Quantifying our understanding of energy use itu may 2013

QUANTIFYING OUR UNDERSTANDING OF

ENERGY USE AND GHG EXTERNALITY IN

EVERYDAY LIFE

Adrian Friday, Mike Hazas,Adrian Clear, Janine Morley and

Oliver Bateshttp://wp.lancs.ac.uk/energychoices/

Thursday, 30 May 13

http://wp.lancs.ac.uk/energychoices/

http://wp.lancs.ac.uk/energychoices/

OUTLINE

• Report on our current work studying energy use in shared student accommodation (specifically energy, cooking)

• Quantified dual of empirical ‘sensing’ and qualitative methods

• Aim to convince you that

• eco-feedback interventions (e.g. in home displays/IHD) are not enough

• interventions must focus on reconfiguring energy intensive ‘services’ supporting everyday life, example of ‘cooking’

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VERY BIG PICTURE(Anderson & Bows. 2008 Philosophical Transactions A of the

Royal Society. 366. pp. 3863-3882)Thursday, 30 May 13


Royal Society. 366. pp. 3863-3882)

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SMART METERS & ECO-FEEDBACKCurrentCost, DIY Kyoto, Enistic, e.g. http://www.diykyoto.com/

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http://www.diykyoto.com

http://www.diykyoto.com

REWARDING BEHAVIOUR“The Ambient Canvas”, Bartram, 2010

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Weekly prizes were awarded for participation, and weekly emails announced winners, prizes and tips. Web sites run by the City and by Dubuque 2.0 also provided publicity.

The public nature of the pilot project had consequences. Its stakeholders, particularly elected officials, were aware that problems could reflect back on them. Thus, it was not acceptable to recruit volunteers for the pilot and then tell half that they could not use the Portal at all because they needed to serve as controls. Nor was it acceptable to make water consumption data from the pilot public (even though water usage data is, legally, public, and available to anyone who asks). Strict user ID and password requirements were enforced out of concern that users might expose their usage. In general, concerns of this sort sometimes drove the design of the system and the pilot in ways that were not ideal for research, particularly with respect to the more social features of the system.

The Water Portal User Interface Each household had a private portal, as shown in Figure 1. Just below the user ID (!), the timeline shows the daily water usage for the last year ("). Moving a ‘thumb’ along the timeline, shows a graph of the hour-by-hour usage for each day (#). The “Weekly Usage” tab displays a bar graph that shows usage for the week, each day broken into 4 periods. The “Compare” tab displays a bar graph that

contrasts usage per day of the week for the last 3 weeks.

The last tab, “This Week’s Game,” provides two means of socially shaping behavior. The first ($) shows the ongoing results of a weekly game. Each week teams of 4 to 6 households were automatically created by the system. Each team was matched against another team that was expected – based on previous consumption patterns – to use about the same amount of water during the upcoming week. The goal was, of course, to use less water than the opposing team. The results were updated throughout the week (with each household being able to see how it and each of its (anonymous) teammates were performing (via the segments in the bar in the graph). Finally, the farthest bar to the right (%) shows the amount of water used by “Neighbors Like You,” to which users can compare to their own usage. At the top right are statistics that provide various metrics of how the household is doing such as rank, and a menu bar that provides access to chat and news functionality (&).

THE STUDY The Portal was deployed to 303 households for 15 weeks. Multiple measures – logs, a survey and interviews – were used to evaluate its effects on its users’ behavior, beliefs and experience. The study examines the following areas: • Degree of usage. How many households made use of the

Water Portal, and what usage patterns did they exhibit?

Figure 1. The Water Portal.

Session: Sustainability & Behavior Change CHI 2012, May 5–10, 2012, Austin, Texas, USA

677

Dubuque energy portal

ENERGY USE AS IGNORANCE?e.g. Dubuque portal, (Erickson, 2013)

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DOES ECO-FEEDBACK WORK?

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5-15% SAVINGS POSSIBLE, BUT SHORTLIVED. WHY IS IT (IN)EFFECTIVE?

Hazas, Mike and Friday, Adrian and Scott, James (2011)doi:10.1109/MPRV.2010.89

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http://doi.ieeecomputersociety.org/10.1109/MPRV.2010.89

http://doi.ieeecomputersociety.org/10.1109/MPRV.2010.89

WHY DOESN’T ECO-FEEDBACK WORK?

