

40

50

60

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH

131


Chest Freezer Chest freezer are horizontal freezers. They are less common in the Swedish households than the vertical one’s: only 4 chest freezers were monitored. The kitchens always have a specific place for fridge / fridge-freezer and/or vertical freezer so there’s no need for that type of equipment.

Annualized consumption Figure 2.205 shows the annual consumption for the chest freezers. With an average annual consumption of 242 kWh/year they are consumming half the energy than a vertical freezer. This value has to be confirmed with a larger panel.

Figure 2.205: Chest freezer: annual consumption – all households

Hourly load curve Figures 2.206 shows us the daily average load curve. The average power is 36 Watt instead of 52 Watt for the vertical freezers. Based on the fact that the power demand for the compressors is normally very similar for the two types of appliances, it indicates that the ON time is shorter for the chest freezers than for the vertical ones and that their consumption will be lower. This was measured in several campaign: for example, in the Eureco project for Denmark, vertical freezers are at 456 kWh/year and chest freezers are at 380 kWh/year.

Chest freezerAnnual consumption - All households

600

700

800

0

100

200

300

400

500

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH


132


Figure 2.206: Chest freezer: daily average load curves – all households

LAUNDRY, DISH-WASHING AND CLEANING APPLIANCES

Average possession of appliances The table from figure 2.207-A indicates the average number of appliances per type of household. The number between brackets indicates the number of households used to calculate the average possession so the results for the last two categories has to be treated with are as only 3 and 4 households were analysed. For all the three appliances, the average

number is always higher for houses than for apartments. It is common to find a common laundry in the residential buildings so the need for a washing-machine and a clothe-dryer is minor for the apartments.

Was

hing

mac

hine

Clo

thes

dry

er

Dis

h w

ashe

r

c

Apartment, couples without children, 26-64 years old (41) 0,49 0,15 0,46

Apartment, couples without children, 64 years old and above (14) 0,43 0,00 0,50

Apartment, family, 26-64 years old (81) 0,63 0,21 0,64

Chest freezerDaily average load curve for houses

0

5

10

15

20

25

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[913

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[2

Hour

Pow

er (W

)

30

35

40

,10[

[10,11

[

[11,12

[

[12, 1,2

2[

[22,23

[

[23,24

[

STEM ENERTECH

133


Apartment, single person, 26-64 years old (41) 0,39 0,10 0,34

Apartment, single person, 64 years old and above (10) 0,40 0,00 0,30

All apartments 0,52 0,15 0,51 House, couples without children, 26-64

years old (46) 1,00 0,57 0,91

House, couples without children, 64 years old and above (21) 1,05 0,48 0,76

House, family, 26-64 years old (125) 1,01 0,64 0,93

House, single person, 26-64 years old (3) 0,67 0,33 1,00

House, single person, 64 years old and above (4) 1,00 0,25 0,75

1,01 0,59 0,90 All houses Figure 2.207-A: Average number of appliances per type of household

CLOTHES-WASHERS This appli the rest of the

ragraph and figures.

ptions

There are some significant differences from one type to the other, which can be explained by different practices (wash-cycle frequency, predominance of very hot cycles over 40°C wash-cycle, etc.). Consumption is higher in the houses (from 107 kWh/year to 213 kWh/year) than in the apartments (from 62 kWh/year to 167 kWh/year) and vary a lot from one type of household to another. As we will see in the next chapter, the annual consumption is very dependant of the number of persons in the household.

ance will be called clothes-washer or washing machine inpa

Annualized consum Figures 2.207 to 2.212 shows the histogram of clothes-washer annualized consumption for the different types of households. The analysis of the one year households didn’t show a seasonality effect.

134


Washing machineAnnual consumption

House, couple without children, 26-64 years old

0

50

100

150

200

250

300

350

Households

Ann

ual c

onsu

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h/ye

ar)

STEM ENERTECH


Figure 2.207: Washing machine: annual consumption – House, couples without children,26-64 years old

Figure 2.208: Wa 4 years old and above


House, couple without children, 64 years old and above

0

50

100

150

200

250

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

shing machine: annual consumption – House, couples without children, 6

)

STEM ENERTECH


135


Figure 2.209: Washing machine: annual consumption – House, family,26-64 years old

Figure 2.210: Washing machine: annual consumption – Apartment, couples without children, 26-64 years old


0

200

400

600

800

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

House, family, 26-64 years old

1000

1200

)STEM ENERTECH




0

50

100

150

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250

300

350

400

450

Households

Ann

ual c

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(kW

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STEM ENERTECH


136




0

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800

1000

1200

1400

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH


Figure 2.21 4 years old

Figure 2.212: Washing machine: annual consumption – Apartment, single person, 26-64 years old

1: Washing machine: annual consumption – Apartment, family, 26-6


0

20

40

60

80

100

120

140

160

180

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

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)

ST ENERTECHEM


137


Annualized consumption per person Figure 2.213 shows us the annual consumption per person per family size. The values per person should be treated with some care, since the family structure has to be taken into account as well. The consumption per person for households from 1 to 4 persons doesn’t vary a lot and is always between 60 and 70 kWh/person/year. It is only for families with more than 5 members that we can see a decrease in the annual consumption per person. The washing machine consumption seems to be very dependent of the number of persons in the household.

Figure 2.213: Washing machine: annual consumption per person per household size

Hourly load curve Figures 2.214 to 2.225 shows the daily average load curve for each type of household split between holidays and workdays. The consumption occurs mainly during the day between 08:00 and 20:00 and during the holidays.

Washing machineAnnual consumption per person per family size

10

20

30

40

50

60

70

80

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar/p

erso

n

01 2 3 4 5 6 1 2 3 4 5

Number of persons in the household

)

STEM ENERTECH

House Apartment

138


Figure 2.214: Washing machine – Daily average load curve – House, couples without children, 26-64 years old – Holidays

Figure 2.215: Washing machine – Daily average load curve – House, couples without children, 26-64 years old – Weekdays

Washing machineDaily average load curve

House, couple without children, 26-64 years oldHolidays

0

20

40

60

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (

10

30

50W)

70

80

STEM ENERTECH


House, couple without children, 26-64 years oldWeekdays

0

10

20

30

40

50

60

70

80

,5[ ,6[ 6,7[

7,8[

8,9[

,10[ 1[ 13

[ [15

[16

[17

[18

[8,1

9[ [22

[24

[

Pow

er (W

)

[0,1[

[1,2[ 2,3

[[3,

4[[4[ [5 [ [ [ [9 [10

,1[11

,12[

[12,

[13,14

[14,

[15,

[16,

[17,

[1 [19,20

[20,21

[

[21,

[22,23

[

[23,

Hour

STEM ENERTECH

139



House, couple without children, 64 years old and aboveHolidays

0

10

20

30

40

50

60

70

80

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)STEM ENERTECH

Figure 2.216: Washi n, 64 years old and above – Holidays

Figure 2.217: Washing machine – Daily average load curve – House, couples without children, 64 years old and above – Weekdays

ng machine – Daily average load curve – House, couples without childre


0

10

20

30

40

50

60

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

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[12,13

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[13,14

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[14,15

[

[15,16

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[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

House, couple without children, 64 years old and aboveWeekdays

70

80

STEM ENERTECH

140


Figure 2.218: Washing machine – Daily average load curve – House, family, 26-64 years old – Holidays

Figure 2.219: Washing machine – Daily average load curve – House, family, 26-64 years old – Weekdays d curve – House, family, 26-64 years old – Weekdays


House, family, 26-64 years oldHolidays

20

30

40

50

60

70

80

90

9,10[

10,11

[

11,12

[

12,13

[

13,14

[

14,15

[

15,16

[

16,17

[

17,18

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9[

19,20

[

20,21

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[22,23

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0

10

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[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[ [ [ [ [ [ [ [ [ [1 [ [

Hour

STEM ENERTECH


House, family, 26-64 years oldWeekdays

0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

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[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH

141


Figure 2.220: Washing machine – Daily average load curve – Apartment, couples without children, 26-64 years old – Holidays

Figure 2.221: Washing machine – Daily average load curve – Apartment, couples without children, 26-64 years old – Weekdays



0

10

20

30

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

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[6,7[

[7,8[

[8,9[

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[16,17

[

[17,18

[

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[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

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Hour

Pow

er (W

) 40

50

60

STEM ENERTECH


Apartment, couple without children, 26-64 years oldWeekdays

40

50

60

[0,1[

[1,2

[2,3[

[3,4

[4,5

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

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[13,14

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er

0

10

20

[ [ [ [ [

30

(W)

STEM ENERTECH

142




0

10

20

30

40

50

60

70

80

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[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

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[11,12

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[12,13

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[14,15

[

[15,16

[

[16,17

[

[17,18

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[18,19

[

[19,20

[

[20,21

[

[21,22

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[22,23

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[23,24

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Figure 2.222: Washing machine – Daily average load curve – Apartment, family, 26-64 years old – Holidays

t, 2 ars old –

Figure 2.223: Washing machine – Daily average load curve – ApaWeekdays

rtmen family, 6-64 ye

Hour

STEM ENERTECH

Washing machine

0

5

10

15

20

25

30

[0,1[

[1,2[ 3[ ,4[ ,5[ ,6[ 7[ 8[ 9[ ,10

[ 1[ 13[ [

15[

16[

16,

17,18

[8,1

9[

19,20

[

20,21

[

21,22

[

[22,23

[

[23,24

[

Hour

Pow

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)

Daily average load curveApartment, family, 26-64 years old

Weekdays

35

40

45

50

[2, [3 [4 [5 [6, [7, [8, [9 [10,1

[11,12

[

[12,

[13,14

[14,

[15,

[ [17

[

[1 [ [ [

STEM ENERTECH

143


Figure 2.225: Washing machine – Daily average load curve – Apartment, single person, 26-64 years old – Weekdays


Apartment, single

Figure 2.224: Washing machine – Daily average load curve – Apartment, single person, 26-64 years old – Holidays

person, 26-64 yearolidays

0

5

10

15

20

25

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

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[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

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)

s oldH

STEM ENERTECH


Apartment, single person, 26-64 years oldWeekdays

0

5

10

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

15

20

25

STEM ENERTECH

144


Analysis of the wash-cycles

Cycle consumption Figures 2.226 and 2.227 tries to give us indications about the cycle consumptions. Figure 2.226 shows the cumulative frequency of the cycle consumption. All the cycles for all the washing machines were individually listed and sorted in descending order: 80 % of the washing cycles consume less than 900 Wh, 20% less than 380 Wh and only 12 % more than 1 kWh. Figure 2.227 shows the distribution of the cycles in order to determine the different washing cycles at 40°C, 60°C and 90°C. What we can see is that it is impossible to sort the washing cycles by temperature using the cycles consumption. The actual electronic regulation adapt the consumption using different parameters like the quantity of clothes, the water temperature etc.

Figure 2.226: Washing machine – Cumulative frequency of the washing cycle consumptions

Washing machineCumulative frequency of the cycle consumption

3000

3500

4000

4500

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage

Con

sum

ptio

n pe

r cyc

le (W

h

0

500

1000

1500

2000

2500

)

STEM ENERTECH

145


Washing machineDistribution of the cycle consumption

0%

5%

10%

15%

20%

25%

30%

35%

{0,20

0{

{200,4

00{

{400,6

00{

{600,8

00{

{800,1

000{

{1000

,1200

{

{1200

,1400

{

{1400

,1600

{

{1600

,1800

{

{1800

,2000

{

{2000

,2200

{

{2200

,2400

{

{2400

,2600

{

{2600

,2800

{

{2800

,3000

{

{3000

,3200

{

{3200

,3400

{

{3400

,3600

{

{3600

,3800

{

{3800

,4000

{

{4000

,4200

{

Wh

Perc

enta

geSTEM ENERTECH

Figure 2.227: Washing machine – Distribution of the washing cycle consumption

NumberFigure 2.227-B and 2.227-C represent the number of annual cycles per washing

machine. The mean value is higher for houses than for apartments: 250 against 150. This

of annual cycles

difference could be explained by the average number of persons per household: 3,1 persons per house and 2,5 persons/apartment for the sample used to create the graphs. Figure 2.227-D and 2.227-E show the annual number of cycles per person. The mean value is a little bit higher for houses: 73 cycles/person against 65 cycles/person.

146


Washing machineAnnual cycles

All houses

0

100

200

300

400

500

600

700

800

900

Num

ber o

f ann

ual c

ycle

s

Mean-Value : 230 cycles/year


Figure 2.227-B: Washing machine – Number of annual cycles – All houses

Figure 2.227-C: Washing machine – Number of annual cycles – All apartments

Washing machineAnnual cyclesAll apartments

0

100

200

300

400

500

600

700

800

900

Num

ber o

f ann

ual c

ycle

s



147


Figure 2.227-D: Washing machine – Number of annual cycles per person – All houses

Figure 2.227-E: Washing machine – Number of annual cycles per person – All apartments

Washing machineAnnual cycles per person

All houses

300

350

0

50

100

150

200

250

Num

ber o

f ann

ual c

ycle

s pe

r per

son

Energimyndigheten

Mean-Value : 73 cycles/person/year

Enertech

Washing machineAnnual cycles per person

All apartments

50

100

0

300

350

400

450

150

200

Num

ber o

f ann

ual c

ycle

s pe

r per

son

250



148


CLOTHES-DRYERS

Annualized consumptions Figures 2.228 to 2.230 shows the histogram of clothes-dryer annualized consumption for the different types of households. The analysis of the one year households didn’t show a seasonality effect. There are some significant differences from one type to the other, which can be explained by different practices. Consumption is higher in the apartments (243 kWh/year to 315 kWh/year) than in the houses (from 95 kWh/year to 131 kWh/year). For houses, it is possible to dry the clothes outside in summer and use the clothes dryer only in winter which is not the case for apartments: this behaviour can explain the big difference in consumption between the two.

Figure 2.228: Clothes dryer: annual consumption – House, family, 26-64 years old

Clothes dryerAnnual consumption


0

200

400

600

800

1000

1200

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

1400

)

STEM ENERTECH


149



Houses

0

50

100

150

200

250

300

350

400

450

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

House, couple without children, 26-

64 years old


and above

STEM ENERTECH

Mean Value : 114 kWh/yearMean Value :

95 kWh/year

Figure 2.229: Clothes dryer: annual consumption – Houses

Figure 2.230: Clothes dryer: annual consumption – Apartments


Apartments

0

100

200

300

400

500

600

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

Apartment, couple without children, 26-

64 years old


STEM ENERTECH



150


Figure 2.231 shows us the annual consumption per person per family size. The values er persons should be treated with some care, since the family structure has to be taken into

account as well. The consumption per person for houses from 2 to 6 persons is between 40 and 70 kWh/person/year. For houses with one person, the small number of household analyzed can explain the difference between this result and the rest. For apartments the consumption per person is maximum for 1 or 2 persons and decreases to around 80 kWh/person/year for 3,4 or 5 persons.

