PERSONAL ENERGY ADMINISTRATION KIOSK APPLICATION Mobilizing residential electricity consumer demand response using an ICT-ecosystem with dynamic electricity price discounts Valeriya Azarova Jed J. Cohen Andrea Kollmann Johannes Reichl 1 June 2019

FACTS 10 PARTNERS 7 COUNTRIES 3 years DURATION 1,9 million € BUDGET smart metering Energy efficiency 7 COUNTRIES ICT 3 years DURATION Behavioral change 250 500 1500 ~2500 USERS social networks 1,9 million € BUDGET Serious gaming

MOTIVATION 80% of EU consumers shall be equipped with smart metering systems by 2020 An easy-to-use mobile application to manage electricity demand without intensive investments in hardware About 50% of the 230 mil. dwellings in the EU are apartments, with no property rights to install PV on the roof possibility to benefit from low-priced spot market prices

OBJECTIVES RESEARCH BEHAVIOURAL CHANGE EMPOWER THE END-USER CREATE COMPETITIVE ADVANTAGE FOR THE PROVIDER Gain insights on engagement, serious gaming, load shifts and sensitivity to prices of users in an energy efficiency context REMOVE BARRIERS FOR MARKET UPTAKE First market solution for forwarding the benefits of clean & cheaper renewable energy to consumers Develop individualized savings opportunities and enable energy consumption control without additional hardware Realizing prompt roll-out, ready-to-sign contracts, cost-benefit analyses, full data protection

POTENTIAL EFFECT Greater awareness of energy topics, prices, and own-consumption Changes in time of electricity use Switching to a ‘green’ power plan Household improvements in behavioral energy efficiency Reducing overall energy demand (2-7% reductions possible1) Decreasing system peak-power – this decreases network costs! Provides flexibility on the grid Increase demand at times of high RES production (demand dispatch) – allows for greater integration of renewable sources 1Delmas, M. A., M. Fischlein, and O. I. Asensio (2013). Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012. Energy Policy 61, 729 -739.

AUSTRIAN FIELDTEST 1.590 recruited users 1.060 with access to PEAKapp

FIRST INSIGHTS

Some statistics about PEAKapp users and their households*: Age: 20% of users are 35 to 45 years old 53% of PEAKapp users are from 45 to 65 years old 17% of users are older than 65 years Gender: 83% male 17% female Education: 56% professional training or Higher Technical school 18% University degree Income: 39% from 1400€ t0 2600€ 26% from 2600€ to 3400€ 27% more than 3400€ *based on results of the after survey completed by 250 PEAKapp users

EXPERIMENTAL DESIGN App users in the “Discount” group were sent messages throughout the field test period offering them a discount on all electricity consumption during specific periods. Price discounts at varying levels from 10% - to 50% Economic (European market price situation) or environmental (high share of production of renewable energy from wind or sun) reason On average two times per week From June 2017 to October 2018 Duration 1 to 3 hours Push messages sent day ahead or one hour ahead

Randomized control trial setting DATA Randomized control trial setting Panel data From June 2017 to October 2018 1589 households Smart meter data for all the three groups in 15 minutes intervals Socio-demographic data for all the three groups (including energy relevant appliances) Google Analytics data on application usage from the two treatment groups

ESTIMATION STRATEGY „Fixed effects panel data regression” ln(priceit) gives the cost in Euros per kWh of electricity for each 15 minute interval λit daily and hourly fixed effects µit household-hour fixed effects Errors are clustered at the household level

REPEATED DISCOUNTS RESULTS Discounts sent over the app increase consumption! Most effective discounts are those that happen at 14:00 or 19:00 and give a renewable energy reason for the discount Variable Estimate Std. Dev. electricity price (EUR/kWh) 0.161* (0.0915) 0.122 (0.0971) discount indicator 0.00961** (0.00394) 0.0115** (0.00486) treatment effect 0.966% 1.157% discount (%) 0.00049*** (0.00012) 0.00041*** (0.00015) HH by hour FE yes Day of sample FE no Hour of sample FE N 42046620 adj. R-sq 0.533 0.536 The “intention to treat effect” of the average discount is 1-1.15% increase in consumption

After PEAKapp: CHANGE Confirmed possibility to increase the load during the times of higher renewable production or cheaper supply costs through discount messages On average the electricity consumption increased by 1.15% Environmental reasons for discounts showed higher increase in electricity consumption than economic Proven potential to mobilize demand response during times of high renewable energy production, and thereby decrease the storage and transportation requirements on the grid Improve ability of the electricity grid to integrate renewable sources of electricity, and decrease GHG emissions from the electricity sector by shifting consumption to times when more renewable electricity

CONTACT: peakapp@energieinstitut-linz.at WEBSITE: Peakapp.eu Thank you CONTACT: peakapp@energieinstitut-linz.at WEBSITE: Peakapp.eu