Sense4En – Technical report (Feedback strategies: Energy efficiency in the shower) 1

ABOUT THIS DOCUMENT

This document: describes project approach and consortium, focuses on work and results on the topic „Smart Metering / Energy efficiency in the shower“, lists the geneated literature for reference, frames the project work within larger initiatives of the contributing groups.

Whenever possible, materials and content are linked to their respective web pages.

Additional publications from evaluation of the long-term experiment on warm water matering areexpected to appear in 2015.

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Project name: Sense4EnKey words: Energy consumption in households, smart metering, large scale testing,

heat, shower, room heating,feedback strategies, user behavior, user engagement.

Funding Institution: Climate-KIC, an iniative of the European Institute of Innovation andTechnology (EIT) to bridge education, entrepreneurship andinnovation in Europe.

Project partners: Technical University Berlin, Eigenossische Technische Hochschule (ETH) Zürich,Vattenfall. Subcontractor: University of Bamberg. Technology provider: Amphiro AG.

Project life time: April 2012 - April 2014

Project web site: http://www.sense4en.tu-berlin.de/

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TABLE OF CONTENTS

SUMMARY..........................................................................................................................................4VIDEOS...............................................................................................................................................41. ENERGY EFFICIENCY IN THE SHOWER..................................................................................51.1 FEEDBACK AND ENERGY........................................................................................................51.2 THE INTELLIGENT DISPLAY AMPHIRO A1...........................................................................61.3 FEEDBACK INTERVENTIONS FOR AMPHIRO A1.................................................................81.4 THE FEEDBACK STUDY............................................................................................................91.5 AMPHIRO APP .............................................................................................................................91.6 CONCLUSIONS..........................................................................................................................102. GENERATED SCIENTIFIC PUBLICATIONS.............................................................................113. FEEDBACK STRATEGIES: REFERENCES...............................................................................124. CONTRIBUTING GROUPS.........................................................................................................14

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SUMMARY(Ivana Agnolin @ Technical University Berlin)

Households account for one third of energy consumption in Europe, thus savings in this sector are strategic.Durable savings cannot be attained with energy efficient technologies alone. Rather, their attainementrequires active engagement of the user , as user behavior heavily influences how technology and energy areemployed. Sense4En embraced this challenge by developing and testing feedback strategies empowering users to saveenergy at home. It adopted a user centered approach which integrates technology development and userbehavior psychology. As opposed with the persistent centrality of electricity in the current discussion aboutSmart Metering, Sense4En focused on showering and room heating. In the EU on average, but also inGermany and Switzerland, these account for, in turn, 13% and 70% of household energy consumption. This document focuses on the Sense4En work on warm water consumption. Specifically, feedback andincentive strategies for this specific consumption behavior were formulated, implemented and tested atlarge scale in Zürich (CH) on example of an intelligent display. Use of the Smart Meter generated average23% savings, which correspond to 440KWh/year/household, the yearly consumption of two washingmachines or five laptops. In first place, the study demonstrated that real-time feedback on a specificbehavior can prompt substantial behavioral change.

In 2012, households accounted for 26% of EU end energy consumption, 27% in Switzerland and Germany. Thenumbers are in %, refer to Switzerland (Prognos 2014) but apply closely also to Germany (Statistisches Bundesamt).

VIDEOS

This short movies are explanatory of installation and use of the intelligent display employed in Sense4En.(2014) Energy efficiency in the shower: The story of the experiment

70,7

12,5

1,9

1,8

1,9

3,722,63 Room heating

Hot water

Lightning

Air conditioning, household technique

Entrateinment, IT

Cooking, Dish washing

washing, drying

refrigerating

other electricity

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1. ENERGY EFFICIENCY IN THE SHOWER(Bits-to-Energy Lab, a joint initiative of ETH Zurich and the Universities of Bamberg and St. Gallen: Thorsten Staake @ Univ. of Bamberg & ETH Zürich; Vojkan Tasic, Samuel Schoeb @ ETH Zürich; Anna Knupfer, Mariya Sodenkamp, Ilya Kozlovsky @ Univ. of Bamberg)

1.1 FEEDBACK AND ENERGYConsumers behavior influence on energy demand is large: through the individual driving style, the choice oftemperature in the own apartment, the effort made to turn off electrical devices when not in use – manyconscious and unconscious decisions directly affect our energy budget. Changes are not easy to induce. Firstof all, most domestic energy usage is invisible to the consumers, which tend to have only vague ideas ofhow much energy they expend for different purposes (Darby 2006), with the consequence of limitedawareness on the personal behavior’s consequences, perceived lack of control and low “energy literacy”,even among individuals with a higher degree of education. While energy-saving tips and enhanced billingseem to meet rather high participation but to generate low savings, prompt feedback on instantaneousenergy usage is regarded as a promising way to durably remedy the mentioned obstacles. However, recentinvestigations reveal that not just the fact that feedback is provided, but rather how this is done explainsthe saving effects.