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“grounded in a basic assumption that home dwellers lack information” (Pierce, 2010),

[...] required if they are understood as “micro-resource

managers” (Strengers, 2011)

disconnect between the types and methods of feedback, and “the realities of everyday life”

?Thursday, 30 May 13

OUR FOCUSHow energy connects to everyday life

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LIFE RATHER THAN CONSUMPTION OF ENERGY

• Shift focus towards the broader functions energy supports (e.g. making hot drinks, having clean clothes, entertaining oneself)

• => qualitative + quantitative understanding (Firth, 2008)

• Goal: to help explain the significant variation in energy consumption across similar homes (Hackett & Lutzenhiser, 1991, Gram-Hanssen, 2010)

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4 FLATS X 8 INDIVIDUAL STUDY BEDROOMS, 2 SHOWERS, 2 TOILETS, KITCHEN + CORRIDOR

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RETROFIT SENSING4 x OWL Single-point sensing +

RFXCOM

129 x Socket-level sensing (Plugwise)

42 x Motion/light, 38 x temperature/humidity

“Hobcam” (motion triggered camera)

Experience sampling + interviews

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20 DAYS

all common areas (kitchens, bathroom, corridor)22 participants opted in to in-bedroom monitoring

11 face to face follow up interviewsa few near-time ‘mini-accounts’ (questions posed by text/email)

3 8 5 6

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00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:000

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AGGREGATE USE10 minutes median bins

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Not discussed further here

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LightingRefrigerationEntertainment & ITOther cooking appliancesOven

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WHERE TO FOCUS?

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ALERTThursday, 30 May 13

ALERTIHDs focus on instantaneous load (Strengers, 2011), need ‘area

under the curve’, (c.f. Costanza, 2012)

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LIGHTING

• 16-29% of the energy in each flat

• bedrooms are comparable (~10 kWh)

• but communal areas more varied (46-85 kWh)

• A mix of conventions, expectations, meanings and actions around the lighting in the flats

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NOT SIMPLY UTILITARIAN

• Communal lights often left on (no surprise...)

• But, corridor switch-offs in “Green” (“otherwise they're just on for no reason”)

• Navigation (“well I really don't like the dark. When I come out of my room it's dark and I'm like arrrr”)

• Meanings around comfort and security

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ENTERTAINMENT AND IT

• Big variation: 3.5% to 34% of the energy

• room inventories

• most had laptops; three PCs

• 9/12 male participants had extra audio, video, or gaming devices

• A room’s energy attribution corresponded roughly to its inventory

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COMPUTING

• discrete periods of use, vs. consistently on

• laptops vs. other: order of magnitude less

• Blue: two server PCs; four with AV/gaming

• differing conventions for power management (Chetty, Brush et al. 2009)

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IT: ONE SERVICE TO RULE THEM ALL?

• multi-purpose: looking up lecture notes, doing coursework, music, reading the news, keeping in touch with friends

• low energy way to ‘do entertainment’

• significant overlap of these activities

• challenges in attributing which practices a service supports beyond disaggregation by appliance, (c.f. Gupta, 2010)

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‘CONSTELLATIONS’ OF DEVICES

• multiple devices clustered together

• e.g. “computer” a bunch of devices served by two sockets

• supporting a service like gaming or watching TV

• often makes sense to bundle the energy of these devices, and attribute to a single service, like entertainment (“I’ve got my hard drives, my router, my two monitors, my stereo and my desktop, that’s all hooked together.”)

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ENTERTAINMENT

• socialising: casual and planned group activities (“We spend a lot of time in each others rooms just talking and watching telly”)

• access to digital media infrastructures

• boredom and filling time has resource implications (“first year I used to play lots of games”)

• ‘connoisseurs of entertainment’

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SENSING + INTERVIEWS

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1. exposes service-reliance across areas of practice (personal and group entertainment, paid work, education, staying in touch, pre-boiling water for pasta...)

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2. identifies systems of devices and constellations of services (beyond appliance disaggregation), we might tackle together

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3. resource measurements can be actioned more effectively, taken in context (not motion triggered lights, but nightlights...?)

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3. resource measurements can be actioned more effectively, taken in context (not motion triggered lights, but nightlights...?)