Figure 2.231: Clothes dryer: annual consumption per person per household size

Hourly load curve Figures 2.232 to 2.241 shows the daily average load curve for each type of household split between holidays and workdays. The consumption occurs mainly during the holidays.

p

Clothes dryerAnnual consumption per person per family size

0

40

60

80

100

120

140

160

1 2 3 4 5 6 1 2 3 4 5

Number of person in the household

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar/p

erso

n)

20

House Apartment

STEM ENERTECH

151


Clothes dryerDaily average load curve


0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)STEM ENERTECH

Figure 2.232: Clothes dryer – Daily average load curve – House, family, 26-64 years old – Holidays



0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH

Figure 2.233: Clothes dryer – Daily average load curve – House, family, 26-64 years old – Weekdays

152




0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH

Figure 2.234: Clothes dryer – Daily average load ouse, couples without children, 26-64 years old – Holidays

Figure 2.235: Clothes dryer – Daily average loa use, couples without children, 26-64 years old – Weekdays

curve – H



0

5

10

15

20

25

30

35

40

45

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Pow

er (W

)

d curve – Ho

Hour

STEM ENERTECH

153


154

and abov s

Figure 2.237: Clothes dryer – Daily average load curve – House, couples without children, 64 years old and above – Weekdays



0

20

40

60

80

100

120

140

160

180

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH

Figure 2.236: Clothes dryer – Daily average load curve – House, couples without children, 64 years old e – Holiday



0

20

40

60

80

100

120

140

160

180

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH




0

50

100

150

200

250

300

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Pow

er (W

)

Figure 2.238: Clothes dryer – Daily average load curve – Apartment, couples without children, 26-64

Figure 2.239: Clothes dryer – Daily average load curve – Apartment, couples without children, 26-64 years old – Weekdays

years old – Holidays

Hour

STEM ENERTECH



200

250

300

0

50

100

150

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

)

STEM ENERTECH

155




0

20

40

60

80

100

120

140

160

180

200

[ [ [ [ [ [ [ [ [ [ [ [ [

Figure 2.240: Clothes dryer – Daily average load curve – Apartment, family, 26-64 years old – Holidays

Figure 2.241: Clothes dryer – Daily average load curve – Apartment, family, 26-64 years old – Weekdays

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

10,11

[

11,12

[

12,13

[

13,14

[

14,15

[

15,16

[

16,17

[

17,18

[

18,19

[

19,20

[

20,21

[

21,22

[

22[

[23,24

[

Hour

Pow

er (W

)

,23

STEM ENERTECH


Apartment, family, 26-64 years oldWeekdays

0

20

40

60

80

100

120

140

160

180

200

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

10,11

[

11,12

[

12,13

[

13,14

[

14,15

[

15,16

[

16,17

[7,1

8[

18,19

[9,2

0[

20,21

[

21,22

[

[22,23

[

[23,24

[

Pow

er (W

)

[ [ [ [ [ [ [ [1 [ [1 [ [

Hour

STEM ENERTECH

156


Analysis of the drying-cycles

Cycle consumption Figures 2.242 and 2.243 tries to give us indications about the cycle consumptions. Figure 2.242 shows the cumulative frequency of the cycle consumptions. All the cycles for all the washing machines were individually listed and sorted in descending order: 80 % of the washing cycles consume less than 2000 Wh, 20% less than 500 Wh and only 7 % more than 3 kWh. Figure 2.243 shows the distribution of the cycles.

Figure 2.242: Clothes dryer – Cumulative frequency of the washing cycle consumption

Clothes dryerCumulative frequency of the cycle consumption

0

1000

2000

3000

4000

5000

6000

7000

Con

sum

ptio

n pe

r cyc

le (W

h

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage

)

STEM ENERTECH

157


Clothes dryerDistribution of the cycle consumption

0%

2%

4%

6%

8%

10%

12%

{0,20

0{

{400,6

00{

{800,1

000{

{1200

,1400

{

{1600

,1800

{

{2000

,2200

{

{2400

,2600

{

{2800

,3000

{

{3200

,3400

{

{3600

,3800

{

{4000

,4200

Figure 2.243: Clothes dryer – Distribution of the drying cycle consumption

Number of cycles Figure 2.243-B and 2.243-C show the number of annual cycles for houses and apartments respectively. Figure 2.243-D and 2.243-E show the number of annual cycles per person. The clothes dryers are more used in the apartments than in the houses: 53 cycles/person for apartments against 31 cycles/person for houses. This can be certainly explained by the possibility to dry the washings outside or in a specific room for houses.

{ { { {

{4400

,4600

{4800

,5000

{5200

,5400

{5600

,5800

{

{6000

,6200

{

Wh

Perc

enta

geSTEM ENERTECH

158


Clothes dryerAnnual cycles

All houses

0

100

200

300

400

500

600

700

800

Num

ber o

f ann

ual c

ycle

sEnergimyndigheten Enertech


Figure 2.243-B: Clothes dryer – Number of annual cycles – All houses

Figure 2.243-C: Clothes dryer – Number of annual cycles – All apartments

Clothes dryerAnnual cyclesAll apartments

100

0

400

200

300

Num

ber o

f ann

ual c

ycle

s

500

600



159


Clothes dryerAnnual cycles per person

All houses

0

50

100

150

200

250

Num

ber o

f ann

ual c

ycle

s pe

r per

son



Figure 2.243-D: Clothes dryer – Number of annual cycles per person – All houses

Clothes dryerAnnual cycles per person

All apartments

0

50

100

150

200

250

300

350

400

Num

ber o

f ann

ual c

ycle

s pe

r per

son



Figure 2.243- apartments

E: Clothes dryer – Number of annual cycles per person – All

160


DISHWASHERS

Annualized consumptions Figures 2.244 to 2.247 shows the histogram of dishwashers annualized consumption for different types of households. The analysis of the one year households didn’t show a seasonality effect. There are some significant differences from one type to another. Consumption for houses are between 143 and 236 kWh/year and between 74 and 214 kWh/year for apartments. In France, the Remodece+ project shows an average consumption of 273 kWh/year. As for the cold appliances, the annual consumption seems lower in Sweden.

Figure 2.244: Dishwasher: annual consumption – House, family, 26-64 years old

DishwasherAnnual consumption


400

500

600

700

800

Households

n (k

Wh/

year

0

100

200

300

Ann

ual c

onsu

mpt

io)

STEM ENERTECH


161



Houses

0

200

400

600

800

1000

1200

1400

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH



and above

Mean value : 157 kWh/year Mean value :

143 kWh/year

Figure 2.245: Dishwasher: annual consumption – Houses

162

Figure 2.246: Dishwasher: annual consumption – Apartments, family, 26-64 years old


0

100

200

300

400

500

600

700

800

900

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Apartments, family, 26-64 years old

1000

)

STEM ENERTECH



Figure 2.248 shows the annual consumption per person per family size. The values per

persons should be treated with some care, since the family structure has to be taken into account as well. The consumption per person for houses from 1 to 6 persons is between 50 and 90 kWh/person/year with an average at 70 kWh/person/year. For apartments the consumption per person are maximum between 1 and 3 persons with an average consumption of 82 kWh/person/year.


Apartments

0

50

100

150

200

250

300

350

400

450

500

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH

Apartment, couple without children, 64 years old and




Apartment, couple without children, 26-64

years old


above

Figure 2.247: Dishwasher: annual consumption – Apartments

163


DishwasherAnnual consumption per person per family size

0

20

40

60

80

100

120

1 2 3 4 5 6 1 2 3 4 5

Number of person in the household

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar/p

erso

n

Figure 2.248: Dishwasher: annual consumption per person per household size

Figures 2.249 to 2.241 shows the daily average load curve for each type of household split between holidays and workdays.

Hourly load curve

)STEM

Houses Apartments

ENERTECH

164


Figure 2.249: Dishwasher – Daily average load curve – Apartment, couples without children, 26-64 years old – Holidays

Figure 2.250: Dishwasher – Daily average load curve – Apartment, couples without children, 26-64 years old – Weekdays

DishwasherDaily average load curve


0

10

20

30

40

50

60

70

80

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH



0

10

20

30

40

50

60

70

80

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

165



Apartment, couple without children, 64 years old and aboveHolidays

0

10

20

30

40

50

60

70

80

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

Fi

gure 2.252: Dishwasher – Daily average load curve – Apartment, couples without children, 64 years old

gure 2.251: Dishwasher – Daily average load curve – Apartment, couples without children, 64 years old and above– Holidays


Apartment, couple without children, 64 years old and aboveWeekdays

0

10

20

30

40

50

60

70

80

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

Fiand above– Weekdays

166




0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

Figure 2.253: Dishwasher – Daily average load curve – Apartment, family, 26-64 years old – Holidays

Figure 2.254: Dishwasher – Daily average load curve – Apartment, family, 26-64 years old – Weekdays



0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

167


Figure 2.255: Dishwasher – Daily average load curve – Apartment, single person, 26-64 years old – Holidays

Figure 2.256: Dishwasher – Daily average load curve – Apartment, single person, 26-64 years old – Weekdays


Apartment, single person, 26-64 years oldHolidays

0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH



0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

168


Figure 2.257: Dishwasher – Daily average load curve – House, couples without children, 26-64 years old – Holidays

Figure 2.258: Dishwasher – Daily average load curve – House, couples without children, 26-64 years old – Weekdays

Dishwasher

0

10

20

30

40

50

60

70

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

Daily average load curveHouse, couple without children, 26-64 years old

Holidays

80

90

STEM ENERTECH



0

10

20

30

40

50

60

70

80

90

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

169




0

10

20

30

40

50

60

70

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

Figure 2.259: D years old and above – Holidays

Figure 2.260: Dishwasher – Daily average load curve – House, couples without children, 64 years old and above – Weekdays

ishwasher – Daily average load curve – House, couples without children, 64



0

10

20

30

40

50

60

70

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

170




0

10

20

30

40

50

60

70

80

90

100

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Hour

Pow

er (W

att)

STEM ENERTECH

Figure 2.261: Dishwasher – Daily average load curve – House, family, 26-64 years old – Holidays



0

10

20

30

40

50

60

70

80

90

100

[0,1[

[1,2[

[2,3[

[3,4[

[4,5[

[5,6[

[6,7[

[7,8[

[8,9[

[9,10

[

[10,11

[

[11,12

[

[12,13

[

[13,14

[

[14,15

[

[15,16

[

[16,17

[

[17,18

[

[18,19

[

[19,20

[

[20,21

[

[21,22

[

[22,23

[

[23,24

[

Pow

er (W

att)

Hour

STEM ENERTECH

Figure 2.262: Dishwasher – Daily average load curve – House, family, 26-64 years old – Weekdays

171


Analysis of the wash-cycles

Cycle consumption Figures 2.263 and 2.264 give us indications about the cycle consumption. Figure 2.263 shows the cumulative frequency of the cycle consumption. All the cycles for all the washing machines were individually listed and sorted in descending order: 80 % of the washing cycles consume less than 750 Wh, 20% less than 300 Wh and only 3 % more than 1 kWh. Figure 2.264 shows the distribution of the cycles. The main cycles are between 400 and 500 Watt.

Figure 2.263: Dishwasher – Cumulative frequency of the cycle consumption

DishwasherCumulative frequency of the cycle consumption

1500

2000

2500

Con

sum

ptio

n pe

r cyc

le (W

h

0

500

1000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage

)

STEM ENERTECH

172


Figure 2.264: Dishwasher – Distribution of the cycle consumption

Number of cycles Figure 2.264-B and 2.264-C show the number of annual cycles per houses and apartments respectively. Figure 2.264-D and 2.264-E indicates the number of annual cycles per person. The values are higher for apartments than for houses. The size of the dishwashers ( 6 or 12 dishes) could explain this.

Dish washertribution of the cycle consumption

0%

5%

10%

25%

{0,20

0{

{200,4

00{

{400,6

00{

{600,8

00{

{800,1

000{

{1000

,1200

{

{1200

,1400

{

{1400

,1600

{

{1600

,1800

{

{1800

,2000

{

{2000

,2200

{

{2200

,2400

{

Wh

Dis

15%

20%

rcen

tage

30%

35%

PeSTEM ENERTECH

173


DishwasherAnnual cycles

All houses

0

100

200

300

400

500

600

700

800

900

Num

ber o

f ann

ual c

ycle

s



Figu uses

re 2.264-B: Dishwasher – Number of annual cycles – All ho

DishwasherAnnual cyclesAll apartments

0

200

400

600

800

1000

1200

Num

ber o

f ann

ual c

ycle

s



Figure 2.264-C: Dishwasher – Number of annual cycles – All apartments

174


Figure 2.264-D: Dishwasher – Number of annual cycles per persons – All houses

Figure 2.264-E: Dishwasher – Number of annual cycles per persons – All apartments

DishwasherAnnual cycles per person

All houses

0

50

100

150

200

250

300

Num

ber o

f ann

ual c

ycle

s pe

r per

son

Mean-Value : 72 cycles/p


erson/year

DishwasherAnnual cycles per person

All apartments

60

700

0

100

200

300

400

500

Num

ber o

f ann

ual c

ycle

s pe

r per

so

0n

Energimyndigheten


Enertech

175


COOKING

Average possession of appliances The table from figure 2.265-A shows the average number of appliances per type of household. The number between brackets indicates the number of households used to calculate the average possession so the results for the last two categories has to be treated with care as only 3 and 4 households were analysed. There is no big difference between houses and apartments except for the stoves that are more present in houses.

Cof

fee

mac

hine

Espr

esso

mac

hine

Food

mix

er

Gril

l

Mic

row

ave

Ove

n

Stov

e

Wat

er b

oile

r

Apartment, couples without children, 26-64 years old (41) 0,51 0,02 0,00 0,00 0,78 0,24 0,73 0,51

Apartment, couples without children, 64 ye 0,43 0,00 0,07 0,00 0,71 0,29 0,71 0,29ars old and above (14)

Apartment, family, 26-64 years old (81) 0,40 0,05 0,00 0,01 0,89 0,27 0,72 0,41

Apartment, single person, 26-64 years old 1) 0,34 0,00 0,00 0,00 0,73 0,34 0,61 0,32(4

Apartment, single person, 64 years old and above (10) 0,50 0,00 0,00 0,00 0,80 0,20 0,70 0,30

0,41 0,03 0,01 0,01 0,81 0,28 0,69 0,39All apartments

House, couples without children, 26-64 years old (46) 0,48 0,04 0,00 0,00 0,89 0,35 0,74 0,39

House, couples without children, 64 years old and above (21) 0,62 0,00 0,00 0,00 0,90 0,33 0,76 0,29

House, family, 26-64 years old (125) 0,44 0,04 0,00 0,00 0,90 0,18 0,93 0,46

House, single person, 26-64 years old (3) 0,33 0,00 0,00 0,00 0,67 0,33 0,67 0,33

House, single person, 64 years old and above (4) 0,50 0,00 0,00 0,00 0,50 0,00 1,00 0,50

0,47 0,04 0,00 0,00 0,89 0,23 0,86 0,42All houses

Figure 2.265-A: Average number of cooking appliances – Per type of household

176


Seasonality effect The consumption of cooking appliances is strongly seasonal, but most of the

households were only monitored for one month. The seasonality effect was calculated using the 40 households monitored for one year. For each household, we calculated the weekly consumption by adding all the data per week. The result consists of 52 values per household corresponding to the number of weeks in one year. This set of values were then normalized to 1 (the average value gives one for each set). An average value per week was then calculated using all the data sets. Figure 2.265.1 represents the seasonality curve calculated by this method. This curve was used to calculate the annual consumption for the appliances monitored for less than six month.

Figure 2.265.1: Cooking – Seasonality effect

Annualized consumptions The two most consuming appliances present in the cooking familie are the oven and/or the kitchen stove. The rest of the appliances represent only a little part of the total consumption. Figures 2.265 to 2.272 shows the annual consumption per type of household. For the houses, the annual consumption are in the range 192 kWh/year (single person) to 411 kWh/year (family) and for the apartments it goes from 148 kWh (single person) to 377 kWh/year (family). This consumptionshow us that cooking is dependant of the numbers of person in the household as show in figure 2.273.