Fig.1: Average household electricity savings by feedback type, based on 36 studies (Erhardt-Martinez 2010).

Figure 2 shows the increasing impact of feedback with higher resolution in time (Houde et al. 2013;Ehrhardt Martinez et al. 2010). Further differentiation arises from the implemented strategies. For example, descriptive normativefeedback (i.e., the comparison to others) leads to a strong decrease in demand among consumers withabove average consumption, while leading to an increase in demand among consumers with below averageconsumption (Schultz et al. 2007). Injunctive normative feedback (i.e., others think about ones behavior orperformance) achieves the same for high consumers, yet does not lead to higher demand among those whoalready perform better than average (Schultz et al. 2007). Look at al. (2013) show that injunctive feedbackcan prevent perverse effects of descriptive feedback. Another powerful concept is the implementation ofsaving goals (Loock et al. 2013). This suggests the necessity of carefully assessing what feedback mechanismshould be chosen for a given information system.Accordingly, feedback interventions and their effectiveness were first overviewed and classified. As sources,

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we used meta-reviews, studies on individual interventions, interviews and own experience (see references).We differentiate between Aggregated and real-time feedback. Then, feedback strategies (in form of real-time and aggregated feedback) were outlined and implemented to address showering as specificconsumption behavior. These strategies were implemented and tested on the example of an intelligentdisplay informing users on their hot water consumption in the shower.

1.2 THE INTELLIGENT DISPLAY AMPHIRO A1A large-scale study was designed to test for the effectiveness of feedback strategies on showering. In fact,showering is extremely relevant to the household energy budget, and can be addressed specifically.The feedback was implemented with help of an intelligent display for the shower. This is a low power LCdisplay with 112 segments. This number represents an upper bound for the device, the segment shapecannot be changed, the segments can be turned on and off by the accompanying software.

Fig.2: The amphiro device (picture source: Amphiro).

Amphiro needs no battery, and generates the energy necessary for operation from the water flow. A smallcapacitor serves as short-time buffer. As a consequence, the device is active only as long as water flowsthrough it plus two additional minutes until when the capacitor is empty. A timer is active during the waterflow, which allows to calculate flow rates, yet it does not measure the time at which the shower takes place.The memory is non-volatile, so that states and values can be permanently saved. The device has noembedded internet connection. During the shower, the display top (1 in Fig.2) switches every three seconds between temperature andenergy efficiency class. The largest digits in the middle of the display (2) indicate water volume and heatenergy. At the bottom (3), an animation with a polar bear on an ice shell evolves with water consumption,in that the shell shrinks with growing consumption. At the end of the shower, the display top stops togglingand shows the energy efficiency class. Aggregated consumption information is used to generate a dynamic 8‐digit alphanumeric code which userscan digited into an online portal. The code is shown for about 30 seconds after each individual showerinstance, and includes an average on water temperature from the last 150 showers, three volume averagesof the last three bins of 50 showers (shower 1 to 50; 51 to 100; and 101 to 150), and the total number ofshowers. The procedure is presented to the users as shown in Figure 3.

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Fig.3: Code Generation by the amphiro device (picture source: Amphiro).

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Fig. 4: Real-time feedback with the intelligent display.

1.3 FEEDBACK INTERVENTIONS FOR AMPHIRO A1The feedback strategies must be compatible with the device, regarding user interface, power supply, datastorage, and data transfer capabilities. The chosen feedback strategies classify as follows:For Real-time Feedback Interventions:

Numeric real-time information (water in liters), Aggregated energy feedback in kWh after each shower instance, real-time efficiency ratings (A+ to G-), An emotional component (an ice bear on an ice shell which gets smaller with increasing

consumption).For Aggregated Feedback:

Numeric information (water in liters, Energy in kWh), efficiency rating (A+ to G-), Injunctive normative feedback (smiley / winey), Trend information for the first implementation. On a longer term run, a competition-component is

planned.

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1.4 THE FEEDBACK STUDYThe experiment included a short and a long time testing campaign.

