Smart Domestic Appliances Provide Flexibility for Sustainable Energy Systems

The sole responsibility for the content of this presentation lies with the authors. It does not necessarily reflect the opinion of the European Communities. The European

Commission is not responsible for any use that may be made of the information contained therein.

Smart Domestic

Appliances Provide

Flexibility for

Sustainable Energy

Systems

Christof Timpe

Öko-Institut

Leonardo Webinar

21 August 2009

Smart Domestic Appliances in Sustainable Energy Systems

2

Partners in the Project

“Smart Domestic Appliances

in Sustainable Energy Systems (Smart-A)”


3

Overview

• The Smart Appliances Vision

• Demand Response Options by Smart Appliances

• Consumer Acceptance of Smart Appliances

• Model Results

– Benefits provided by Demand Response Devices

– Cost of Smart Appliances

– Comparison of Cost and Benefits

• A Snapshot on the Actors Involved

and Incentives Required

• Conclusions


4

The Smart Appliances Vision

© Öko-Institut e.V.


5

Examples Illustrating the Smart-A Vision

• The freezer receives a signal from the local

electricity network operator that a load peak is

expected around noon, and therefore it stores

cold in the morning to avoid operation during

peak time.

• The user switches on the dishwasher in the

morning and leaves for work. The appliance

optimises the timing of its operation based on

heat supply from the solar heat system.

• The washing machine checks the weather

forecast from the Internet and signals to the

user that a sunny day allows for the use of a

programme with higher temperatures.

Low-level

consumer interaction

Complex

consumer interaction

Automatic

smart operation


6

Appliance Load of a Generic European Household

0

100

200

300

400

500

600

700

800

900

0 2 4 6 8 10 12 14 16 18 20 22

Time of day (hours)

Po

we

r d

em

an

d (

W)

Water Heater

Air Conditioner

Oven and Stove

Tumble Dryer

Washing Machine

Circul. Pump

Dishwasher

Refrigerator

Freezer


7

Demand Response Options for Appliances

Smart Timing of Appliances Cycles

Washing Machine, Dryer: Typical <3 hrs.; Maximum 9 hrs.

Dishwasher: Typical <6 hrs.; Maximum >12 hrs.

Refrigerator, Freezer: n/a

Other Appliances: Typical <15 mins. … 1 hr.

Interruptions of the Appliance Cycle

Washing Machine: Typical <10 mins.

Dryer: Typical <30 mins.

Dishwasher: Typical <10 mins.

Refrigerator, Freezer: Typical <15 mins.

Other Appliances: Typical <15 mins.


8

Consumer Objections and Wishes

• Higher investment cost

• Consumers want to be able to

retain full control over their

appliances

• Health and safety issues

(fire, flooding, food might

be compromised)

• Doubts about maturity

of the technology

• Scepticism about the

ecological benefits

• Economic Incentives

• Enhanced safety functions

Overloading signal

Temperature surveillance

Water stop

Detection of technical faults

• Enhanced comfort and usability

• High quality service & support

• Attractive design

Pictures © PIXELIO


9

Applications of Demand Response –

Requirements of Sustainable Energy Systems

So

urc

e: A

ba

ravic

ius &

Pyrk

o,

20

06

The key challenge

of the future:

Balancing out

variable wind

(& solar)

generation.


10

Determining the Economic Benefits of Smart

Appliances in Sustainable Energy Systems

Step 1:

Value of Demand Response Devices

for Balancing Wind Generation


11

Sample View on a Model Run

8000

9000

10000

11000

12000

13000

14000

15000

16000

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

MW

hour

Pd_original Pd_dsm


12

Model A: Value of Generic 1kW DSM Device

Effects of introducing DR into

system balancing in energy

systems with high shares of wind:

– Reduced requirement for

“spinning reserve” from part-

loaded fossil fuel plants

– Reduced necessity to shut

down wind plants in order to

ensure system stability

Both effects result in:

– Reduced use of fossil fuel

– Reduced CO2 emissions

The figure shows the annual

value per kW of DR load.

0

10

20

30

40

50

60

70

80

90

100

Low Flexibility

Generation

(DE, FR, PL ..)

Medium Flexibility

Generation

(ES, IT, PT ..)

High Flexibility

Generation

(Nordic, AT, CH, ..)