CookingSeasonnality effect on the consumption

0

0,2

0,4

0,6

1

1,2

1,4

1,6

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51Weeks

0,8


177


Figure 2.265: Cooking – Annual consumption – House, couples without children, 26-64 years old

Figure 2.266: Cooking – Annual consumption – House, couples without children, 64 years old and above

0

100

200

300

400

500

600

700

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECHCookingAnnual consumption



0

100

200

300

400

500

600

700

800

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

ENERTECHCookingAnnual consumption


STEM


178


Figure 2.267: Cooking – Annual consumption – House, family, 26-64 years old

Figure 2.268: Cooking – Annual consumption – House, single person, 64 years old and above

0

200

400

600

800

1000

1200

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)




0

50

100

150

200

250

300

350

400

450

500

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)


House, single person, 64 years old and above


179


Figure 2.268: Cooking – Annual consumption – Apartment, couples without children, 26-64 years old

Figure 2.269: Cooking – Annual consumption – Apartment, couples without children, 64 years old and above

0

100

200

300

400

500

600

700

800

900

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

CookingAnnual consumption


STEM


ENERTECH

0

100

200

300

400

500

600

700

800

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)

STEM ENERTECH

Annual consumptionApartment, couple without children, 64 years old and above

Cooking


180


Figure 2.270: Cooking – Annual consumption – Apartment, family, 26-64 years old

Figure 2.271: Cooking – Annual consumption – Apartment, single person, 26-64 years old

0

200

400

600

800

1000

1200

1400

1600

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Households

)




0

100

200

300

400

500

600

700

Households

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)




181


Figure 2.272: Cooking – Annual consumption – Apartment, single person, 64 years old and above

Figure 2.273 shows us the annual consumption per person as a function of the number of persons in the household. The values per person should be treated with some care, since the family structure has to be taken into account as well. This consumption will decrease from 172 kWh/person/year to 160 kWh/person/year for 2 persons to 115 kWh/person/year for 3 and then be stable around this value for 4, 5 or 6 persons. Cooking is efficient in terms of electric consumption if done for more than 2 persons.

0Households

50

100

150

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Figure 2.273: Cooking – Annual consumption per person per family size

ourly load curve HFigures 2.274 to 2.291 show the daily average load curve per type of household per

type of day (holidays and weekdays). The main peak for both type of days will be found in the evening between 17:00 and 19:00 but for the holidays, there is also a higher consumption at lunch time (13:00-14:00)

CookingAnnual consumption per person per family size

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Figure 2.274: Cooking – Daily average load curve – Apartment, couples without children, 26-64 years old – Holidays

Figure 2.275: Cooking – Daily average load curve – Apartment, couples without children, 26-64 years old – Weekdays

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CookingDaily average load curve


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STEM ENERTECHCookingDaily average load curve


184


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)Cooking

Daily average load curveApartment, couple without children, 64 years old and above

Holidays

STEM ENERTECH

Figure 2.276: Coo 64 years old and above – Holidays

Figure 2.277: Cooking – Daily average load curve – Apartment, couples without children, 64 years old and above – Weekdays

king – Daily average load curve – Apartment, couples without children,

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ENERTECHCookingSTEM


Weekdays

185


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)STEM ENERTECHCooking


Holidays

Figure 2.278: C ld – Holidays

ld – Holidays

Figure 2.279: Cooking – Daily average load curve – Apartment, family, 26-64 years old – Weekdays

ooking – Daily average load curve – Apartment, family, 26-64 years oly, 26-64 years o

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Figure 2.279: Cooking – Daily average load curve – Apartment, family, 26-64 years old – Weekdays

186


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Daily average load curveApartment, single person, 26-64 years old

Holidays

Figure 2.280 olidays

: Cooking – Daily average load curve – Apartment, single person, 26-64 years old – H

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Figure 2.281: Cooking – Daily average load curve – Apartment, single person, 26-64 years old – Weekdays

187


Figure 2.2 ve – Apartment, single person, 64 years old and above – y

Figure 2.283: Cooking – Daily average load curve – Apartment, single person, 64 years old and above – Weekdays

82: Cooking – Daily average load curHolida s

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ENERTECHCookingDaily average load curve

on, 64 years old and above

STEM

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Daily average load curve4 o

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TEM Cooking EN TECH

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188


Figure 2.284: Cooking – Daily average load curve – House, couples without children, 26-64 years old – Holidays

Figure 2.285: Cooking – Daily average load curve – House, couples without children, 26-64 years old – Weekdays

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Daily average load curveHouse, couple without children, 64 years old and above

Holidays

Fi d above – Holidays

above – Weekdays

gure 2.286: Cooking – Daily average load curve – House, couples without children, 64 years old an

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Figure 2.287: Cooking – Daily average load curve – House, couples without children, 64 years old and

190


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Daily average load curveHouse, family, 26-64 years old

Holidays

Figure lidays

F

2.288: Cooking – Daily average load curve – House, family, 26-64 years old – Ho

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igure 2.289: Cooking – Daily average load curve – House, family, 26-64 years old – Weekdays

191


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Daily average load curveHouse, single person, 64 years old and above

Holidays

Figure 2.290: Cooking – Daily average load curve – House, single person, 64 years old and above – Holidays

Weekdays

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House, single person, 64 years old and aboveWeekdays

Figure 2.291: Cooking – Daily average load curve – House, single person, 64 years old and above –

192


Annualized consumption per appliance

ven O Figures 2.292 and 2.293 show the annual consumption for the oven for houses and apartments. This consumption is 17% higher for the apartments than for the houses.

OvenAnnual consumption

All Houses

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Figure 2.292: Oven – Annual consumption – Houses

Figure 2.293: Oven – Annual consumption – Apartments

Households

)

STEM ENERTECH


OvenAnnual consumption

All Apartments

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STEM ENERTECH


193


Figure 2.294 shows the annual consumption per person as a function of the number of ersons in the household. The values per persons should be treated with some care, since the mily structure has to be taken into account as well. We can see that the more persons there

Figure 2.294: Oven – Annual consumption per person per family size

pfaare in the household, the lower is the consumption per person.

OvenAnnual consumption per person per family size

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Figures 2.295 to 2.298 shows the daily average load curve for ovens in houses and apartments per type of day (holidays and weekdays). We can see that this appliance is mainly used in the evening between 17:00 and 18:00


)

STEM ENERTECH

194


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)Oven

Daily average load curveHouse

Holidays

STEM ENERTECH

Figure 2.295: Oven – Daily average load curve – Houses – Holidays

Figure 2.296: Oven – Daily average load curve – Houses – Weekdays

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80

90

STEM ENERTECHOvenDaily average load curve

HouseWeekdays

195


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)STEM ENERTECH

OvenDaily average load curve

ApartmentHolidays

Figure 2.297: Oven – Daily average load curve – Apartment – Holidays

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STEM ENERTECHOvenDaily average load curve

ApartmentWeekdays

Figure 2.298: Oven – Daily average load curve – Apartment – Weekdays

196


Kitchen Stove The next two figures give us the annual consumption for the kitchen stove in houses and apartments. This time the highest consumption will be found for the houses at 281 kWh/year and the apartments consume 20 % less at 218 kWh/year.

Figure 2.299: Kitchen Stove – Annual consumption – Houses

Kitchen StoveAnnual consumption

All Houses

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STEM ENERTECH


197


Kitchen StoveAnnual consumption

All Apartments

0

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1000

1200

1400

Households

Ann

ual c

onsu

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(kW

h/ye

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STEM ENERTECH


Figure 2.300: Kitchen stove – Annual consumption – Apartments

Figure 2.294 shows the annual consumption per person as a function of the number of persons in the household for the kitchen stove. The values per person should be treated with some care, since the family structure has to be taken into account as well. This consumption will decrease from 142 kWh/person/year to 132 kWh/person/year for 2 persons to 92 kWh/person/year for 3 and then be stable around this value for 4, 5 or 6 persons. Using the kitchen stove for less than 3 persons is very inefficient.

Figures 2.302 to 2.305 represent the daily average load curve for kitchen stove in houses and apartments per type of day (holidays and weekdays). As for the oven, we can see that this appliance is mainly used in the evening between 17:00 and 19:00 and a little bit more at lunch time during the holidays.

198


Figure 2.301: Kitchen stove – Annual consumption per person per family size

Kitchen StoveAnnual consumption per person per family size

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1 2 3 4 5 6


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Kitchen StoveDaily average load curve

HouseHolidays

STEM ENERTECH

Figure 2.302: Kitchen Stove – Daily average load curve – Houses – Holidays

199


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)STEM ENERTECHKitchen Stove


Weekdays

Figure 2.303: Kitchen Stove – Daily average load curve – Houses – Weekdays

Figure 2.304: Kitchen Stove – Daily average load curve – Apartments – Holidays

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[9,10

[

[10,11

[

[11,12

[

[12,13

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[13,14

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[14,15

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Hours

Pow

er (W

)

STEM ENERTECH

Kitchen StoveDaily average load curve

ApartmentHolidays

200


Figure 2.305: Kitchen Stove – Daily ad curve – Apartments – Holidays

Microwave Microwave ovens are very common in the houses and apartments and their consumption represent only 38 and 29 kWh/year respectively as shown in figures 2.306 and 2.307. Using this appliance to warm cold plates is very easy and fast, that’s why they are used all the day along as shown in figures 2.308 to 2.311 which represent the daily average load curve per type of household per type of day (holidays and weekdays).

average lo

0

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[0,1[

[1,2[

[2,3[

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Hours

Pow

er (W

)STEM ENERTECHKitchen Stove

Daily average load curveApartmentWeekdays

201


MicrowaveAnnual consumption

All Houses

0

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400

500

600

700

Households

Ann

ual c

onsu

mpt

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(kW

h/ye

ar)

STEM ENERTECH


Figure 2.306: Microwave – Annual consumption – Houses

Figure 2.307: Microwave – Annual consumption – Apartments

MicrowaveAnnual consumption

All Apartments

0

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Households

Ann

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STEM ENERTECH


202


0

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Hours

Pow

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)Microwave


Holidays

STEM ENERTECH

Figure 2.308: Microwave – Daily average load curve – Houses – Holidays

0

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8

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[0,1[

[1,2[

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Pow

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)

STEM ENERTECHMicrowaveDaily average load curve

HouseWeekdays

Figure 2.309: Microwave – Daily average load curve – Houses – Weekdays

203


0

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Hours

Pow

er (W

)STEM ENERTECH

MicrowaveDaily average load curve

ApartmentHolidays

Figure 2.310: Microwave – Daily average load curve – Apartments – Holidays

Figure 2.311: Microwave – Daily average load curve – Apartments – Weekdays

0

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Pow

er (W

)

ENERTECHMicrowaveDaily average load curve

ApartmentWeekdays

STEM

204


Water boiler As for microwave, water boilers are very common in the Swedish kitchen. Their

Figure 2.312: Water boiler – Annual consumption – Houses

annual consumption represent 51 kWh/year for houses and 45 kWh/year for apartments. That’s more than the microwave and represents up to 23 % of the consumption of a kitchen tove for example. s

Water boilerAnnual consumption

All Houses

0

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Ann

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)

STEM ENERTECH


205


Water boilerAnnual consumption

All Apartments

0

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Ann

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STEM ENERTECH


Figure 2.313: Water boiler – Annual consumption – Apartments

LIGHTING The foll ual measuring

evice (called Lamp-meter), associated to each light control point of a household. This device

ption can be easily determined from these measured operating durations. This type of operation is obviously not suitable for lighting equipped with dimmer switches (like halogen lights), which were therefore monitored using a Serial-wattmeter plug.

As a rule, all the light sources of the households should have been monitored during the measurement campaigns. Let us not forget that a questionnaire allowed us to get an identification of the lighting wattage installed, per type of room and per type of source. Remarks: in the following chapter, we will use CFL or low energy lights to refer to Compact Fluorescent Lights.

owing analysis was realised thanks to the use of an individdis equipped with an optical sensor, and records the operating duration of all the light sources controlled by the same switch. By simply summing the wattage of all the lamps controlled by this switch, their associated energy consum

206


CHARACTERISTICS OF THE LIGHTING IN PLACE

Number of light sources per type By light source, we mean any bulb, fluorescent strip lighting, low energy light bulb, or

halogen spotlight. If a light fitting should comprise several sources (bulbs), each one of them is taken into account separately.

The average total number of light sources per household, all types taken together, is 42, 55.2 if we only count houses and 31.2 for apartments. Figures 2.314 to 2.316 shows for each type of household, the average number of light sources for each type of bulb per household.

Figure 2.314: Lighting – Average number of light sources per type of light bulbs – All households

LightingAverage number of light sources per type of light bulbs

All households

CFL : 5,5 light bulbs

Halogen : 0,7 light bulbs

Halogen LV : 6,1 light bulbs

Incandescent :25,4 light bulbs

Average number of light bulbs per household : 42,0

STEM ENERTECH

Fluorescent : 4,3 light bulbs

207



Houses






Average number of light bulbs per household :55,2

STEM ENERTECH

Figure 2. ouses

Figure 2.3 artments

315: Lighting – Average number of light sources per type of light bulbs – h


Apartments






Average number of light bulbs per household : 31,2

STEM ENERTECH

16: Lighting – Average number of light sources per type of light bulbs – ap

208


Number of light sources and control points per household

t sources.

Figure 2.317: Lighting – Average number of light bulbs and controls per type of room – Houses

Figures 2.317 and 2.318 show for houses and apartments the average number of light sources and the average number of control points per type of room. Just one control point is ounted, for instance if a two-way switch controls one or several lighc

For both types, the highest number of light sources is found in the living room: 8.9 and 7.1 on average. Kitchens come in second position followed by the bedrooms.

LightingAverage number of light bulbs and light controls per type of room

Houses

3,0

4,0

5,0

6,0

7,0

8,0

9,0

10,0

0,0

1,0

2,0

Living room Kitchen Bedroom Office Bathroom Outdoor-Garage

Circulation Other rooms Cellar/Store

Number of light bulbs

Number of light controls

STEM ENERTECH

209


LightingAverage number of light bulbs and light controls per type of room

Apartments

0,0

1,0

2,0

3,0

4,0

5,0

6,0

7,0

8,0

9,0

10,0

Living room Kitchen Office Bedroom Circulation Bathroom Outdoor -Garage

Other rooms Store room

Number of light bulbs

Number of light controls

STEM ENERTECH

Figure 2.318: Lig m – Apartments hting – Average number of light bulbs and controls per type of roo

Number of light sources per m2 Figures 2.319 and 2.320 show the distribution of the number of bulbs per m² for each type of household. There are more light bulbs per m² for houses (0,43) then for apartments (0,34).

210


LightingAverage number of light bulbs per m²

Houses

0

0,1

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Num

ber o

f lig

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ulbs

(bul

bs/m

²)STEM ENERTECH

Mean value : 0,43 bulbs/m²

Figure 2.319: Lighting – Number of light bulbs per m² - Houses


Apartments

0

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0,9

Households

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ber o

f lig

ht b

ulbs

(bul

bs/m

²)

STEM ENERTECH

Mean value : 0,34 bulbs/m²

Figure 2.320: Lighting – Number of light bulbs per m² - Apartments

211


Distribution of the number of bulbs per room and per type of light sources Figure 2.321 shows the distribution of the number of installed light sources as a

function of their nature and the types of room they are in.

Figure 2.321: Lighting – Distribution of the number of installed light bulbs per type of room and per type of light bulbs – All households

ANALYSIS OF THE INSTALLED LIGHTING WATTAGE

Total installed wattage Figures 2.322 and 2.323 show the distribution of the total installed lighting wattage for houses and apartments. On average, the total installed wattage, taking all light sources together, is 1618 Watt for houses and 829 Watt for apartments. The ration between houses and apartments is near 2:1 .

