Maximizing Smart Charging of EVs: The Impact of Privacy and Money on Data Sharing

Smart charging has the potential to shift peak load to times of lower demand, which better exploits renewable generation and enhances grid resilience. For increased effectiveness, smart charging requires access to data that consumers might be hesitant to share. To explore which data consumers would share and which factors influence this decision, we adopt the Barth and de Jong’s risk-benefit calculation framework to smart charging and conduct an online-survey (n = 479). We find that most respondents who would share charging details with a smart charging application, are ambivalent about location data and would never share calendar details. When presented with concrete monetary rewards, participants lose their initial reservations and would share all data for an amount dependent on the data’s sensitivity. Thus, our study contributes to research on the privacy paradox by highlighting the importance of calculations between perceived risks and benefits for the decision to share data

Towards an evaluation of incentives and nudges for smart charging

Electric vehicles (EVs) are an important cornerstone to achieve transport decarbonization. Still, simultaneous charging of EVs when home charging increases peak demand, especially during evenings. Smart charging allows optimal distribution of load, thus preventing peak loads. Nevertheless, this incorporates certain risks for the EV user, e.g., unavailability of EVs for unplanned events. This might lead to a lack of user acceptance. This paper focuses on specific incentives and nudges, motivating users to adopt smart charging. We conducted an integrative literature review, bringing together literature from different areas. Possible incentives and nudges are monetary incentives, feedback, gamification, or smart charging as a default-setting. We conducted three focus groups with 13 EV users in Luxembourg to get first insights into which of those incentives and nudges they prefer. Preliminary results indicate that incentives and nudges should be individualized. In the future, we would use these first insights to develop a large-scale survey

Empirical evaluation of behavioral interventions to enhance flexibility provision in smart charging

peer reviewedThe growing adoption of Electric vehicles (EVs) puts pressure on the power grid, and implementing smart solutions can ease this pressure. Smart charging at home is a solution where users offer flexibility in their charging schedule, which energy suppliers and/or other aggregators can exploit by charging during times of low demand and low market prices. However, giving charging control to the energy provider can concern EV users, particularly about driving range, and give a sense of loss of control. We conducted an experimental online survey with EV users (n = 289), examining the effect and perception of different behavioral interventions to improve flexibility provision. We found that all monetary incentives (high, low, credit points) resulted in higher flexibility, while environmental framing, feedback and badges, default-setting, and battery-related tips had no effect. The perception of all behavioral interventions did not correlate significantly with the flexibility offered for any of the interventions

Maximizing Smart Charging of EVs: The Impact of Privacy and Money on Data Sharing

peer reviewedSmart charging has the potential to shift peak load to times of lower demand, which better exploits renewable generation and enhances grid resilience. For increased effectiveness, smart charging requires access to data that consumers might be hesitant to share. To explore which data consumers would share and which factors influence this decision, we adopt the Barth and de Jong’s risk-benefit calculation framework to smart charging and conduct an online-survey (n = 479). We find that most respondents who would share charging details with a smart charging application, are ambivalent about location data and would never share calendar details. When presented with concrete monetary rewards, participants lose their initial reservations and would share all data for an amount dependent on the data’s sensitivity. Thus, our study contributes to research on the privacy paradox by highlighting the importance of calculations between perceived risks and benefits for the decision to share data.U-AGR-8002 - Enovos Inductive (01/01/2021 - 31/12/2022) - CORDY Maxim

Towards an evaluation of incentives and nudges for smart charging

Electric vehicles (EVs) are an important cornerstone to achieve transport decarbonization. Still, simultaneous charging of EVs when home charging increases peak demand, especially during evenings. Smart charging allows optimal distribution of load, thus preventing peak loads. Nevertheless, this incorporates certain risks for the EV user, e.g., unavailability of EVs for unplanned events. This might lead to a lack of user acceptance. This paper focuses on specific incentives and nudges, motivating users to adopt smart charging. We conducted an integrative literature review, bringing together literature from different areas. Possible incentives and nudges are monetary incentives, feedback, gamification, or smart charging as a default-setting. We conducted three focus groups with 13 EV users in Luxembourg to get first insights into which of those incentives and nudges they prefer. Preliminary results indicate that incentives and nudges should be individualized. In the future, we would use these first insights to develop a large-scale survey

Impact of Minimum Energy Requirement on Electric Vehicle Charging Costs on Spot Markets

peer reviewedSimultaneous charging of electric vehicles (EVs) increases the peak demand and might lead to higher electricity prices. This could increase EV charging costs and make EVs unattractive. Smart charging utilizes the flexibility provided by EVs and adapts charging behavior in response to the electricity market price signals. However, some studies indicate users' reluctance to participate in smart charging programs, as they perceive the risk of their vehicle not being charged sufficiently at required times. As a countermeasure, several researchers use the concept of minimum state of charge (SOCmin). It is the percentage of the battery up to which the EV is charged uncontrollably at full power right after it is connected to the charger. Depending on the users' SOCminrequirement, there might be an impact on EV flexibility and subsequently on EV charging costs. We developed a novel flexibility algorithm which quantifies EV flexibility in terms of both energy and power as a function of time. To calculate the EV charging costs, we developed a two-stage scenario-based stochastic optimization model. Optimization utilizes flexibility input and minimizes charging costs while participating in both day-ahead and intraday markets. We found that in most cases where EVs provide some flexibility, there was no significant increase in charging costs. However, we observed a 50% increase in costs when EVs do not provide flexibility. Therefore, EVs possess high flexibility potential. This flexibility can be provided almost without any loss of user comfort for high monetary gains.U-AGR-8002 - Enovos Inductive (01/01/2021 - 31/12/2022) - CORDY Maxime7. Affordable and clean energ