4. facilitates higher-level reconsideration of how service might be reconfigured for sustainability

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A STEP TOWARD REFOCUSED INTERVENTIONS

Centred on the impact of food & cooking practices

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THE “HOBCAM”

BedroomBedroom

Bedroom

Bedroom

Kitchen Bedroom

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READY?Thursday, 30 May 13

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COOKING SESSION ANNOTATION

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One cook, single portion

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Components used

Back-right

Back-left

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Foods observed

Jarred sauce

Pasta

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... and quantities

(160g)

(100g)

Foods observed

Jarred sauce

Pasta

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Cooking method

Boiling

Heating

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Cooking method

Heating

Boiling

(no lid)

(no lid)

Use of lid?

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Changes in control position

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COOKING: QUANTIFIED

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RELATIVE IMPACTS

Cooking Energy Emissions (22%)

Indirect Emissions (78%)

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Other food

RELATIVE IMPACTS

Cooking Energy Emissions (22%)

Waste

Otherdevices

Indirect Emissions (78%)

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DESIGN AREAS

Diet Change

Technique & Method

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TECHNIQUE AND METHOD

Photo: reutC (via Flickr)

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FRYING VS. GRILLING

33m 30s170g

9m 50s

113g

0.118 kWh 0.965 kWh

Average 1.2 kWh/kg Average 6.7 kWh/kgThursday, 30 May 13

PASTA VS. PASTA

41 mins16 mins7 mins

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PIZZA VS. PIZZA27 minutes

...53 minutes before cooking

Oven switched on

85 minutes

36 minutes later...

...oven switched off

Pizza ready

55 minutes

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• Which calls into question technique, and cooking skills in play (Short, 2003)

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• But, also how food often takes a back seat to other activities

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• But, also how food often takes a back seat to other activities

• More efficient methods & techniques (reduce timing “errors” / “forgetfulness”), 10-20% cooking energy; 2-4% overall GHG

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DIET

Pastasauce

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DIET

High Impact

Low Impact

Pastasauce

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A CONVENIENT DIET

“typical student food”

“all those kind of really easy things”

0

20

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60

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jarred sauce

chicken

pastavegetables

sausages

chipspizza

breadbaked beans

ricepotatoes

tortellini

baconfrozen veg.

tinned tomatoes

eggnoodles

mince beef

steakreadymeal

fishsoup

61

70

87

88

41

43

21

9217

33

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1540

22

8 29

27

109

8 107

Embo

died

Ghg

em

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ns (k

g CO

2e)0

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60

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90

jarred sauce

chicken

pastavegetables

sausages

chipspizza

breadbaked beans

ricepotatoes

tortellini

baconfrozen veg.

tinned tomatoes

eggnoodles

mince beef

steakreadymeal

fish

61

69

87

66

41

43

20

8817

32

8

1541

21

8 29

27

109

8 10

Embo

died

GhG

em

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ns (k

g CO

2e)

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A CONVENIENT DIET

“typical student food”

“all those kind of really easy things”

0

20

40

60

80

jarred sauce

chicken

pastavegetables

sausages

chipspizza

breadbaked beans

ricepotatoes

tortellini

baconfrozen veg.

tinned tomatoes

eggnoodles

mince beef

steakreadymeal

fishsoup

61

70

87

88

41

43

21

9217

33

8

1540

22

8 29

27

109

8 107

Embo

died

Ghg

em

issio

ns (k

g CO

2e)0

10

20

30

40

50

60

70

80

90

jarred sauce

chicken

pastavegetables

sausages

chipspizza

breadbaked beans

ricepotatoes

tortellini

baconfrozen veg.

tinned tomatoes

eggnoodles

mince beef

steakreadymeal

fish

61

69

87

66

41

43

20

8817

32

8

1541

21

8 29

27

109

8 10

Embo

died

GhG

em

issio

ns (k

g CO

2e)

• Repeated moderate- to high-impact foods

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MEALS

Pastasauce

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MEALS

Pastasauce

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CHICKEN, PASTA, AND SAUCE

0

0.5

1.0

1.5

2.0

Region 1

Total: 3.57 Kg CO2e

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GRILLED POTATOES

0

0.1

0.3

0.4

0.5

Potatoes Cooker

Total: 0.62 Kg CO2e

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•Make indirect emissions more explicit to “cooks”, help keep infrequent high-impact foods “special” (Grimes, 2008), 20-30% indirect emissions; 17-24% overall GHG

