End-use metering in 400 Swedish households

Peter Bennich

Purpose

• Improved prognoses of energy use and policy instruments for increased energy efficiency requires better resolution of the energy statistics

• Example of questions at issue:– Why does not the domestic electricity use decrease despite the fact that

e.g. white goods become increasingly more energy efficient?– How large is the contribution from standby-consumption?– What constitutes peak loads, when do they occur (the grid perspective)?

• More precise: three basic questions:– How does the distribution of apparatus really look like in

different types of households?– How energy efficient are these apparatus?– How does the user patterns look like?

Malmö

Kiruna

Stockholm +Region Lake Mälardalen

• Domestic end use in 200 detached houses and 200 apartments, plus common area of 20 residential buildings (elevators, washing room, etc

• One year: 40 (evenly distributed)

• One month: 360 (evenly distributed)

• Geografic spread limited to lake Mälardalen, plus some referense objects in Kiruna and Malmö

Measurements

Selection of households

• Selection by Statistics Sweden: 600 letters plus questionnaires per round.

• Selection from the Swedish ”building register”

• Answers from roughly 1 out of 4 (150 per round)

• Installers contact these households directly

• Not all households will be measured in the end, ca 100

• Can still use all questionnaires for mapping of certain characteristica. Total nr: more than 2000

• Additional option: water measurements as well

Questionnaire information• Locus type: city, small city; country side

• House or apartment

• Number of rooms

• Area

• Type of heating system

• Family structure:

– Number of people

– Age (note: Birth year!)

– Gender

• Income

• Number and model of cold appliances and TV’s

Additional information at installation:

• Distribution of appliances per room

• Distribution of lamps and lamp types per room

• Nominal standby power of appliances (measurement)

Additional studies:

• Water measurement in 8 households at tap level (1 – 10 min data, one month)

• Water measurements in (max) 50 households: incoming cold water and hot water. (10 min data, one month)

• Behaviour study of lighting: interviews of 8 households

• Behaviour study of the other uses: ”Cooking”, ”Entertainment”, ”Cleaning”, etc. Interviews and/or diarys; 14 households

• Harmonic containts of incadescent light, CFL’s and LED’s: per lamp and per household (lab study)

• Measurements and interviews of 2 households before and after replacement of lights and white goods to the best available (not started)

• Heat contribution from appliances and lighting (lab study) (not started)

Actual measurements

Many loads (especially light sources)... Easily over 60 in a house (35 – 45 light sources)

Measurements (2)

Så mycket som möjligt mäts i elcentralen – den totala elförbrukningen; spis, tvättmaskin, etc.

Öriga apparater (TV, PC, etc) mäts genom seriekopplade mätare placerade mellan apparaten och vägguttaget.

Measurements (3)

Ljuskällor mäts indirekt: ljus-sensorer mäter när lamporna är av eller på. Information om motsvarande ljuskällors effekt gör

det då möjligt att beräkna energin:energi = effekt*tid

Measurements (4)

Ifall det förekommer en blandning av fasta installationer och lösa apparater matade från samma säkring: Mät i punkterna

1, 2 och 3, då erhålls lastpunkten 4 (handdukshängaren) som differensen mellan 1 (säkringen) och lasterna (2+3).

Measurements (5)

Measurements (6)

• Measure as much as possible at the switch board (especially 3 phase installations), including total incoming electricity

• All other appliances are measured with a serial power meter connected at the outlets

• Lamps are measured with light sensors. Nominal power is written down.