LightingDistribution of the number of installed light bulbs per type of room and per type of

light bulbs

0%

10%

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30%

40%

50%

60%

70%

80%

90%

100%

Bedro

om

Living r

Cellar/

S

Circula Ot Ooom

tore tion her

ffKitc

Bath

Outdoor/Gara

geice henro

om

Halogen LV

Halogen

Fluorescent

CFL

Incandescent

STEM ENERTECH

212


Figure 2.322: Lighting – Average value for the installed lighting wattage – Houses

Figure 2.323: Lighting – Average value for the installed lighting wattage – Apartments

LightingAverage value of the installed lighting wattage

Houses

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)STEM ENERTECH



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STEM ENERTECH


213


Installed wattage per type of light source

Total installed wattage per type of light source Figure 2.324 and 2.325 shows for houses and apartments the part of each source type in the total installed wattage. This representation obviously leads to giving a low weight to CFLs and other fluorescent strip lights. It is interesting to note that:

- incandescent lamps represents between 70,5 % in houses and 76,8 % in apartments of the total installed lighting wattage, - halogen lighting represents between 13 % and 15,5 % of it, - CFLs represents between 3,8 % (in apartments) to 4,5 % (in houses) of it, - fluorescent tube lighting represents between 6,3 % (in apartments) to 9,5 %

(in houses) of the total installed lighting wattage.

All fluorescent light sources taken together (tube lights and CFLs), represents 14 % of the total installed wattage in houses, and 10% in apartments.

LightingPart of each type of light sources in the total installed wattage

Houses

CFL : 4,5%

Fluorescent : 9,5%

Halogen : 4,5%

Halogen LV

Incandescent :70,5%

STEM ENERTECH

:11%

Figure 2.324: Lighting – Part of each type of light sources in the total installed wattage – Houses

214


LightingPart of each type of light sources in the total installed wattage

Apartments

CFL : 3,8%

Fluorescent : 6,3%

Halogen : 4,9%

Halogen LV : 8,1%

Incandescent :76,8%

STEM ENERTECH

Figure 2.325 Apartments : Lighting – Part of each type of light sources in the total installed wattage –

Installed wattage per type of room Figures 2.326 and 2.327 indicate that for the two types of households, the room with the highest installed wattage is the living-room. Then comes the kitchen. The values on these graphs are averaged over all the rooms of the same type. The addition of all these different wattages has therefore no physical meaning at all, and will always be different from the household average installed wattages.

215


LightingInstalled wattage per type of room

HousesOutside-Garage : 117 Watts

Office : 108 Watts

Living room262 Watts

Kitchen : 207 Watts

Circulation : 102 Watts

Bedroom : 130 Watts

Bathroom : 103 Watts

Other rooms : 81 Watts

Cellar/Store : 67 Watts

STEM ENERTECH

Figure 2.326: Lighting – Installed wattage per type of room – Houses

LightingInstalled wattage per type of room

ApartmentsOutside-Garage : 56 Watts

Office : 127 Watts

Living room : 221 Watts

Kitchen : 162 watts

Circulation : 101 Watts

Cellar/Store : 56 Watts

Bedroom : 124 Watts

Bathroom : 71 Watts

Other rooms : 67 Watts

STEM ENERTECH

Figure 2.327: Lighting – Installed wattage per type of room – Apartments

216


Total installed

wattage per m²

Figures 2.328 and 2.329 shows, for each type of household, the distributions of the average installed wattage per m². We can see that the values for houses and apartments are very near: 13 W/m² for houses and 11,1 W/m² for apartments.

Figure 2.328: Lighting – Average installed wattage per m² - Houses

LightingAverage installed wattage per m²

Houses

0,0

5,0

10,0

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20,0

25,0

30,0

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Wat

tage

(W/m

²)

STEM ENERTECH

Mean value : 13,0 W/m²

217


LightingAverage installed wattage per m²

Apartments

0,0

5,0

10,0

15,0

20,0

25,0

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Wat

tage

(W/m

²)STEM ENERTECH


Figure 2.329: Lighting – Average installed wattage per m² - Apartments

er type of source and per m² .330 to 2.339 show the distributions of the installed wattages per sample and

per m²

Installed wattage p Figure 2

for each type of light source.

218


Figure 2.330: Lighting – Average installed wattage per m² for CFL bulbs – Houses

Figure 2.331: Lighting – Average installed wattage per m² for fluorescent tubes – Houses

LightingAverage installed wattage per m², for CFL bulbs

Houses

0,0

0,5

1,0

1,5

2,0

2,5

Households

W

3,0

atta

ge (W

/m²)

STEM ENERTECH


LightingAverage installed wattage per m², for fluorescent tubes

Houses

0,0

1,0

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7,0

8,0

Households

Wat

tage

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²) 5,0

STEM ENERTECH


219


LightingAverage installed wattage per m², for Halogen bulbs

Houses

0,0

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4,0

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7,0

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9,0

10,0

Households

Wat

tage

(W/m

²)STEM ENERTECH


Figure 2.332: Lighting – Average installed wattage per m² for halogen bulbs – Houses

LightingAverage installed wattage per m², for Low Voltage Halogen bulbs

Houses

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

Wat

tage

(W/m

²)

Figure 2.333: Lighting – Average installed wattage per m² for low voltage halogen bulbs – Houses

Households

STEM ENERTECH


220


Figure 2.334: Lighting – Average installed wattage per m² for incandescent bulbs – Houses

Figure 2.335: Lighting – Average installed wattage per m² for CFL bulbs – Apartments

Lighting

0,0

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10,0

15,0

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Wat

tage

(W/m

²)

Average installed wattage per m², for incandescent bulbsHouses

25,0

20,0

STEM ENERTECH


LightingAverage installed wattage per m², for CFL bulbs

Apartments

0,0

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Households

Wat

tage

(W/m

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STEM ENERTECH


221


LightingAverage installed wattage per m², for fluorescent tubes

Apartments

0,0

0,5

1,0

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3,0

Households

Wat

tage

(W/m

²)STEM ENERTECH


Figure 2.336: Lighting – Average installed wattage per m² for fluorescent tubes – Apartments

Figure 2.337: Lighting – Average installed wattage per m² for halogen tubes – Apartments

LightingAverage installed wattage per m², for Halogen bulbs

Apartments

0,0

1,0

2,0

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Wat

tage

(W/m

²)

STEM ENERTECH


222


LightingAverage installed wattage per m², for Low Voltage Halogen bulbs

Apartments

0,0

2,0

4,0

6,0

8,0

10,0

12,0

Households

Wat

tage

(W/m

²)STEM ENERTECH


Figure 2.338: Lighting – Average installed wattage er m² for low voltage halogen tubes – Apartments

Figure 2.339: Lighting – Average installed wattage per m² for incandescent tubes – Apartments

p

LightingAverage installed wattage per m², for incandescent bulbs

Apartments

0,0

5,0

10,0

15,0

20,0

25,0

Wat

tage

(W/m

²)

Households

STEM ENERTECH


223


Distribution of the unit wattage of the bulbs, per type of light source

ies information about the nature of e household equipment, and it also allows to target a better DSM action over a particular

Figure 2.340: Lighting – Distribution of the incandescent light bulbs unit wattage

Graphs 2.340 to 2.344 represent the distributions of the unit lighting wattage for the installed equipment. This is an important point, as it supplthtype of light source. A succinct analysis can be done for each type of light bulbs:

• almost 34 % of the GLS (General Lighting Service) incandescent bulb wattage is 40 W. Then come the 25 W followed by the 60 W light bulbs (about 27 % and 17 % each). There are almost no 100 W light bulbs,

• halogen lighting is dominated by low voltage halogens, with a wattage lower than 50 W. The dominant class is centred on 20 W (60 %). Powerful halogen lights (more than 250 W) represent 12,5 % of the halogen light stock,

• the stock of fluorescent tube lights essentially comprises 18W (50 %) and 36 W (30 %) tube lights,

• low energy light stock comprises 40 % of 11 W CFL bulbs (9-12 W class), and then 7 W.

LightingDistribution of the incandescent light bulbs unit wattage

0,0%

5,0%

1 4 7 10

10,0%

15,0%

20,0%

25,0%

35,0%

40,0%

15 20 24 30 35 40 50 60 70 80 110

190

300

Wattage (W)

30,0%

Dis

trib

utio

n (%

)


224


LightingDistribution of the CFL light bulbs unit wattage

0,0%

5,0%

10,0%

15,0%

20,0%

25,0%

30,0%

35,0%

40,0%

45,0%

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 20 21 23 25 26 28 36 40

Wattage (W)

Dis

trib

utio

n (%

)ENERTECHEnergimyndigheten

Figure 2.341: Lighting – Distribution of the CFL light bulbs unit wattage

LightingDistribution of the fluorescent light tubes unit wattage

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

4 5 6 7 8 9 11 13 14 15 16 18 20 22 25 26 28 30 35 36 38 40 58 60

Wattage (W)

Dis

trib

utio

n (%

)


Figure 2.342: Lighting – Distribution of the fluorescent light tubes unit wattage

225


Figure 2.343: Lighting – Distribution of the halogen light bulbs unit wattage

Figure 2.344: Lighting – Distribution of the low voltage halogen light bulbs unit wattage

LightingDistribution of the halogen light bulbs unit wattage

0,0

5,0

10,0%

15,0%

20,0%

25,0%

30,0

Dis

trib

utio

n (%

)

%10 20 25 28 30 35 40 42 50 60 75 100 150 300 350 500

Wattage (W)

%

%

35,0%

40,0%


LightingDistribution of the low voltage halogen light bulbs unit wattage

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

3 5 6 8 9 10 11 12 13 15 17 20 25 28 30 35 40 50

Dis

trib

utio

n (%

)

Wattage (W)


226


ANNUALIZED LIGHTING CONSUMPTION

Seasonality effect The consumption for lighting is strongly seasonal, but most of the households were

only monitored for one month. The seasonality effect was calculated using the 40 households monitored for one year. For each household, we calculated the weekly consumption by adding all the data per week. The result output consists of 52 values per household corresponding to the number of weeks in one year. This set of values was then normalized to 1 (the average value gives one for each set). An average value per week was then calculated using all the data sets. Figure 2.345 represents the seasonality curve calculated by this method. This curve was used to calculate the annual consumption for the lights monitored for less than six month.

Figure 2.345: Lighting – Seasonality effect on the consumption

Annualized consumption per household Figures 2.346 to 2.353 represent the distribution of the total lighting consumption for the different household categories. For houses, the annual consumption is in the range 646-937 kWh/year and 240-691 kWh/year for apartments.

LightingSeasonnality effect on the consumption

01 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51

Weeks

0,2

1

1,

1,4

1,6

1,8

2

0,4

0,6

0,8

2

STEM ENERTECH

227


LightingAnnualized consumption per household


0

500

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2000

2500

3000

3500

Households

Con

sum

ptio

n (k

Wh/

year

)STEM ENERTECH


Figure 2.346: L 26-64 years old

Figure 2.347: ears old and

ighting – Annualized consumption – House, couples without children,



0

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Con

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)

STEM ENERTECH


Lighting – Annualized consumption – House, couples without children, 64 yabove

228


Figure 2.348: Lighting – Annualized consumption – House, family, 26-64 years old

Figure 2.349: Lighting – Annualized consumption – Apartment, couples without children, 26-64 years old



0

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6000

7000

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Households

Con

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Wh/

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)STEM ENERTECH


Lighting

0

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Households

Con

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)

Annualized consumption per householdApartment, couple without children, 26-64 years old

STEM ENERTECH


229




0

200

400

600

800

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1400

1600

Households

Con

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)STEM ENERTECH


Figure 2.350: L , 64 years old and above

Figure 2.351: Lighting – Annualized consumption – Apartment, family, 26-64 years old

ighting – Annualized consumption – Apartment, couples without children



0

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3000

Households

Con

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)

STEM ENERTECH


230




0

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1200

Households

Con

sum

ptio

n (k

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)STEM ENERTECH


Figur s old

Figur bove

e 2.352: Lighting – Annualized consumption – Apartment, single person, 26-64 year



0

100

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600

700

800

900

1000

Households

Con

sum

ptio

n (k

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e 2.353: Lighting – Annualized consumption – Apartment, single person, 64 years old and a

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Annualized consumption per person Figure 2.354 shows us the annual consumption per person as a function of the number of persons in the household. The values per persons should be treated with some care, since the family structure has to be taken into account as well. This consumption is equal to 340 kWh/person/year for 1 or 2 persons, 285 kWh/person/year for household with 3 or 4 persons and then decrease to 200 kWh/person for 6 persons.

Figure 2.354: Lighting: Annual consumption per person

Annualized consumption per m2 Figures 2.355 and 2.356 show us the annual consumption per m² for both types of households. It is interesting to note that the values are very near: 6,7 kWh/m²/year for houses and 6,3 kWh/m²/year for apartments so it’s the difference of size between houses and apartments that will explain the difference of consumption between the two.

LightingAnnual consumption per person per family size

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LightingAnnualized consumption per m²

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Mean value : 6,7 kWh/year/m²

Figure 2.355: Lighting – Annual consumption per m² - Houses

Figure 2.356: Lighting – Annual consumption per m² - Apartments

LightingAnnualized consumption per m²

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Mean value : 6,3 kWh/year/m²

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Annualized consumption per type of room Figures 2.357 and 2.358 will answer the question

What is the average lighting consumption of a living-room or a bedroom for both type of households ? The two rooms with the highest consumption are the living room and the kitchen. For houses, the kitchen take the first place with 178 kWh/year followed by the living room with 150 kWh/year. For apartments, the living room will beat the kitchen.

Figure 2.357: Lighting – Annual consumption per type of room – Houses

LightingAverage annual consumption per type of room

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Figure 2.358: Lighting – Annual consumption per type of room – Apartments

TRUCTURE OF THE ANNUALIZED LIGHTING CONSUMPTION S

Structure of the consumption per type of room, from the grid point of view Figure 2.359 shows the consumption structure per type of room, from the grid point of view. In order to obtain this graph, we summed all observed consumption for every household over all the measurement periods, and we grouped them together by type of room. Then we referred the total consumption of each type of room to the total observed lighting consumption of all the households. The result tells us about the final usage of the supplied electricity. This study highlights that in the houses, there’s no “most consuming room”, the total consumption is split between the different type of rooms. For apartments, the kitchen, the living room and circulations represent 60% of the total consumption.

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Figure 2.359: Lighting – Structure of the annual consumption per type of room – From the grid point of view

Structure of the consumption per type of light source, from the grid point of view Figure 2.360 shows the same kind of analysis as in the former paragraph, but as a function of the light source type, and not of the room type. Taking into account its very low energy efficiency, incandescence lighting represents the most important part of the total lighting consumption, with 65 % for houses and 72 % for apartments. If the halogen part is added, the part of these merged sources is 82 % for houses and 86 % for apartments. Finally, the low energy lamps fraction, varies from 6 to 10 %.

LightingStructure of the consumption per type of room

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LightingStructure of the consumption per type of light source

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Figure 2.360: oint of view Lighting – Annual consumption per type of light sources – From the grid p

AVERAGE HOURLY LOAD CURVE

Hourly load curve per type of household Figures 2.361 to 2.378 represent the average hourly load curve observed for the households as a whole, for each type of household. It is notable that lighting consumption during the night exist in any type of household. It is less than probable that this consumption could be entirely due to night users. Here is a potential energy saving that is sometimes significant. The main peak is always between 20:00 and 22:00 and goes from 135 to 300 Watt for houses and 90 to 200 Watt for apartments. The maximum power demand for the two types of households is always obtained for families.