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ORGANIZATION

Cooking & Eating

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ORGANIZATION

Cooking & Eating

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ORGANIZATION

Cooking & Eating

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ORGANIZATION

Cooking & Eating

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ORGANIZATION

Cooking & Eating

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“SIMPLE” & “EASY” =

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• Short cooking time (< 20mins) (~70%)

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• Single cooker component (69%)

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• Few “ingredients”

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• Repetitive

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• Repetitive

• Single portion

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• Repetitive

• Single portion

• Cooking for oneself (90%)

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SOCIAL COOKING

“we keep saying we’re going to cook together but something always

gets in the way”

“one person would go out or one person

would not want what we wanted”

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“WHATEVER’S IN THE CUPBOARD”

“I like vegetables and salads and stuff like that but when I buy it it just all

goes off...”

“um, risottos, stuff, pasta and sauce whatever, um

shepherds pie ...whatever ingredients we have”

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•Encourage more shared cooking, help overcome barriers or discover opportunities for sharing (impact?)

LOWER IMPACT COOKING?

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WE’VE LOOKED AT INDIRECT FOOD EMISSIONS AND COOKING ENERGY

EMISSIONS

both be addressed to some extent through cooking and the way it’s organised in everyday life, but...

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INTERDEPENDENCIES

Cooking Energy

Diet Change

Technique

Indirect Emissions

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INTERDEPENDENCIES

Cooking Energy

Diet Change

Technique

Indirect Emissions

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INTERDEPENDENCIES

Cooking Energy

Diet Change

TechniqueSharing

Indirect Emissions

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INTERDEPENDENCIES

Cooking Energy

Diet Change

TechniqueSharing

Indirect Emissions

Thursday, 30 May 13

INTERDEPENDENCIES

Cooking Energy

Diet Change

TechniqueSharing

Indirect Emissions

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INTERDEPENDENCIES

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INTERDEPENDENCIES

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INTERDEPENDENCIES

Cooking Energy

A Different Diet

Technique & Method

Sharing

Indirect Emissions

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DISCUSSION

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RESOURCE MANAGERS?

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RESOURCE MANAGERS?

• negotiable: feedback can expose things already seen as wasteful

• ...resulting changes tend to result in savings of about 10% (Darby, 2006)

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RESOURCE MANAGERS?

• negotiable: feedback can expose things already seen as wasteful

• ...resulting changes tend to result in savings of about 10% (Darby, 2006)

• non-negotiable: external factors dictate the possible range of actions, and which of them are affordable/rewarding/valued (Strengers, 2011)

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A BROADER VIEW

• sustainability research needs to take the broader view that it needs

• quantifying the impacts of everyday life

• and understanding how it connects and supports services and practices in the home

• due to the nature of variation, formative studies are always needed, and we advocate a qualitative/quantitative approach

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BUSY LIVES AND SOCIAL EXPECTATIONS

• social expectations dictate things like how we need to look or smell, which has big implications for daily practice (Shove 2003)

• powerful institutions (like employment)

• contribute to these expectations,

• tend to organise time in certain ways,

• ... making other ways of doing things more difficult

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BEYOND THE OBVIOUS

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BEYOND THE OBVIOUS• Eco-feedback interventions need to respect barriers to change

in the context of everyday life

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• We posit: there are non-trivial impact reductions through focused interventions

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• but, there is no one size fits all, we must understand each service, and we argue for a quantitative + qualitative approach

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• but, there is no one size fits all, we must understand each service, and we argue for a quantitative + qualitative approach

• Challenge: to design these focused interventions (in the widest sense), and reshape norms & expectations (Dourish, 2010) - can we go beyond 5-15%?

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[email protected]

http://wp.lancs.ac.uk/energychoicesThis work was funded by the UK Research Councils (EPSRC grants EP/G008523/1 and EP/I00033X/1), and the Facilities Division and Faculty of

Science and Technology at Lancaster University. Thanks to: Darren Axe at Green Lancaster, and the student residences officer at Lancaster University for their cooperation.

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mailto:[email protected]

mailto:[email protected]

http://wp.lancs.ac.uk/energychoices

http://wp.lancs.ac.uk/energychoices