• We also measure ventilation, water heating, circulation pumps and heating (direct, water, heat pumps) whenever possible

• Temperature inside and outside is also measured

• Time resolved data, 10 min rms-average on an appliance level. I.e., load curves for invidual appliances

• Goal: try to minimise the ”Not followed” part to be < 10 %. Easy for apartments, not so easy for houses…

Preliminary resultsHouses, all households[kWh/yr]

Apartments, all households[kWh/yr]

Fridge and freezers 1020 720

Lighting 1275 630

Cooking 510 390

Dish washers 306 120

Wash and dry 306 210

Stereo 102 60

TV 255 150

DVD, VCR etc 153 60

PC and related eq. 459 270

Others 357 60

Not measured 357 330

Sum 5100 3000

Relative distributions

Houses

Apartments

Cold appl

Lighting

Cooking

Dish

Wash, dry

Stereo, radio

TV

DVD +VCR etc

PC site

Others

3%

20%

25%

10%6%

6%

2%

5%

9%

7%7%

Not meas.

24%

21%

13%4%

7%

2%

5%

2%

9%

2%

11%

Some observations:Large spread of the results:

Houses: from 2000 to 7000 kWh/yrAverage ca 5100 +- 750 (15%) not definitive value!

Apartments: from 1000 to 5000 kWh/yr Average ca 3000 +- 450 (15%) not definitive value!

The composition and the other socio-ekonomical factors are important

• Lighting is the largest load

• Cold appliances comes second

• Entertainment electronics (TV, PC etc) comes on third place

Some observations (2):Increase in houses according to SCB (Statistics Sweden):

1970: ca 4 000 kWh/yr 2005: ca 6 000 kWh/yr

The absolute level of the values from 2005 may be doubted… but a redistribution has definitely occured:

Study from 1994: The domestic electric consumption in houses ca 5 000 kWh/yr

• Cold appliances then largest, at least 30 %

• Lighting approx as today, ca 20 %

• Entertainment electronics much less, way below 20 %

Is resolving of households into

subcategories important? (The

household perspective.)

Type of households/Age - 25 26-64 65-

Singles

Pair without children (age as close as possible to these intervals)

Families with children = Singles or pairs with children (irrespective of age)

Table 2: One example of subcategories for households in houses and apartments.

Resolving households into

subcategories is important!

House,all households[kWh/yr]

House, familieswith children[kWh/yr]

House, pairs withoutchildren, 25-64 yr

[kWh/yr]

Cold appliances 679 565 946

Computer site 360 490 180

Audiovisual site 398 436 438

Cooking 328 334 328

Washing 588 838 354

Lighting 1143 1333 1046

Rest 156 9 357

Stand-by 181 180 175

Not followed 1201 1063 1173

Total 5034 5248 4997

Load curves: more detailed information on user patterns Apartments, all households, one year

Monthly consumption per type of applianceApartment

0

50

100

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300

Janua

ry

Febr

uary

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chApr

ilM

ayJu

neJu

ly

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Octob

er

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Month

Co

nsu

mp

tio

n (

kWh

)

Not followed

Washing/Drying

Visual site excl. TV

TV

Audio site

Others

Dishwasher

Cooking

Computer site

Lightning

Cold appliances

ENERTECHSTEM

Loadcurves (2)Houses, all households, week day

Structure of the average hourly load curve

Weekdays

0

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800

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Hours

Co

ns

um

pti

on

(W

h)

Others

Computer site

Visual site excl. TV

TV

Audio site

Washing/drying

Dishwasher

Cooking

Lighting

Cold appliances

ENERTECHSTEM

All Houses

Example:Lighting in houses

Week day

Holiday

LightAverage hourly load curve

Weekdays

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300

350

400

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Hour

ENERTECHSTEM

All houses

LightAverage hourly load curve

Holidays

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350

400

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Hour

ENERTECHSTEM

Lighting (2): distribution of light sources

Inc

Halogen(trafo)

Halogen(230 V)

Fluor. Light strips

CFL

LightDistribution of the light sources per type of bulbs for the houses

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

All houses Houses,family w kids

Houses,couple w/o kids

ENERTECHSTEM

Lighting (3): large number of light sources…

Number of lamps in houses

0

10

20

30

40

50

60

1-20 21-40 41-60 61-80 81-100

Number of lamps in apartments

0

10

20

30

40

50

60

1-20 21-40 41-60 61-8081-100

Number of lamps in all households

0

10

20

30

40

50

60

1-20 21-40 41-60 61-80 81-100

Installed power: average 1 – 2 kW

Light

Average hourly load curve

Weekdays

0

50

100

150

200

250

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350

400

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Hour

ENERTECHSTEM

All houses

ENERTECHSTEM

Behaviour study of lighting: explains the data more…

Old couple, a day in October 2005. Use per room:

Breakfast w light candles

She: prepares foodHe: works in the

cellar

Siesta?