Short-Term Study The Swiss federal Office of Energy funded a first short term study in Zürich to evaluate Smart Metering andFeedback strategies in the perspective of Smart Metering and Smart Grid roll-out in Switzerland. Incollaboration with the Zürich energy provider ewz, the shower monitor amphiro a1 was first deployed in7'000 households for two months between end of 2012 and beginning of 2013. Of these households, 697participated in the accompanying survey. The Climate-KIC project „Sense4En“ supported the technologicaldevelopment necessary for the experiment and data interpretation. This is aligned with the specific featuresof the EU Climate-KIC funding programs, which support high-impact complementary project constellationswith the purpose of optimising synergies and, with them, the chances for innovations.The study used a difference-in-difference design. Pre-intervention data were collected during a baselineperiod in which no information was shown for about ten shower instances. Then, the display activated itselfautomatically at the onset of the treatment period. In parallel, in a control group the amphiro a1 deviceremained in baseline mode during the entire testing period.The experiment resulted in a 23% reduction of energy and water use for the target behavior. The 23%consumption reduction corresponded to 74 kWh (16 kg of CO2)1 heat energy for the average household,significantly larger than the 14 kWh (2 kg of CO2)2 for the smart metering case for electricity tested over thesame period (Degen et al. 2013).

Long-Term StudyUntil March 2014, a sub group of the short-term study participated also in the long-term study. These datawere collected via an accompanying survey and are currently being analyzed.

1.5 AMPHIRO APP Sense4En extended the amphiro platform by developing an associated mobile application. The Appprovides an interface for displaying consumption on mobile phones and devices. While having being alreadyincorporated into the product offer, the App was not part of the configuration employed in the experiment.

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Fig.5: The App extending the Amphiro platform. The long-term feedack is also accessible through an internet portal.

1.6 CONCLUSIONSThe two month study demonstrated that real-time feedback on a specific behavior can prompt substantialbehavioral change, resulting in a 23% reduction of energy and water use for the target behavior. In the 2months study period, this resulted in a reduction of 74 kWh (16 kg of CO2)1 in heat energy for the averagehousehold, compared to 14 kWh of electric energy (2 kg of CO2)2 for the smart metering case over the sameperiod (Degen et al. 2013). The collection of survey data will allow to disentangle the underlyingmechanisms.

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2. GENERATED SCIENTIFIC PUBLICATIONSWhen directly accessible, a web link is included in the publication title.

2013: Loock, C., Staake, T., Thiesse, F., Motivating Energy-Efficient Behavior with Green IS: An Investigation

of Goal Setting and the Role of Defaults, MIS Quarterly 37(4), 1313-1332 Tiefenbeck, V., Staake, T., Roth, K., Sachs, O. For better or for worse? Empirical evidence of moral

licensing in a behavioral energy conservation campaign, Energy Policy (57), 160-171 Tiefenbeck, V., Tasic, V., Schöb, S., Staake, T. Pushing the boundaries of energy informatics: The

application of direct feedback to reduce hot water consumption; 39th Annual Conference of the IEEE Industrial Electronics Society (IECON 2013), Vienna, Austria, November 11-13

Tiefenbeck, V., Tasic, V., Staake, T., Goette, L., Real-time feedback and social dynamics in energy conservation: evidence from randomized trials with 50,000 showers, Behavior, Energy and Climate Change (BECC 2013), Sacramento, USA, November 18-20

Tiefenbeck, V., Tasic, V, Staake, T., Fleisch, E. Contrasting the effects of real-time feedback on resource consumption between single- and multi-person households, SSES Annual Meeting 2013, Neuchatel, Switzerland, June 2013

Kleiminger, W., Beckel, C., Staake, T., Santini, S. Occupancy Detection from Electricity Consumption Data Title ; 5th ACM Workshop on Embedded Systems for Energy-Efficient Buildings (BUILDSYS), Rome, Italy, November 13-14

Lossin, F., Staake, T., Fleisch, E., Online-based energy auditing and incentive mechanisms to reduce domestic energy consumption , Swiss Society of Economics and Statistics Meeting 2013: The Energytransition and its Challenges

2012: Loock, C.; Landwehr, J.; Staake, T.; Fleisch, E.; Pentland, A. The influence of reference frame and

population density on the effectiveness of social normative feedback on electricity consumption, Proceedings of AIS International Conference on Information Systems (ICIS, Orlando, Florida) 2012, on line

F. Weiss, M., Staake, T., and Mattern, Leveraging smart meter data to recognize home appliances, Proceedings of IEEE conference “Pervasive Computing and Communication (PerCom)”, Lugano, Switzerland (March 2012), 190-197.