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Figure 2.361: Lighting – Daily average load curve – Apartment, couples without children, 26-64 years old

igure 2.362: Lighting – Daily average load curve – Apartment, couples without children, 26-64 years old – Weekdays

– Holidays

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Figure 2.363: Lighting – Daily average load curve – Apartment, couples without children, 64 years old and above – Holidays

Figure 2.364: Lighting – Daily average load curve – Apartment, couples without children, 64 years old and above – Weekdays

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Figure 2.365: Lighting – Daily average load curve – Apartment, family, 26-64 years old – Holidays

Figure 2.366: Lighting – Daily average load curve – Apartment, family, 26-64 years old – Weekdays

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Figure 2.36 Holidays

Figure 2.368: Lighting – Daily average load curve – Apartment, single person, 26-64 years old – Weekdays

7: Lighting – Daily average load curve – Apartment, single person, 26-64 years old –

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Daily average load curveApartment, single person, 64 years old and above

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Figure 2.369: Lighting – Daily average load curve – Apartment, single person, 64 years old and above – Holidays

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Figure 2. bove – 370: Lighting – Daily average load curve – Apartment, single person, 64 years old and aWeekdays

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Figu – Holidays

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re 2.371: Lighting – Daily average load curve – House, couples without children, 26-64 years old

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igure 2.372: Lighting – Daily average load curve – House, couples without children, 26-64 years old –

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Figure 2.373: Lighting – Daily average load curve – House, couples without children, 64 years old and above – Holidays

Figure 2.374: Lighting – Daily average load curve – House, couples without children, 64 years old and above – Weekdays

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Figure 2.375: L ld – Holidays

ighting – Daily average load curve – House, family, 26-64 years o

Figure 2.376: Lighting – Daily average load curve – House, family, 26-64 years old – Weekdays

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LightingDaily average load curve

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Figure 2.377: Lighting – Daily average load curve – House, single person, 64 years old and above – Holidays

Figure 2.378: Lighting – Daily average load curve – House, single person, 64 years old and above – Weekdays

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AUDIOVISUAL SITE

Description of the monitored equipment In order to limit the number of meters used, parts of the existing appliances were monitored together with TV’s always monitored apart. We rather looked for a total vision of the audiovisual consumptions, by monitoring in each household the « audiovisual site». This site usually groups all the equipment that are around television sets. Here is the average composition of the audiovisual site for houses and apartments:

Device Houses ApartmentsTV 2,11 1,52 Hi-fi 1,12 0,88 DVD player 0,98 0,73 VCR 0,83 0,72 Satellite 0,72 0,29 Home cinema 0,12 0,08 Xbox 0,05 0,02 Surround system 0,03 0,00 PS2 0,03 0,07 Projector 0,02 0,02 Cable TV Box 0,01 0,01 Tuner 0,01 0,01

Figure 2.379.1: Composition of the audiovisual site

nce

composing the audiovisual site: The table from Figure 2.379.2 shows the individual numbers of each applia

Device Houses Apartments

TV 419 285 Hi-fi 223 166 DVD 195 138 VCR 166 136 Satellite 143 55 Home cinema 23 15 Xbox 9 4 Surround system 6 0 PS2 6 13 Projector 3 3 Cable TV Box 1 1 Tuner 1 1

Figure 2.379.2: Number of appliances monitored per type of appliance

Seasonality effect The consumption for audiovisual is strongly seasonal, but most of the households were

only monitored for one month. The seasonality effect was calculated using the 40 households monitored for one year. For each household, we calculated the weekly consumption by adding all the data per week. The result output consists of 52 values per household corresponding to

247


the number of weeks in one year. This set of values was then normalized to 1 (the average value gives one for each set). An average value per week was then calculated using all the data sets. We calculated two different seasonality curves, one for “Audiovisual site excl. TV” and one for the TV. Figures 2.379.1 and 2.379.2 represent the seasonality curve calculated by this method. These curves were used to calculate the annual consumption for the audiovisual sites and TV’s monitored for less than six month. We summed the two results to create the Audiovisual site as analyzed in this chapter.

Audiovisual site excl. TVSeasonnality effect on the consumption

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Figure 2.379.1: Audiovisual site excl. TV – Seasonality effect on the consumption

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TelevisionSeasonnality effect on the consumption

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Figure 2.379.2: Television – Seasonality effect on the consumption

Annualized consumption the distribution of the total audiovisual site gories. For houses, the annual consumption is in

r for apartments.

Figure 2.379: Audiovisual site – Annual consumption – House, couples without children, 26-64 years old

Figures 2.379 to 2.387 represent consumption for the different household catethe range 233-428 kWh/year and 185-309 kWh/yea

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Figure 2.380: Audiovisual site – Annual consumption – House, couples without children, 64 years old and above

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Figure 2.381: Audiovisual site – Annual consumption – House, family, 26-64 years old

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Figure 2.382: Audiovisual site – Annual consumption – House, single person, 64 years old and above

igure 2.383: Audiovisual site – Annual consumption – Apartment, couples without children, 26-64 yearsold

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Fig ld and above

Figure 2.385: Audiovisual site – Annual consumption – Apartment, family, 26-64 years old

ure 2.384: Audiovisual site – Annual consumption – Apartment, couples without children, 64 years o

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Figure 2.386: Audiovisual site – Annual consumption – Apartment, single person, 26-64 years old

gure 2.387: Audiovisual site – Annual consumption – Apartment, single person, 64 years old and above

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Figure 2.388 shows the annual consumption per person as a function of the number of persons in the household. The values per person should be treated with some care, since the family structure has to be taken into account as well. We can see that the more persons are in the household, the lower is the consumption per person. This indicates that the annual consumption for the audiovisual site is not a direct function of the number of persons. This can be understood easily: the consumption of a TV will remain the same if there is 1 person in front of the TV or 6.

Figure 2.388: Audiovisual site – Annual consumption per person per family size

Hourly load curve per type of household Figures 2.389 to 2.406 represents the average hourly load curve observed, for each type of household. It is notable that audiovisual consumption during the night exists in all types of households. It is less than probable that this consumption could be entirely due to night users but more probably due to Standby consumptions. Here is also a potential energy saving that is sometimes significant. The main peak is always between 20:00 and 22:00. The maximum power demand for the two types of households is always obtained for families.

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Figure 2.389: Audiovisual site – Daily average load curve – Apartment, couples without children, 26-64 old – Holidyears ays

Figure 2.390: Audiovisual site – Daily average Apartment, couples without children, 26-64 years old – Weekdays

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Figure 2.391: Audiovisual site – Daily average load curve – Apartment, couples without children, 64 years old and above – Holidays

igure 2.392: Audiovisual site – Daily average load curve – Apartment, couples without children, 64 years old and above – Weekdays

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e 2.393: Audiovisual site – Daily average load curve – Apartment, family, 26-64 years old – Holid

Figure 2.394: Audiovisual site – Daily average load curve – Apartment, family, 26-64 years old – Weekdays

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Figure 2.395: Audiovisual site – Daily average load curve – Apartment, single person, 26-64 years old – Holidays

Figure 2.396: Audiovisual site – Daily average load curve – Apartment, single person, 26-64 years old –

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Figure 2.397: Audiovisual person, 64 years old and site – Daily average load curve – Apartment, singleabove – Holidays

Figure 2.398: Audiovisual site – Daily average load curve – Apartment, single person, 64 years old and above – Weekdays

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Figure 2.399: Audiovisual site – Daily average load curve – House, couples without children, 26-64 years old – Holidays

Figure 2.400: Audiovisual site – Daily average load curve – House, couples without children, 26-64 years old – Weekdays

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Figure 2.401: Audiovisual site – Daily average load curve – House, couples without children, 64 years old and above – Holidays

Figure 2.402: Audiovisual site – Daily average load curve – House, couples without children, 64 years old and above – Weekdays

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Figure 2.403: Audiovisual site – Daily average load curve – House, family, 26-64 years old – Holidays

Figure 2 kdays

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.404: Audiovisual site – Daily average load curve – House, family, 26-64 years old – Wee

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Figure 2.405: Audiovisual site – Daily average load curve – House, single person, 64 years old and above – Holidays

Figure 2.406: Audiovisual site – Daily average load curve – House, single person, 64 years old and above – Weekdays

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Standby consumption Figures 2.407 shows the time distribution between the 3 main states of the audiovisual site: ON mode when used, Stand By mode where the appliances continue to consume energy but are not used and OFF mode when the appliances are disconnected from the plug. These states where calculated for each audiovisual site individually. The sites were analyzed graphically to separate the Standby power from the ON power. The graph was calculated by averaging each state for all the sites. They are in ON mode 32,7 % of the time (2864 hours per year), in Standby mode 60,5 % of the time (5300 hours per year) and in OFF mode the rest of the time (596 hours per year).

Figure 2.407: Audiovisual site – Consumption distribution between the different states

Figure 2.408 shows the daily average load curve split between ON mode and Standby mode. We can see that most of the night consumption is due to Standby . The Standby is minimal between 20:00 and 22:00, corresponding to the hours where the site is often used.

Audiovisual siteTime distribution between the different states

OFF mode (P=0W) : 6,8%

ON mode : 32,7%


Standby mode : 60,5%

Mean power in ON mode : 85 Watt

Mean power in Standby mode : 15 Watt

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Audiovisual siteDaily average load curve splitted between ON mode and Standby

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Figure 2.408: Audiovisual site – Daily average load curve split between On mode and Standby

nalysis per type of equipment A

TV

Annualized consumptions Figure 2.409 and 2.410 show the annual consumption for TV for the two types of households. All the TV’s present in the households were used to calculate these average values. Figure 2.411 shows the average annual consumption from the most consuming TV to the less consuming one. To obtain these values, we sorted for each household the TV’s from the most consuming one to the less consuming one and then averaged all the most consuming ones together, the second most consuming ones together etc. The main TV has an average annual consumption of 174 kWh/year, the second one has a consumption of 51 kWh/year. Figure 2.412 shows the annual consumption per person as a function of the number of persons in the household. The values per person should be treated with some care, since the family structure has to be taken into account as well. For household with one person, the annual consumption is near 130 kWh/year. This consumption decreases then with the number of persons in the household. As explained before, the consumption of the TV won’t change if there is 1 or more persons who use it.

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Figure 2.409: TV – Annual consumption – Houses

Figure 2.410: TV – Annual consumption – Apartments

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Figure 2.411: TV – Annual consumption

Figure 2.412: TV – Annual consumption per person per family size


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Average number of TV per house : 2,1Average number of TV per apartment : 1,5

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Figure 2.413: TV – Structure of the daily average load curve – Houses – Holidays

Figures 2.413 to 2.416 represent the average hourly load curve observed, for each type of household split between holidays and workdays. It is notable that TV consumption during the night exists in all types of households. It is less than probable that this consumption could be entirely due to night users but more probably due to Standby consumption. There is here also a potential energy saving that is sometimes significant. The main peak is always between 20:00 and 22:00.

TVDaily average load curve

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Figure 2.414: TV – Structure of the daily average load curve – Houses – Weekdays

Figure 2.415: TV – Structure of the daily average load curve – Apartments – Holidays


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Figure 2.416: TV – Structure of the daily average load curve – Apartments – Weekdays

Standby power analysis Figures 2.417 shows the time distribution between the 3 main states of the TV’s: ON mode when used, Standby mode where the appliances continue to consume energy but are not used and OFF mode when the appliances are disconnected from the plug. These states where calculated for each TV individually. The TV’s were analyzed graphically to separate the Standby power from the ON power. The graph was calculated by averaging each state for all the TV’s. They are in ON mode 23 % of the time (2015 hours per year), in Standby mode 31 % of the time (2716 hours per year) and in OFF mode the rest of the time (4038 hour per year). TV’s are more often in OFF mode than the complete audiovisual site: it is easier and more natural to switch off the TV than the rest of the devices like DVD’s, satellite etc.

270


TVTime distribution between the different states

OFF mode (P=0W) : 46 %

Standby mode : 31 %

ON mode : 23 %

STEM ENERTECH


Mean power in Standby mode : 4,8 Watt

Figure 2.417: TV – Time distribution between the different states

ge load cu Figure 2.418 shows the daily avera rve split between ON mode and Standby ode. We can see that a large part of the night consumption is due to Standby . The Standby

Figure 2.418: TV – Daily average tween ON mode and Standby

mis minimal between 20:00 and 22:00, corresponding to the hours where the TV is often used.

TVDaily average load curve splitted between ON mode and Standby

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271


Other Audiovisual appliances

Annual consumption The table from figure 2.419 lists all the appliances or group of appliances that were monitored individually. The audiovisual site was calculated by adding all the individual appliances present in this table.

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VCR + DVD + Satellite + Home

nema 15 270 110 (2) 185 (3) 130 (1) 337 (1) 350 (8)

ci

VCR + DVD + Cable TV Box 2 247 128 (1) 367 (1)

VCR + DVD + Tuner 2 220 107 (1) 333 (1)

DVD + Satellite + Home cinema 10 216 115 (1) 183 (3) 379 (2) 253 (1) 162 (3)

VCR + DVD + Satellite 48 174 178 (4) 150 (2) 203 (4) 177 (1) 147 (10) 154 (2) 183 (25)

VCR + Satellite + Modem 2 173 139 (1) 207 (1)

VCR + DVD + PS2 5 151 47 (2) 112 (1) 276 (2) Hi-fi + VCR + DVD 3 131 131 (3)

Home cinema 13 124 392 (1) 14 (1) 10 (1) 120 (10) VCR + Satellite 21 123 107 (2) 83 (3) 145 (7) 151 (3) 93 (5) 180 (1)DVD + Surround

system 5 118 15 (1) 144 (4)

DVD + Satellite 59 101 78 (5) 17 (2) 101 (8) 116 (6) 93 (4) 108 (34) Satellite 41 95 158 (1) 79 (6) 108 (3) 96 (9) 74 (2) 97 (20)

VCR + Xbox 5 84 111 (1) 167 (1) 62 (1) 41 (2) Hi-fi + DVD 6 83 18 (1) 112 (1) 157 (1) 71 (3)

Xbox 8 81 315 (1) 122 (1) 36 (6) VCR + DVD 109 65 53 (9) 66 (34) 74 (12) 92 (2) 59 (12) 69 (6) 62 (32) 89 (2)

VCR 77 57 98 (1) 63 (10) 35 (4) 44 (12) 62 (8) 9 (3) 53 (8) 77 (7) 63 (22) 49 (2) Hi-fi 370 52 88 (2) 42 (33) 13 (5) 61 (80) 38 (28) 34 (7) 90 (2) 62 (56) 36 (15) 50 (136) 66 (3) 50 (3)

Speaker 6 47 50 (2) 45 (4) Sub woofer 8 42 12 (1) 7 (2) 130 (1) 42 (2) 47 (2) P rojector 5 40 34 (2) 5 (1) 64 (2)

DVD 66 32 64 (6) 2 (1) 2 (1) 18 (3) 28 (30) 38 (20) 7 (5) 1Playstation 14 30 38 (10) 3 (2) 18 (2)

272


Game cube 3 29 36 (2) 13 (1) Synthesizer 6 27 52 (2) 15 (4) CD Radio 3 23 32 (2) 7 (1)

Radio 99 14 18 (5) 9 (7) 13 (16) 7 (12) 10 (3) 20 (12) 10 (8) 16 (32) 96 (1) 8 (3)

Figure 2.419: Other audiovisual appliances – Annual consumption

Standby power The table from figure 2.420 shows the different Standby powers that were measured

individually at installation time or extracted from the monitored data. If the number of annual hours in Standby mode is know, it is possible to use the power to calculate the annual Standby consumption: for example, a satellite box that will stay in Standby 90 % of the time will have a consumption of 0,9 * 8760 * 9,1 = 71,7 kWh/year.