EU

R/k

W/y

ear

All cases assume a

30% wind share in

installed generation

& moderate CO2 cost


13

Model A: Application to EU29 Countries

0

10

20

30

40

50

60

70

80

90

100

AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IT LT LU LV MT NL NO PL PT RO SE SI SK

EU

R/k

W D

SM

2010, moderate energy prices,

CO2 cost included


CO2 cost included

2025, high energy prices,

CO2 cost included

104 130 100


14

Model B: Value of Selected Appliances

The value of individual appliances

is driven by:

– The degree of flexibility

offered (duration of the

load shift)

– The volume of energy shifted

per appliance

The figure shows the annual

value of three selected appliances

used for DR.

0

2

4

6

8

10

12

14

16

18

Washing Machine Dishwasher Washer+Drier

EU

R/a

pp

lian

ce/y

ear

Low flexibility generation

system with 30% wind

share at moderate

energy and CO2 prices.


15



Step 2:

Cost of Enabling Smart Appliances

as Demand Response Devices


16

Cost for Providing DR by Appliances

The following cost items are relevant

• Additional production cost for the Smart Appliance

– Significant reductions expected through mass production

• Investments in an in-house communication hub

– In the future, this function can be taken over by any WLAN system.

• Cost for additional electricity consumption of Smart Appliances

– Expected average value: 1 W extra for SA “ready to operate”.

Smart Meters are not really required for Smart Appliances operation,

Also, Smart Meters can provide other services to consumers as well.

No extra cost have been taken into account here.


17



Step 3:

Comparison of Cost and Benefits

of Smart Appliances


18

Comparison of Cost and Benefits

0

10

20

30

40

50

60

70

80

90

100

AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IT LT LU LV MT NL NO PL PT RO SE SI SK

EU

R/k

W D

SM


CO2 cost included


CO2 cost included

2025, high energy prices,

CO2 cost included

104 130 100

Expected

range of

costs

(2025)


19

A Few Words of Caution

• Models A and B only looked at benefits of Smart Appliances used

for balancing wind power.

– Additional benefits can be gained by other applications,

e.g. managing local or regional network congestions.

• The analysis is based on a number of rough assumptions.

– Du to these uncertainties, the results should be regarded as

rough estimates rather than precise results.

• The analysis is performed on a country-by country basis.

– To the extent that balancing markets in the EU become better

connected, differences will be reduced.


20

A Snapshot on the Actors Involved

„Smart“

Household

System

Balancing

Smart Appl.

Aggregator

Other Balancing

Power Providers

Wind

Generators

Other kWh

Generators

Power

Market

DSOs

Retailer of

„Smart“

Household

Other

Retailers

Other

Energy

Consumers

Appliances

Manufacturers

Appliances

Retailers


21

A Snapshot on the Actors Involved

„Smart“

Household

System

Balancing

Smart Appl.

Aggregator

Other Balancing

Power Providers

Wind

Generators

Other kWh

Generators

Power

Market

DSOs

Retailer of

„Smart“

Household

Other

Retailers

Other

Energy

Consumers

Appliances

Manufacturers

Appliances

Retailers

Economic

Benefit

Economic

Disadvantage

Options for

Incentives


22

Conclusions on Smart Appliances (SA)

• Domestic appliances offer a variety of load management options.

Technical constraints and consumer preferences define the limits.

• Consumers tend to accept SA if their daily routines are not changed and

comfort and safety are maintained.

• From a system perspective the value of SA is driven by the flexibility of

the conventional generation mix and the share of wind & solar energy.

• Typical values of SA for balancing wind generation are moderate. Not all

EU countries seem to offer viable potentials for SA.

• SA can have significant value, when contributing to congestion relieve

and reducing congestion costs.

• Incentive mechanisms are needed to give the right signals to the actors

involved in Demand Response through SA.


23

Many Thanks for Your Attention!

Christof Timpe

Smart-A Project Coordinator

Oeko-Institut e.V. –

Institute for Applied Ecology

Freiburg - Darmstadt - Berlin

PO Box 50 02 40,

79028 Freiburg, Germany

Ph.: +49-761-452 95-25

[email protected]

http://www.oeko.de

Project Websitehttp://www.smart-a.org

Technology

Smart Domestic Appliances Provide Flexibility for Sustainable Energy Systems