Tasic, V., Staake, T., Stiefmeier, T., Tiefenbeck, V., Fleisch, E., Tröster, G., Self-powered Water Meter for Direct Feedback, Proceedings of 3rd Conference of Internet of Things (IOT), Wuxi, China (October 2012), 24-30

Beckel, C., Kleiminger, W., Staake, T., Santini, S., Improving Device-level Electricity Consumption Breakdowns in Private Households Using ON/OFF Events, ACM SIGBED Review – Special Issue on the 3rd International Workshop on Networks of Cooperating Objects (CONET 2012, Beijing, China), Volume 9 (3), July 2012, 32-38

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3. FEEDBACK STRATEGIES: REFERENCES Abrahamse, W., Steg, L., Vlek, C., and Rothengatter, T. (2005). A review of intervention studies

aimed at household energy conservation. Journal of Environmental Psychology, 25(3):273–291. Allcott, H. And Mullainathan, (2012). External validity and partner selection bias. Working Paper

18373, National Bureau of Economic Research. Allcott and Rogers (2014); Ayres, I., Raseman, S., and Shih, A. (2009). Evidence from two large field

experiments that peer comparison feedback can reduce residential energy usage. Working Paper 15386, National Bureau of Economic Research.

Carragher, B. J., Stewart, R. A., and Beal, C. D. (2012). Quantifying the influence of residential water appliance efficiency on average day diurnal demand patterns at an end use level: A precursor to optimised water service infrastructure planning. Resources, Conservation and Recycling , 62:81– 90.

Cialdini, . B. (2009). Influence:science and practice . Pearson Education, Boston. Darby, S.(2006). The effectiveness of feedback on energy consumption. A review for DEFRA of the

literature on metering, billing and direct displays. Technical report. Darby, S. (2011). Smart metering: what potential for householder engagement? Building Research & Information, 38(5):442–457.

Degen, K.,Efferson, C., Frei, F., Götte, L., and Lalive, R. (2013). Smart Metering, Beratung oder sozialer Vergleich: Was beeinflusst den Elektrizitätsverbrauch? Final report to the Swiss Federal Office of Energy.

Ehrhardt Martinez, K., Donnelly, K. A., and Laitner, S. (2010). Advanced metering initiatives and residential feedback programs: A meta--‐review for household electricity--‐saving opportunities. ACEEE Research Report E105.

Faruqui, A.,Sergici, S., and , A. (2010). The impact of informational feedback on energy consumption—A survey of the experimental evidence. Energy ,35(4):1598–1608.

Ferraro, P. J., Miranda, J. J., and Price, M. K. (2011). The persistence of treatment effects with norm--‐ based policy instruments: evidence from a randomized environmental policy experiment. American Economic Review, 101(3):318-322.

Ferraro, P. J. And Price, M. K. (2013). Using nonpecuniary strategies to influence behavior: Evidence from a large--‐scale field experiment. Review of Economics and Statistics, 95(1):64–73.

Fielding, K. S., Spinks, A., Russell, S., McCrea, R., Stewart, R., and Gardner, J. (2013). An experimentaltest of voluntary strategies to promote urban water demand management. Journal of Environmental Management , 114:343–351.

Froehlich, J., Findlater, L., and Landay, J. (2010). The´design of eco--‐feedback technology. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’10, page 1999–2008, New York, NY, USA. ACM.

Gardner, Gerald T. And Paul C. Stern (2008). The Short List: The Most Effective Actions U.S. Households Can Take to Curb Climate Change, Environment, 50, 12–23.

Gardner, G.T. And Stern, P. C. (2008). The short list: The most effective actions U.S. Households can take to curb climate change. Environment , 50:12–23.

Goelz,S. (2011). Smart Energy und der Endkunde --‐ Ergebnisse und Schlussfolgerungen aus der Smart EnergyForschung. Energietouren 2011 "Smart Metering – Smart Home" Intelligent mit Strom umgehen. 2011-- 11--‐29. Freiburg. <www.hwk--‐freiburg.de/web/adb/output/asset/19616>.

Goldstein, N. J., Cialdini, R. B., and Griskevicius, V. (2008). A room with a viewpoint: Using social norms to motivate environmental conservation in hotels. Journal of Consumer Research, 35(3):472–482.

Houde, S., Todd, A., Sudarshan, A., Flora, J. A., and Armel, K. C. (2013). Real--‐time feedback and electricity consumption: A field experiment assessing the potential for savings and persistence. The Energy Journal , Volume 34(Number 1). intelliekon (2011). Intelliekon --‐ achieving sustainable

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energy consumption with smart metering, communication and tariff systems. Technical report, Freiburg.

Kinzig, A. P., Ehrlich, P. R., Alston, L. J., Arrow, K., Barrett, S., Buchman, T. G., Daily, G. C., Levin, B., Levin, S., Oppenheimer, M., Ostrom,., and Saari, D. (2013). Social norms and global environmental challenges: The complex interaction of behaviors, values, and policy. BioScience , 63(3):164–175.