Appliance Number monitored Power (Watt) VCR + Satellite 4 33,8

VCR + DVD + Satellite 4 21,6 DVD + Sattelite 5 20,1

VCR + DVD + Satellite + Home cinema 1 16,2 Digital TV Box 9 11,4

Hi-fi + DVD 2 10,9 TV + VCR 3 10,6

Cable TV Box 4 9,6 Satelite 154 9,1

Home cinema 26 7,6 Subwoofer 4 7,4 Projector 2 7,2

Tuner (Audio) 1 6,4 VCR 195 6,4

LCD TV 1 6,1 Hi-fi 291 5,4

VCR + DVD 29 5,3 Cassette player 2 4,5

Surround system 6 3,9 DVD 145 3,8

Synthesizer 1 3,6 CD Player 11 3,2

TV 242 3,1 Antenna amplifier 23 2,8 Wireless headset 9 2,7

Xbox 1 8 2,5 Amplifier (Audio) 6 2,5

Radio 229 2,1 Gramophone 2 1,6 Playstation 2 12 1,4

Digital antenna 2 1,3 Nintendo Gamecube 4 1,0

Figure 2.420: Other audiovisual appliances – Standby power

273


COMPUTER SITES

Description of the monitored equipment In about 10 years, the quick development of information technologies deeply modified the household energy landscape. The new equipment leads to new electricity consumption. These latter sometimes represents the biggest consumption sector in the household. This usage draws a big quantity of electricity. All the more so, when this equipment is badly used, or used very intensively, it might become the most important in the household. Computer equipment, as most of the electronic appliances, might draw much Standby power. It looked therefore interesting and justified, in this project, to meter the computer sites, and to explore the behaviours of the appliances they are made up of. It is probably the first time in Europe that a so important campaign on computers is carried out, as 451 computer sites and 139 laptops were studied and metered. In a « computer site », we included all the appliances that make up a working place. In the great majority, it consists of a CPU, a monitor and a printer, as well as most of the times a modem/ADSL box. The total consumption of this set will be analysed, rather than the consumption of each one of these appliances.

Annualized consumption No seasonality effect could be observed with the one year household. Therefore the

ption was calculated without seasonality correction. annualized consumFigures 2.421 to 2.426 represent the distribution of the total computer site

onsumption for the different household categories. For houses, the annual consumption is in cthe range 191-390 kWh/year and 170-287 kWh/year for apartments. The maximum consumption for houses (4846 kWh/year) was measured for an one year house with 4 computer sites that were ON most of the time. The maximum consumption for apartments (2955 kWh/year) was measured for a one month apartment with 3 computer sites that were ON most of the time.

274


Figure 2.421: Computer site – Annual consumption – House, couples without children, 26-64 years old

Figure 2.422: Computer site – Annual consumption – House, couples without children, 64 years old and

above

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Figure 2.423: Computer site – Annual consumption – House, family, 26-64 years old

Figure 2.424: Computer site – Annual consumption – Apartment, couples without children, 26-64 years old

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Figure 2. ars old and above

425: Computer site – Annual consumption – Apartment, couples without children, 64 ye

Figure 2.426: Computer site – Annual consumption – Apartment, family, 26-64 years old

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Figure 2.427 shows the annual consumption per person as a function of the number of persons in the household. The values per persons should be treated with some care, since the

ount as well. The annual consumption for a single person is 207 kWh/year, for more than one person this value is in the range 120-160

person/year. There is no clear pattern that shows that more persons/less consumption per person. It seems that the computer site is very dependant of the number of persons in the

Figure 2.427: Computer site – annual consumption per person per family size

Hourly load curve The average hourly load curves are shown in figures 2.428 to 2.443. Computer site consumption grows progressively from a minimum value during the night (consumption is then mostly due to Standby power), to a mevening (the peak demand value varies much from one type of household to the other). Then it decreases rather suddenly at the beginning of the night to its lowest level. The consumption of the sites that are ON between 02.00 and 03.00 hours is still very important. Computers are often used during the night, unless users forget to stop their CPUs over the night.

family structure has to be taken into acc

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Computer siteAnnual consumption per person per family size

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Computer siteDaily average load curve


Figure 2.428: Compute ithout children, 26-64 years old – Holidays

Figure 2.429: Computer site – D es without children, 26-64 years old – Weekdays

r site – Daily average load curve – Apartment, couples w

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Figure 2.430: Com children, 64 years old and above – Holidays

Figure 2.431: Computer site – Daily average load curve – Apartment, couples without children, 64 years old and above – Weekdays

puter site – Daily average load curve – Apartment, couples without

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2.434: Computer site – Daily average load curve – Apartment, single person, 26-64 years

435: Computer site – Daily average load curve – Apartment, single person, 26-64 years ol

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Figure 2.436: Computer site – Daily average load curve – Apartment, single person, 64 years old and above – Holidays

Figure 2.437: Computer site – Daily average load curve – Apartment, single person, 64 years old and above – Weekdays

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.439: Computer site – Daily average load curve – House, couples without children, 26-64 years

38: Computer site – Daily average load curve – House, couples without children, 26

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Figure 2.442: Computer site – Daily average load curve – House, family, 26-64 years old – Holidays

Figure 2.443: Computer site – Daily average load curve – House, family, 26-64 years old – Weekdays

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STEM ENERTECHComputer siteDaily average load curv

ouse, family, 26-64 years Holidays

eH old

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ENERTECHComputer siteDaily average load curve

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Standby consumption Figures 2.444 shows the time distribution between the 3 main states for the computer site: ON mode when used, Standby mode where the appliances continue to consume energy but are not used and OFF mode when the appliances are disconnected from the plug. These tates where calculated for each computer site individually. The sites were analyzed raphically to separate the Standby power from the ON power. The graph was calculated by

Figure 2.444: Computer site: Consumption distribution between the different states

Figure 2.445 shows the daily average load curve split between ON mode and Standby mode. We can see that a large part of the night consumption is due to Standby (as for the audiovisual site). The Standby is minimal between 19:00 and 22:00, corresponding to the hours where the computer is often used.

sgaveraging each state for all the sites. They are in ON mode 26 % of the time (2278 hours per year), in Standby mode 56 % of the time (4906 hours per year) and in OFF mode the rest of the time (1576 hour per year).

Computer siteConsumption distribution between the different states

OFF mode (P=0W) : 18 %

Standby mode :56 %

ON mode : 26 %



Mean power in Standby mode : 14 Watt

287


Computer siteDaily average load curve splitted between ON mode and Standby

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STEM ENERTECH

Figure 2.445: Computer site: Daily average load curve split between ON mode and Standby

Analysis per type of equipment

Annualized consumption The table from figure 2.446 lists all the different devices monitored separately during the campaign. The most interesting part is to compare the annual consumption for a desktop computer with the annual consumption for a laptop: 343 kWh/year to 35 kWh/year! , the ratio is very near to 10-1.

288


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All appliances Annual consumption kWh/year (Number of appliance) Broadband 3 38 42 (2) 32 (1) Computer

(desktop/Monitor/modem) 441 343 188 (2)

255 (41)

171 (10)

560 (106)

172 (30) 51 (3) 362 (1) 195

(45) 177 (19)

342 (178) 138 (4) 152 (2)

Harddisk 1 12 12 (1) Laptop 139 35 30 (17) 43 (32) 12 (10) 47 (1) 10 (1) 25 (11) 59 (5) 36 (61) Modem 5 80 28 (1) 49 (2) 75 (1) 199 (1) Printer 34 45 9 (4) 75 (1) 70 (8) 25 (4) 23 (1) 29 (4) 51 (12)

Monitor + Scanner + Printer + Router 2 214 11 (1) 417 (1)

Monitor 2 27 27 (2) UPC Modem 5 52 19 (1) 86 (1) 58 (2) 39 (1)

Figure 2.446: Average annual consumption per device

Standby power analysis The table from figure 2.447 show the different Standby power that were measured

individually at installation time or extracted from the monitored data for computer devices. If the number of annual hours in Standby mode is know, it is possible to use the power to calculate the annual Standby consumption: for example, a printer that will stay in Standby 90 % of the time will have a consumption of 0,9 * 8760 * 5,2 = 41 kWh/year.

Appliance Number monitored Power (Watt) Computer site 288 15,5 External harddisk 2 9,6 Laptop 29 2,6 Modem/Router (ADSL) 177 7,2 Printer 35 5,2 Switch 6 5,4

Figure 2.447: Standby power per device

289


HEATING/WATER HEATER

Description of the monitored equipment There are different types of heating depending on the energy used: direct electric heating, heat pump, gas, wood, district heating etc. Each type of heating needs different devices to work properly: electric radiators, heat pump, circulation pump for hot water etc. In this monitoring campaign, all the consumption involved in the heating production were monitored, generally directly from the switchboard. According to the questionnaire that each household owner had to fill in, the households were split in two categories: the ones “with direct electric heating” (radiators or electric furnace) and the ones “without direct electric heating” (district heating, heat pump or other types of energy). The table from figure 2.448.1 shows the equipment rate for the different devices monitored during the campaign. This table concerns only the houses, the apartments weren’t split in two categories. It is interesting to note that floor heating is present in the two types of households (and more in the “without electric heating” category!). The water heater was monitored directly from the switchboard in the case of a three-phased appliance or with a wattmeter in the case of a mono-phased device with standard electric plug.

Heating Device With direct electric heating


Heating departure in switchboard 1,22 0,4

Floor heating 0,52 0,63 Heater 0,24 0,19

Air heat pump 0,15 0,12 Heat pump 0,11 0,14 Radiator 0,11 0,09

Water pump 0,06 0,03 Circulation pump 0,03 0,12

Air heater 0,02 0,04 Air Water heat pump 0,01 0

Furnace 0,01 0,01 Heat regulation 0,01 0,03

Exhaust air heat pump 0 0,02 Heat exchanger pump 0 0,02

Figure 2.448.1: Heating – Equipment rate for the different heating devices

Seasonality effect The consumption for the heating site is strongly seasonal, but most of the households

were only monitored for one month. The seasonality effect was calculated using the 40 households monitored for one year. For each household, we calculated the weekly consumption by adding all the data per week. The result output consists of 52 values per household corresponding to the number of weeks in one year. This set of values were then normalized to 1 (the average value gives one for each set). An average value per week was then calculated using all the data sets.

290


Electric heatingSeasonnality effect on the consumption

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STEM ENERTECH

Figure 2.448: Heating – Seasonality effect

Average consumption nsumption per m²

nd the annual consumption per person for heating and water heating for the different types of

ich has the lowest consumption with 2904 kWh/person/year and the “couples without children” which has the highest with 4403 kWh/person/year.

for the houses without direct electric heating, the total consumption goes from 2097 kWh/year (couples without children, 64 years old and above) to 6907 kWh/year (couples without children, 26-64 years old). The consumption per m² is in the range 10-50 kWh/m²/year in the same order as for the total annual consumption. Per person, it’s the family household which has the lowest consumption with 768 kWh/person/year and the “couples without children, 26-64 years old” which has the highest with 3453 kWh/person/year.

the total water heating consumption for the houses with direct electric heating are very close: from 2945 to 3046 kWh/year or 21 to 25 kWh/m²/year,

the total water heating consumption for the houses without direct electric heating goes from 1850 to 2675 kWh/year or 9 to 20 kWh/m²/year.

Figures 2.449 to 2.481 show the annual consumption, the annual coahouseholds:

for the houses with direct electric heating, the total consumption goes from 6804 kWh/year (couples without children, 26-64 years old) to 11217 kWh/year (family). The consumption per m² is in the range 50-81 kWh/m²/year in the same order as for the total annual consumption. Per person, it’s the family household wh

291


Heating

Figure 2.449: Heating – Annual consum -64 years old –Direct electric heating

–

ption – House, family, 26

Figure 2.450: Heating – Annual consumption – House, couples without children, 64 years old and aboveDirect electric heating

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Figure 2.451: Heating – Annual consum out children, 26-64 years old – Direct electric heating

ption – House, couples with

Figure 2.452: Heating – Annual consumption – House, family, 26-64 years old – Without direct electric heating

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293


Figure 2.453: Heating – Annual consumption – House, couples without children, 64 years old and above –Without direct electric heating

Figure 2.454: Heating – Annual consumption – House, couples without children, 26-64 years old –Without direct electric heating

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Water Heating

Figure 2.455: Water heating – Annual consu ouse, family, 26-64 years old –Direct electric heating

Fi

mption – H

gure 2.456: Water heating – Annual consumption – House, couples without children, 26-64 years old –Direct electric heating

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Fiabove ng

gure 2.457: Water heating – Annual consumption – House, couples without children, 64 years old and –Direct electric heati

Figure 2.458: Water heating – Annual consumption – House, family, 26-64 years old – Without direct electric heating

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ENERTECHWater HeatingAnnual consumption




Energimyndigheten

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Figure 2.459: Water heating – Annual consumption – House, couples without children, 26-64 years old –Without direct electric heating

297



Heating

Figure 2.460: Heating – Annual consumption per m² – House, family, 26-64 years old –Direct electric heating

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STEM ENERTECHHeatingAnnual consumption per m²


Mean value : 81 kWh/m²/year


298


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Annual consumption per m²House, couple without children, 64 years old and above



Fig d

FiDirect electric heating

ure 2.461: Heating – Annual consumption per m² – House, couples without children, 64 years old anabove –Direct electric heating

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gure 2.462: Heating – Annual consumption per m² – House, couples without children, 26-64 years old –

299


Figure 2.463: Heating – Annual consumption per m² – House, family, 26-64 years old – Without direct electric heating

Figure 2.464: Heating – Annual consumption per m² – House, couples without children, 64 years old and above –Without direct electric heating

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Annual consumption per m²House, family, 26-64 years old


ENERTECH


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Figure old –Without direct electric heating

Figure 2.466: Water heating – Annual consumption per m² – House, couples without children, 26-64 years old – Direct electric heating

2.465: Heating – Annual consumption per m² – House, couples without children, 26-64 years

Water heating

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Annual consumption per m²House, couple without children, 26-64 years old



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Energimyndigheten W ENERTECHater heatingAnnual consumption per m²




301


Fig 7: Water hea – A nu tio e H se, c pl ho c 6 yearsld

Figure 2.468: Water heating – Annual consumption per m² – House, family, 26-64 years old –Direct electric heating

ure 2.46 ting n al consump n p r m² – ou ou es wit ut hildren, 4 o and above –Direct electric heating

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ou

)Energimyndigheten ENERTECHter heating

nua nsumption per mHouse, pl ithout children, 64 yea ld and ab

Wal coAn

e w²

rs o cou ove

Me

g

an ue : kW ²/y

h d t e ic tin

val 21 h/m ear

Wit irec lectr hea

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Energimy ERTECHW ter nnual on t r m


ndigheten ENa heati gAn c sump ion pe ²


Mea e : 24n valu kWh/m²/year

302


Figure 2.469: al consum – House, cou ut children, 26-64 old –Withou t electric heating

Water heating – Annuyears

ption per m² ples withot direc

Figure 2.470: Water heating – Annual consumption per m² – House, family, 26-64 years old – Without direct electric heating

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House, couple without children, 26-64 years oldAnnu


c heatingWithout direct electri


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ENERTECHWate tingAnnual con ion per m²

House, fami 4 years old

r heasumptly, 26-6

Mean value : h/m²/year


Energimyndigheten

20 kW

303



Heating Figure 2.471: Heating – Annual consumption per person – House, family, 26-64 years old –Direct electric

heating

ure 2.472: Heating – Annual consumption per person – House, couples without children, 64 years old and above –Direct electric heating

Fig

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STEM ENERTECHHeatingAnnual consumption per person


Mean value : 2904 kWh/person/year


0Households

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Figure 2.473: Heating – Annual consumption per person – House, couples without children, 26-64 years old – Direct electric heating

Figure 2.474: Heating – Annual consumption per person – House, family, 26-64 years old – Without direct electric heating

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Annual consumption per personHouse, couple without children, 26-64 years old

STEM



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ENERTECH


305


Figure 2.475: Heating – Annual consumption per person – House, couples without children, 64 years old and above –Without direct electric heating

F

old –Without tric heating igure 2.476: Heating – Annual consumption per person – House, couples without children, 26-64 years

direct elec

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Annual consumption per personHouse, couple without children, 64 years old and above

STEM



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Water heating

Figure 2.477: Water heating – Annu se, couples without children, 26-64 years old – Direct electric heating

F 4 years ng

al consumption per person – Hou

igure 2.478: Water heating – Annual consumption per person – House, couples without children, 6old and above –Direct electric heati

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Energimyndigheten ENERTECHWater heatingAnnual consumption per person




307


308

Figure 2.480: Water heating – Annual consumption per person – House, couples without children, 26-64 years old –Without direct electric heating

Figure 2.479: Water heating – Annual consumption per person – House, family, 26-64 years old –Direct electric heating

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Annual consumption per personHouse, family, 26-64 years old



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Energ


imyndigheten ENERTECH


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Annual consumption per personHouse, family, 26-64 years old



Energimyndigheten

Figure 2.481: Water heating – Annual consumption per person – House, family, 26-64 years old – hout direct electric heatinout direct electric heatinWit g g

Part of the electric heating consumption Figure 2.482 and 2.483 show the distribution between heating and specific consumption for houses with and without direct electric heating. These graphs were calculated with the one year households and represent only 20 monitored houses. It is interesting to note that the heating consumption vary only from 42 % of the total consumption in winter to 25 % in summer for the houses with direct electric heating and from 30 % to 10 % for the houses without electric heating.