Outdoor lighting turns on by timer

But what do they do?

Another example: Stand-by vs operational (1)

TV: Rel low standby, high operationalTV

Daily average load curve

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Hour

W

Standby On-mode consumption

ENERTECHSTEM

All Houses

Stand-by vs operational (2)

VCR, DVD etc: Rel high standby, low op

Visual site excl. TVDaily average load curve

0

5

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20

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Hour

W

Standby On-mode consumption

ENERTECHSTEM

All Houses

Stand-by vs operational (3)

PC + related eq: Rel high standby and high opComputer site

Daily average load curve

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Hour

W

Standby On-mode consumption

ENERTECHSTEM

All Houses

Stand-by (4). Another view: relative energy use

Energy contribution of the different consumption states per function

0%

20%

40%

60%

80%

100%

Audio site Computer site Cooking Dishwasher TV Visual site excl.TV Washing/Drying

Co

ntr

ibu

tio

n (

%)

Standby consumption On-mode consumption

ENERTECHSTEM

All Houses

Stand-by (5). Yet another view – relative time in use

Time contribution of the different consumption states per function

0%

10%

20%

30%

40%

50%

60%

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80%

90%

100%

Audio site Computer site Cooking Dishwasher TV Visual site excl.TV Washing/Drying

Co

ntr

ibu

tio

n (

%)

Relative Off time Relative Standby time Relative On time

ENERTECHSTEM

All Houses

6.0 h7.5 h

Number of freezers in houses

Number of freezers in houses

1 Freezer60%

2 or more Freezers40%

Total sample: 53 houses

Trend: increasing number of apparatus and electricity use

TV:s in the homes

1 TV 47%

2 TV 38%

4 or 5 TV 2%

3 TV 13%

PC:s in the homes

No PC

9%

1 PC

61%

2 PC

22%

3 or more PC:s

8%

Information and entertainment

Why..?From ”gathering around the fire” - communal use - to

parallell, individual, use

In some cases… gathering around the ”cyber-fire”! Individual double use

System of different user patterns• Communal use: two or more family members use an appliance together

(e.g. watching TV together)

• Use for common goals: one member uses appliances that serves many members (e.g. cooking the family dinner)

• Serial use: the same appliance is used at different times by different members (e.g. the tea-kettel)

• Parallell use: the same type of appliances are used at the same time by different members in different places in the dwelling (e.g. TV or PC)

Trend towards more individual use – add patterns like:

• Individual simultaneous use (e.g. cooking and listening to the radio)

• Individual by-turn use (e.g. alternating between TV and PC without switching off the appliance not in use for the moment)

• Individual double use (e.g. two or more appliances must be turned on at the same time to achieve the desired function).

Conclusions from the behaviour study:

The interplay between household members is crucial:

• Competition and/or negotiation of common resources

• Is more and more solved by adding more resources

• Tendency from communal use to individual use• Ex: All must have their own set of PC, broadband, TV, stereo etc.

The electricity use increase even more...

Finally, methodology issues:

• Optimum between data collection and statistical methods seem to be an open question…

• STEM-data will be processed by researchers in order to try to scale up to national level. May be difficult… 400 is not enough for all the detailed descriptions we want to achieve (different household types– not one typical household!)

• REMODECE

• Nordic informal group

• IEA-IA on Energy efficient end-use equipment: Annex on benchmarking

• IEA workshop on Energy indicators