Loock, C.--‐M., Staake, T., and Thiesse, F. (2013). Motivating energy--‐efficient behavior with green IS: an investigation of goal setting and the role of defaults. Management Information Systems Quarterly.

Mazur Stommen (2012); McKenzie--‐Mohr, D. (2013). Fostering Sustainable Behavior: An Introduction to Community--‐ Based Social Marketing New Society Publishers.

Mitchell, D. L., Cubed, M., and Chesnutt, T. W. (2013). Evaluation of east bay municipal utility district’s pilot of at erSmart home water reports. Technical report.

Neenan (2009). Residential Electricity Use Feedback: A Research Synthesis and Economic Framework, Electric Power Research Institute, EPRI 2009.

Nolan, J. M., Schultz, P. W., Cialdini, R. B., Goldstein, N. J., and Griskevicius, V. (2008). Normative social influence is underdetected. Personality and Social Psychology Bulletin, 34(7):913–923.

Raw, G. And Ross, D. (2011). Energy demand research project: Final analysis --‐ AECOM. Technical Report 60163857, Hertfordshire.

Schleich, J., Klobasa, M., S., and Brunner, M. (2013). Effects of feedback on residential electricity demand Findings from a field trial in austria. Energy Policy , 61:1097–1106.

Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., and Griskevicius, V. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18(5):429–434.

SFOE (2013). Schweizerische Gesamtenergiestatistik 2012, Report, Swiss Federal Office of Energy (BFE).

Tiefenbeck, V., Tasic, V., Schöb, S., Staake, T. (2013). Mechatronics to drive environmental sustainability: measuring, visualizing and transforming consumer patterns on a large scale, D--‐A--‐ CH Energieinformatik 2013, Vienna, Austria.

Tulusan, J., Staake T., Fleisch, E. (2012). Providing eco--‐driving feedback to corporate car drivers: what mpact does a smartphone application have on their fuel efficiency? Proceedings of the 2012 ACM Conference on Ubiquitous Computing, 212-215

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4. CONTRIBUTING GROUPS

Quality & Usability Lab – The group aims to measure, model and assess quality of IT systems at the human-computer interface with respect to user-friendliness and self-explanatoryness. Quality of Speech & Video Transmissionand Multimodal Systems are the fields of application. Activities merge technology development with user centred engineering. Tasks: In Sense4En, the group programmed the Amphiro App, supported technological development for RF data transmission of Amphiro data, conceived and evaluated the user experience for the Room Heating solution.

In charge: Tilo Westermann, Sebastian Möller. Building Technology & Design – The group focuses on integration of renewable energies and energyefficient technologies in architectural design. This requires knowledge of user habits, needs and behavior. Tasks: the group simulated numerically the behavior of users in their apartments and conceived theintelligence of the Room Heating system. In charge: Johanna Moser. Project Management: Ivana Agnolin.Center for Entrepreneurship – The center supports TU Berlin students and personnel in the first stepstowards entrepreneurship and in the last six years has qualified as the most successful in the Berlin-Brandenburg region. Its team makes the kern of the entrepreneurship German center of Climate-KIC. Tasks: the group conceived and implemented the Open Innovation Slam. In charge: Franke Birke.

Bits to Energy Lab B2E – A joint initiative of ETH Zurich and the Universities ofBamberg and St. Gallen, the lab combines information technology andbehavioral science to the aim of supporting sustainable energy consumption.Research focuses on consumption feedback, customer engagement and data

analytics, with emphasis on economically attractive applications; on informing the Swiss authorities informulating their Smart Metering roll-out strategy. Tasks: the group conceived and implemented the feedback for the large scale deployment of a1 in Zürichand interpreted the experimental results. In charge: Thorsten Staake, Vojkan Tasic

A spinOff of the B2E at the ETH-Zürich, Amphiro makes the animated display a1 available on the market. Among the distribution channels, a1 is available through the Amphiro web-site, Amazon, Grünspar. Tasks: technology providerand support in implementation of the large scale experiment.

Energy Efficient Systems Group - Merges IT with knowledge of and research on consumption behavior, trends and psychology, to the purpose of supporting IT engineering in the Smart Grid. The focus is two-fold: large scale IT engineering for energy production and distribution, and the smaller scale of households and individual consumption. Tasks: Thorsten Staake leaded the feedback design and intelligence for a1.

Berlin electricity and heat provider. Tasks: Vattenfall explored application and business perspectives of the RoomHeating system. In charge: Peter Vespermann.