Part of the electric heating consumption Figure 2.482 and 2.483 show the distribution between heating and specific consumption for houses with and without direct electric heating. These graphs were calculated with the one year households and represent only 20 monitored houses. It is interesting to note that the heating consumption vary only from 42 % of the total consumption in winter to 25 % in summer for the houses with direct electric heating and from 30 % to 10 % for the houses without electric heating.

309


HeatingPart of the electric heating consumption in the total household consumption

Houses with direct electric heating

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Total consumptionElectric heating consumption

STEM ENERTECH

Figure 2.482: Heating – Part of the electric heating consumption in the total household consumption – direct electric headirect electric heaWith ting

Figure 2.483: Heating – Part of the electric heating consumption in the total household consumption –

th ting

Figure 2.483: Heating – Part of the electric heating consumption in the total household consumption –

HeatingPart of the electric heating consumption in the total household consumption

Houses without direct electric heating

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STEM ENERTECH

Without direct electric heating Without direct electric heating

310


Analysis per type of equipment

ed consumptions Annualiz The table from figure 2.484 lists all the different devices that were monitored during the measurement campaign. In most of the houses with electric heating, there were always one or more specific departures from the switchboard concerning heating but the exact devices powered by this departures were not know (radiators, etc.). It is interesting to note that the second most consuming specific device is the floor heating, considered as a “comfort” heating device and present in the houses with or without electric heating.

Heat pump, air heat pump or air water pump concern the houses without direct electric heating

Number of devices monitored

Annual consumption (kWh/year)

Heating monitored from switchboard 151 8988

Furnace 2 5202 Heat pump 25 4749 Air heat pump 27 2661 Water heater 79 2646 Floor heating 99 2160 Circulation pump 14 1601 Radiator 15 1264 Heater 28 1197 Air Water pump 1 1145 Air heater 1024 5 Exhaust air heat pump 2 355

Heat exchanger pump 2 354 Water pump 11 284 Heat regulation 4 96

Figure 2.484: annual consumption per type of device

311


OTHER APPLIANCES

Average consumption The table from figure 2.485 lists all the other appliances monitored during the campaign that didn’t fit in one of the families that we defined in the rest of this report. Six of these appliances have an annual consumption greater than 100 kWh/year, 12 are between 10 and 100 kWh/year and the rest (7 appliances) consume less than 10 kWh/year.

Number of monitored Annual consumption Appliance appliances (kWh/year)

Air dryer 4 585 Aquarium 23 230 Roof fan 2 203 Water bed 8 140 Alarm 5 140 Car heater 21 100 Fan 29 97 Solarium 1 88 Sauna 20 82 Air cleaner 5 67 Oxygen mask 3 61 Central vacuum cle 35 aner 26 Copier 6 38 Type writer 1 38 Clock radio 1 32 Kitchen ventilation 255 25 Shoes dryer 2 19 Radio 99 11 Hair dryer 1 7 Model train 1 7 Jacuzzi 13 6 High pressure washer 1 4 Calculator 3 3 Lawn mover 3 2 Sewing machine 1 1

Figure 2.485: annual consumption per type of device

ANALYSIS OF STANDBY POWERS IN THE HOUSEHOLDS It is not possible to deal with domestic electricity consumptions, without an in depth analysis of the Standby power issue. Several times in this report, this aspect was tackled for some appliance types, but the present chapter proposes an overall analysis. Before beginning with the analysis, it is important to define the meaning of the different terms used in this chapter:

OFF mode: the power drawn by an is mode. It might be unplugged, or witched-off on the primary side of the supply transformer.

appliance is null in th

s

312


ON mode: mode in which the appliance realises its principal function. All its components are supplied with their maximum powers. No power management at all is implemented.

Standby mode: mode in which the appliance is neither switched Off, nor in Full-On mode. This mode groups all the Standby and energy management modes that exists in a single appliance together. Depending on the appliance, it might includes the « idle », « energy saving », « doze », « Standby », « delay start » or « suspend » modes. Average Standby power (W): for a continuously monitored appliance, this is the average power it draws when working in Standby mode. For instance, for a VCR with two different Standby power levels (8 and 12 W) that would be used alternatively in these two modes during the same length, the considered average Standby power would be 10 W. Operating Rate (%): this is the ratio of the operating time (in Full-On mode) to the total reference time. Standby Rate (%): this is the ratio of the time spent in Standby mode, to the sum of the times spent in the Off or Standby modes.

General methodology The ge e household. In most of the households, audiovisua ain ources of Standby powers in the households) were continuously monitored with wattmeter

plugs. Using specific software developed for this campaign, it was possible to extract from the monitoring data all the Standby power and rate. On the other hand, all the other Standby power were directly measured with a portable wattmeter (NZR - SEM10). The first approach for calculating the Standby power per household consists of adding per household all the directly measured Standby to the ones extracted from the monitored data. This sum will represent the minimum of the Standby power because there are always hidden consumptions that are not measured The second approach consists in analysing the difference between the total household consumption and the sum of the consumption of all the appliances monitored. This « remnant » consumption is interesting because it removes any appliance that could interfere with our Standby analysis (notably cold appliances, whose regulation resistor is not considered as a Standby power source in this chapter). The aim was to study this remnant part and to investigate the periods during which the remnant power demand was minimum.

Figures 2.486 and 2.87 show us the number of appliances (or group of appliances) that

were measured for Standby power. The average numbers are 12 for the houses and 8 for the apartments.

implemented in situ measurements included the monitoring of the household neral consumptions, as well as the measurements of the different appliances present in th

l and computer sites, (which are the ms

313


StandbyAverage number of standby measured

All Houses

0

5

10

15

20

25

30

Households

Num

ber o

f app

lianc

esEnergimyndigheten ENERTECH

Mean value : 12 appliances

Figure 2.486: Standby – Average number Standby measured per house

Figure 2.487: Standby – Average number of Standby measured per apartment

StandbyAverage number of standby measured

All Apartments

0

5

10

15

20

25

30

35

Households

Num

ber o

f app

lianc

es


Mean value : 8 appliances

314


Figure 2.488 shows the distribution of the Standby power measured with the wattmeter. 60 % of the Standby power is in the range 0,5 – 5,0 Watt, the rest are going up to 30 Watt. Actually, only 1 % of the Standby measured were lower than 0,5 Watt.

StandbyDistribution of the standby power

0,0%

2,0%

4,0%

6,0%

8,0%

10,0%

12,0%

14,0%

0;0,5[ ,5;

2[3;3

,5[ ,5;5[

6;6,5[ ,5;

8[9;9

,5[ 11[

12,5[

5;14[

15,5[

5;17[

18,5[

5;20[

21,5[ 23

[24

,5[ 26[

27,5[

29,5[

Num

ber o

f occ

uren

ce

Figure 2.488: Distribution of the Standby power

Standby power demand Figures 2.489 and 2.490 show the Standby power calculated by adding all the individual Standby powers measured for each appliance in the household. For houses, the average Standby power is 59 Watt and 34 Watt for the apartments. This value can be compared to the 60 Watt that was found in the Eureco project for Denmark, but don’t forget that for Denmark 60 Watt was the average value for the maximum Standby power demand and this value was calculated for houses and apartments together. For the houses in Sweden, 59 Watt is the minimum value due to all of the hidden consumption that we couldn’t take into account. This remark is also valid for the apartments.

[ [1 [ [4 [ [7 [[10

,5;[12

;[13

,[15

;[16

,[18

;[19

,[21

;[22

,5;[24

;[25

,5;[27

;[28

,5;

Power (W)


315


Figure 2.489: Standby – Average Standby power per house

Figures 4.491 and 4.492 show the average standby power calculated using the main consumption. An average power between 03:00 and 04:00 was calculated for all the families

Figure 2.490: Standby – Average Standby power per apartment

StandbyAverage standby power

All Houses

0

50

100

150

200

250

Households

Pow

er (W

)ENERTECH

Mean value : 59 Watt

Energimyndigheten

StandbyAverage standby power

All Apartments

0

50

100

150

200

250

Households

Pow

er (W

)



316


of appliances and for the main using all the data from the monitoring period. All the families average power (for computer and audiovisual sites) was then subtracted from the main

wer. This method gives us a value near the maximum power for Standby for each hafor houses is in the range [59-116] Watt and for the apartments in the range [34-48] Watt.

Figure 2.491: Standby – Average Standby power measured from the main for the houses

average poousehold. For houses, the maximum average Standby power is 116 Watt and 48 Watt for the partments. Combined with the results found above, it seems that the average Standby power

StandbyStandby power measured between 03:00 and 04:00

All Houses

0

200

400

600

800

1000

1200

1400

1600

Households

Pow

er (W

)

ENERTECH


Energimyndigheten

317


Figure 2.492: Standby – Average Standby power measured from the main for the apartments

SINGLE FAMILY HOUSES VS RESIDENTIAL BUILDINGS In the previous chapters, the annual consumption for the different appliances were calculated on a “per type of household” basis. The results are very interesting for a detailed analysis when you know exactly the composition of your sample. On the other hand, more general results will be interesting to quickly calculate an approached value. The table of figure 2.493 shows us the annual consumption for all houses and all apartments together. Using the total number of houses and apartments in Sweden, it is possible to use this numbers to calculate a total consumption for a national or for a city point of view.

All results are in kWh/year except for standby values (Watt)

One Family Houses

Multiple Family Houses

Fridge 275 297 Fridge-freezers 569 505 Vertical freezers 489 476 Table top freezers 489 American freezers 454 Chest freezers 242

Cold appliances

Total 818 633 Clothes washers 209 163 Clothes dry 194 236 ers Dishwasher 193 152

Washing/Drying

Total 525 296 Cooking Oven 175 205

StandbyStandby power measured between 03:00 and 04:00

All apartments

0

100

200

300

400

500

600

700

800

Households

Pow

er (W

)ENERTECH


Energimyndigheten

318


Kitchen stove 281 218 Microwave 38 29 Water boiler 51 45

Total 402 320 Lighting Total 1021 574

TV 181 139 Audiovisual site All 455 311 Desktop 298 402 Laptop 36 34 Computer site Total 374 434 Heating (with electric heating) 11595 Heating (without electric heating) 5547 Heating (global) 8378

Heating

Water Heating 2269

Standby Total min/max (Watt) 59-116 34-48

Figure 2.493: Annual consumption for single family houses vs. Residential buildings

ASSESSMENT OF THE POTENTIAL ELECTRICITY SAVINGS

residential sector. These savings can be ly by replacing the existing appliances y energy efficient ones. From the characteristics of the existing equipment, and from the easurements done every 10 minutes, we had the data to simulate the operation of efficient

appliances that would be placed in the same conditions. We took into account the following steps:

replacement of all the cold appliances with class A+ or A++ equipment, replacement of all the incandescent and halogen light bulbs with compact

fluorescent light (CFL) bulbs or LEDs, reduction of all the Standby powers for the audiovisual and computer site, replacement of existing clothes-washers, clothes-dryers and dish washer

with energy efficient class A appliances, replacement of all the desktops by laptops.

DOMESTIC COLD PRODUCTION

Methods for assessing the savings The objective here is to determine the potential savings for cold appliances, using the annual consumption calculated with the 10 min values. The annual consumption of the energy efficiency class A+ or A++ appliances working in the same environment can be found on internet (topten database: http://www.topten.ch/index.php

One of the objectives of this report is to assess the potential electricity savings in the achieved main

bm

), and this for each type of cold appliance. appliance as replacement fo s were extracted from the

opten.ch database.

The table of figure 3.1 shows the annual consumption used for each type of cold r the actual consumption. These value

T

319


Annual consumption (kWh/year)

Fridge (200-250 liters) 92

Vertical freezer (200-250 liters) 190

Fridge freezer (200 litesr) 157

Table top freezer (height < 85 cm) 127

American freezer (350 liters) 250

Chest freezer (300 liters) 182

Figure 3.1: Cold appliances – annual consumption of the efficient ones

Refrigerator potential electricity saving Figure 3.2 shows the average annual saving per household for the fridges by replacing all that type of appliance by an efficient one. The average value per household is 132 kWh/year and can be compared to the 148 kWh found for Denmark in the Eureco project. The two projects are separated by 6 years but have more or less the same result: in six years, the numbers of household with efficient fridges increased but the best annual consumption decreased. It is therefore possible to find the same result.

Figure 3.2: Fridges – Average annual savings per household

Vertical freezers potential electricity saving Figure 3.3 shows the average annual saving per household for the vertical freezers by replacing all that type of appliance by an efficient one. The average value per household is 218 kWh/year and can be compared to the 220 kWh/year calculated for Denmark in the Eureco project. As for the fridges, the two projects are separated by 6 years but have more or less the same result: in six years, the numbers of household with efficient vertical freezers

FridgesAverage annual saving per household

0

200

400

600

800

1200

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

1400

Consumption after substitution

)

Savings due to change ofappliances1000



320


increased but the best annual consumption decreased. It is therefore possible to find the samresult.

e

Figure 3.4: Fridge freezers – Average annual savings per household

Vertical freezersAverage annual saving per household

0

400

600

800

1000

1200

1400

1600

1800

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar)


Savings due to change ofappliances

Figure 3.3: Vertical freezers – Average annual savings per household

Fridge freezers potential electricity saving

Fridge-freezersAverage annual saving per household

0

400

600

800

1000

1200

1400

1600

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

200

)





200



321


Table-top freezers potential electricity saving It is for the tabletop freezers that we find the highest savings for a cold appliance per household with 362 kWh/year.

TableTop freezersAverage annual saving per household

0

200

400

600

800

1000

1200

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Consumption after substitution)




Figure 3.5: Tabletop freezers – Average annual savings per household

American freezers potential electricity saving

American freezersAverage annual saving per household

0

100

200

300

400

500

600

700

800

900

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar

Consumption after substitution)




Figure 3.6: American freezers – Average annual savings per household

322


Chest freezers potential electricity saving There were only 4 chest freezers monitored in the whole campaign. The estimation of 60 kWh/year has to be confirmed with a larger panel.

Chest freezersAverage annual saving per household

0

100

200

300

400

500

600

700

800

Ann

ual c

onsu

mpt

ion

(kW

h/ye

ar Consumption after substitution)




Figure 3.7: Chest freezers – Average annual savings per household

ent. The difference between the actual consumption ble per household. In the Eureco project for

Denmark, the value found was 385 kWh/year/household: the value for this campaign is very close with 390 kWh/year/household !

Cold appliances potential electricity saving Figure 3.8 shows the total savings for the cold appliances site. This value was calculated by replacing individually each appliance with an efficient one and then calculating

e annual consumption after replacemthand the new one gives the annual savings possi

323


Cold appliancesAverage annual savings per household

0

400

800

1200

1600

2000

Household

Ann

ual s

avin

gs (k

Wh/

year

Figure 3.8: All cold appliances – Average annual savings per household

LIGHTING

Methods for assessing the savings The only method for saving lighting energy in the household that was considered in this study, was the replacement of all the incandescent or halogen lights of the households by compact fluorescent light bulbs (CFLs) or LED. Practically, the assessment of the energy saving was calculated by modifying the bulb wattages in the lighting database. The bulb wattages were divided by 4 which seems a good ratio between incandescent and CFL and LED technologies. As it contains every 10 minutes records, this database also provides the operating periods of each light source. It was therefore easy to deduce by comparison the potential electricity savings.

Lightning potential electricity saving Figure 3.9 and 3.10 show the annual average saving per household for houses and apartments. The value is higher in the houses with 517 kWh/years than in apartments (305 kWh/year) but we saw in the lighting chapter that the installed wattage is higher for houses than apartments. This values can be compared to the 265 kWh/year that was found in the Eureco project for Denmark. This time, the savings are higher in Sweden.

)



Cold site consumption after replacement with efficient appliances : 282 kWh/year/household

324


Lightingal average savings per household

All Houses

0

500

1000

15

20

Figure 3.9: Lighting – Ave annual savings per

Figure 3.10: Lighting – Average annual savings per apartments

rage houses

Annu

00

Ann

ual s

avin

gs (k

Wh/

year

00

2500

)Energimyndigheten


Enertech

L tingAnnual average ings per household

All A rtments

0

500

1000

1500

2000

2500

Ann

ual s

avin

gs (k

Wh/

year

ighsavpa

)



325


WASHING/DRYING

Methods for assessing the savings ach efficient clothes-washer, clothes dryer and dish washer was

timat

the end of the ycle analysis we calculated a new annual consumption: the difference between the actual and

the new one gives us the annual savin ure 3.11 shows the different co per cycle used to calculate the sav

The consumption of ees ed as a function of the annual number of cycles of the existing appliance. For each type of appliance, we extracted individually the different working cycles and compared the consumption with the cycle consumption of an efficient appliance. If the actual consumption was higher than the efficient one, we replaced it with this consumption. At c

gs for the appliance. The table from figings. nsumption

Consumption p cle er cy(kWh)

Clothes washer 0,93 Clothes dryer 1,35 Dish washer 0,98

Figure 3.11: Washing: consumpti er cycle for efficien liances

Clothes-was l electricity s During the calculation of the savings, we saw that consumption of the washing cycles in many cases lue for efficient one. Therefore the average saving represents only r/household.

Figure 3.12: Washing machine: Annual average savings per household

on p t app

her potentia aving

were lower than the va t he 10 kWh/yea

Clothe erAnnual average sav s per household

400

500

600

700

800

900

Ann

ual s

avin

gs (k

Wh/

year

s washing

0

100

200

300

)



326


Clothes dryers potential electricity saving During the calculation of the savings, we saw that the consumption of the drying

s, we saw that the consumption of the washing

cycles in many cases were lower than the value for the efficient one. Therefore the average savings represent only 45 kWh/year/household.

Figure 3.13: Clothes dryer: Annual average savings per household

Dishwasher potential electricity saving During the calculation of the savingcycles in many cases were lower than the value for the efficient one. Therefore the average saving represents only 11 kWh/year/household.

Clothes dryer

300

v

Annual average savings per household

600

0

100

200

Ann

u

400

(kW

h/

500

ral

sa

ings

yea

)



327


Dish washerAnnual average savings per household

0

50

100

150

200

250

300

350

Ann

ual s

avin

gs (k

Wh/

year

)



Figure 3.14: Dish washer: Annual average savings per household

AUDIOVISUAL SITE

Methods for assessing the savings The audiovisual site was analyzed as a whole. The main work was to recalculate the Standby consumption using appliances with less than 0,5 Watt Standby power. The ON mode power was not modified because recent studies, such as the Remodece+ study in France, indicates that customers, when they change their TV for example, will buy a bigger one and that, despite of the fact that recent appliances will have their ON mode power minimized, the ON mode power will remain the same. The distribution between Standby and ON mode were used to recalculate the annual consumption by replacing the Standby power by 0,5 Watt. At the same time, the night consumption(between 00:00 and 06:00) were deleted because this consumptions is due to Standby and there are possibilities to switch the entire site OFF when not used.

328


Potential electricity saving Figure 3.15 shows the annual savings per household for the audiovisual site. It is possible to save 84 kWh/year/household only by reducing the Standby power and by

Figure 3.15: Audiovisual site: Annual average savings per household

the computer sites with desktop computer were replaced with laptops: ON mode Watt and an average of 8 Watt ON mode for the

canner etc.) Using the distribution between Standby mode and ON mode, it was possible to re-

calculate an annual consumption. The difference between this new consumption and the actual one will give the annual savings per household.

switching the site OFF when not used.

Audiovisual sitesAnnual average savings per household

0

100

200

300

400

500

600

Ann

ual s

avin

gs (k

Wh/

year

)



C UTER SITE

Methods for assessing the savings The savings for the computer site were calculated by analyzing each device separately:

- the laptops were replaced with the same type of device using 20 Watt ON mode power, Standby power: 0,5 Watt

- the desktops computers were replaced with laptops: ON mode power 20 Watt, Standby power: 0,5 Watt

-

OMP

power 20 W, Standby power: 0,5 rest of the devices (modem/printer/s

329


Potential electricity saving Figure 3.16 and 3.17 show the annual savings for houses and apartments. This value is higher for houses.

Figure 3.16: Computer site: Annual average savings per houses

Computer siteAverage annual savings per household

All Houses

500

1000

1500

2000

2500

3000

3500

4000

4500

Ann

ual s

avin

gs (k

Wh/

year

0Household

)



330


Computer siteAverage annual savings per household

All Houses

2000

2500

Figure 3.17: Audiovisual site: Annual average savings per apartments

POTENTIAL ENERGY SAVING PER TYPE OF HOUSEHOLD Figures 3.18 to 3.31 show the annual savings for the different types of household and the distribution of this savings between the different families of appliances.

- for the two types of households (Houses and apartments), the maximum saving is achieved for families: 1815 kWh/year for houses and 1366 kWh/year for

achieved for persons older than 65 year old: 1344 kWh/year for houses and 632 kWh/year for apartments,

- for the same type of persons, the savings are always higher in the houses as in the apartments,

- the sum of the savings for cold appliances, lighting and computer sites represent always more than 75 % of the total savings.

apartments, - for the two types of household (houses and apartments), the minimum saving is

0

500

1000

1500

Household

Ann

ual s

avin

gs (k

Wh/

year

)


yndEnergim igheten Enertech

331



Annual savings

Total annual savings per householdApartment, family, 26-64 years old

0

5

1000

1500

2000

2500

3000

3500

4000

Ann

ual s

avin

gs (k

Wh/

year

Cold appliances Washing machine

Clothes dryer Dish washer)

Lighting Audiovisual site

Computer site

Figure 3.18: Total annual savings per household – Apartment, family, 26-64 years old

Distribution of the savings between the different families of appliances

Figure 3.19: Distribution of the savings – Apartment, y, 26-64 year annual famil s old

00



Distribution of the annual savingsApartment, family, 26-64 years old

41 kWh/year

24 kWh/y

15 kWh/y

26 kWh/year

438 kWh/year

509 kWh/year

ear

ear

313 kWh/year

Cold appliances

Washing machine

Clothes dryer

Dish washer

Lighting

Audiovisual site

Computer site


332



Annual savings

Total annual savings per householdApartment, single person, 26-64 years old

400

60

80

1000

1200

1600

Ann

ual s

avin

gs (k

Wh/

year


0

1400

Clothes dryer Dish washer

Figure 3.20: Total annual savings per household – Apartment, single person, 26-64 years old

istribution of the savings between the different families of appliances D

Figure 3.21: Distribution of the annual savings – Apartment, single person, 26-64 years old

0

200

0

)


Computer site

M : 685 kWh

Energimyndig Enertech

ean-Value /year

heten

Distribution of the annual savingsApartment, single person, 26-64 years old

40 kWh/ye

304 kWh/year

106

ar

227 kWh/year 1 kWh/year


kWh/year

Cold appliances

Washing machine

Clothes dryer

Dish washer

Lighting

Audiovisual site

Computer site


333


Apartment, couples without children, 26-

Annual saving

64 years old

s

Figure 3.22: Total annual savings per household – Apartment, couples without children, 26-64 years old


Figure 3.23: Distribution of the annual savings – Apartment, couples without children, 26-64 years old

Total annual savings per householldren, 26-64 y ld

0

500

3000

3500

dApartment, couple without chi ears o

1000

1500

2000

Ann

ual s

avin

gs (k

Wh/

year 2500

)

Cold a espplianc Washing machine



Computer site



Distribution of the annual savingsApartment, couple without children, 26-64 years old

226 kWh/year

382 kWh/year

42 kWh/year

10 kWh/year

12 kWh/year

20 kWh/year

311 kWh/year

Cold appliances

Washing machine

Clothes dryer

Dish washer

Lighting

Audiovisual site

Computer site


334


Apartment, couples without children, 64 years old and above

Annual savings

Figure 3.24: Tota 64 years old and

ent families of appliances

Total annual savings per householdApartment, couple without children, 64 years old and above

0

200

400

600

800

1000

1200

1400

1600

Ann

ual s

avin

gs (k

Wh/

year



)


Computer site



l annual savings per household – Apartment, couples without children,above

Distribution of the savings between the differ

Distribution of the annual savingsApartment, couple without children, 64 years old and above

Figure 3.25: Distribution of the annual savings – Apartment, couples without children, 64 years old and above

118 kWh/year

28 kWh/year

367 kWh/year

3 kWh/year

2 kWh/year

346 kWh/year

Cold appliances

Washing machine

Dish washer

Lighting

Audiovisual site

Computer site


335



Figure 3.25: D d and above

Annual savings

Total annual savings per householdApartment, single person, 64 years old and above

0

100

200

300

400

500

600

700

800

900

1000

Ann

ual s

avin

gs (k

Wh/

year



Computer site)



Figure 3.24: Total annual savings per household – Apartment, single person, 64 years old and above


Distribution of the annual savingsApartment, single person, 64 years old and above14 kWh/year

40 kWh/year

236 kWh/year

4 kWh/year

338 kWh/year

Cold appliances

Washing machine

Lighting

Audiovisual site

Computer site


istribution of the annual savings – Apartment, single person, 64 years ol

336



Annual savings

Total annual savings per householdHouse, family, 26-64 years old

0

1000

2000

3000

4000

5000

6000

Ann

ual s

avin

gs (k

Wh/

year



)


Computer site



Figure 3.26: Total annual savings per household – House, family, 26-64 years old

Distribution o liances

Figure 3.27: Distribution of the annual savings – House, family, 26-64 years old

f the savings between the different families of app

Distribution of the annual saHouse, family, 26-64 years o

vingsld

168 kWh/year

654 kWh/year

49 kWh/year

48 kWh/year

26 kWh/year

518 kWh/year

351 kWh/year

Cold appliances

Washing machine

Clothes dryer

Dish washer

Lighting

Audiovisual site

Computer site


337


House, couples without children, 26-64 years old

Annual savings

Total annual savings per householdHouse, couple without children, 26-64 years old

0

500

1000

1500

2000

2500

3000

Ann

ual s

avin

gs (k

Wh/

year



)


Computer site



Figure 3.28: Total annual savings per household – House, couples without children, 26-64 years old

Figure 3.29: Distribution of the annual savings – House, couples without children, 26-64 years old


Distribution of the annual savingsHouse, couple without children, 26-64 years old

166 kWh/year

545 kWh/year


24 kWh/year

150 kWh/year

17 kWh/year

Cold appliances

Washing machine

Clothes dryer

Dish washer

Lighting

Audiovisual site

Computer site


338


House, couples without children, 64 years old and above

Annual savings

Figure 3.30: Total annual savings per household – House, couples without children, 64 years old and

Figure 3.31: Distribution of the annual savings – House, couples without children, 64 years old and above

above


Total annual savings per householdHouse, couple without children, 64 years old and above

0

500

1000

1500

2000

2500

3000

Ann

ual s

avin

gs (k

Wh/

year

)




Computer site



Distribution of the annual savingsHouse, couple without children, 64 years old and above

162 kWh/year

421 kWh/year

17 kWh/year

26 kWh/year

567 kWh/year

135 kWh/year

17 kWh/year

Cold appliances

Washing machine

Clothes dryer

Dish washer

Lighting

Audiovisual site

Computer site


339

Conclusion

CONCLUSION asurement campaign ever made in Europe (and

nd computer sites: Replacing the inefficient cold appliances by the best ones can save up to

560 kWh/year per household Replacing the incandescent and halogen light bulbs by compact fluorescent

educe the annual consum by 650 kWh for certain

laptop instead of a desktop and reducing the Standby site,

Using only audiovisual appliances with Standby powers less than 0.5 Watt can reduce this site consumption by 160 kWh/year.

r management procedures for computer appliances using power managers like Energy star,

This project represents the biggest mecertainly in the world). The high number of households monitored and analysed lets us have a precise overview of the electrical consumption and more important, lets us calculate the potential savings:

Today in Sweden, the total potential electricity saving per household ranges from 600 to 1800 kWh/year depending on the type of household.

The priority actions that should be carried out for Demand Side Management (DSM) concern cold appliances, lighting, audiovisual a

lamps would r ptionhouseholds Choosing aconsumption can save up to 550 kWh/year for the computer

Therefore it is important:

to implement the regulation that bans the putting on the market of appliances with Standby power above 1 W, or even 0·5 W,

to implement Standby powe

to implement a national program to address existing Standby powers. The objective is to remove them, by simply cutting the electrical supply of the appliances by using manual switches or Standby power managers, which are generally very cheap devices,

to intensify and accelerate the fixation of stricter consumption norms, and class A appliances should in a very short term become the standard.

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Conclusion

Reference The ecodrome project, Experimental Study of highly efficient Electrical Appliances in Household Use, Enertech, 1998 (Save n° 1031/S/94-093) The eureco project, End-use metering campaign in 400 households of the European Community, Assessment of the Potential Electricity Savings, Save project (N° 4.1031/Z/98-267) The remodece project, Residential Monitoring to Decrease Energy Use and Carbon Emissions in Europe, 2009, ISR-University of Coimbra, Dep. of Electrical Engineering, an EU, EACI project.

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Documents

RESULTS OF THE MEASUREMENT CAMPAIGN · The Swedish Energy Agency has financed the project, “End-use metering campaign in 400 ... Their consumption appear like wasted energy, and