ACM MuC2024_ Time and Money Matters for Sustainability_ Insights on User Preferences on Renewable Energy for Electric Vehicle Charging Stations.pdf

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Time and Money Matters for Sustainability: Insights on User Preferences on Renewable Energy for Electric Vehicle Charging Stations

ACM Mensch und Computer 24
Paper Link: https://lnkd.in/e6zW5jsP

Delong Du, Apostolos Vavouris, Omid Veisi, Lu Jin, Gunnar Stevens, Lina Stankovic, Vladimir Stankovic, Alexander Boden


MSCA GECKO Innovation and Training Network
Institut für Verbraucherinformatik
Socio-Informatics - University of Siegen

1. DOI: 10.1145/3670653.3670677
Time and Money Matters for Sustainability: Insights on
User Preferences on Renewable Energy for Electric
Vehicle Charging Stations
Delong K. Du
Apostolos K. Vavouris
Omid Veisi
Lu Jin
Prof. Dr. Gunnar Stevens
Prof. Dr. Lina Stankovic
Prof. Dr. Vladimir Stankovic
Prof. Dr. Alexander Boden

2. Public Charging Stations Navigation

3. Navigation Recommender System
Which one would you go?

4. Eco-Feedback
Which one would you go
now? If the further one is a
green charging station.

5. Main Takeaway

6. Renewable Energy Availability

7. Mehrnaz Anvari, Gerald Lohmann, Matthias Wächter, Patrick Milan, Elke Lorenz, Detlev Heinemann, M Reza Rahimi Tabar, and Joachim Peinke. 2016. Short term fluctuations of wind and solar
power systems. New Journal of Physics 18, 6 (2016), 063027
27. N Himabindu, Santoshkumar Hampannavar, B Deepa, and M Swapna. 2021. Analysis of microgrid integrated Photovoltaic (PV) Powered Electric Vehicle Charging Stations (EVCS) under
different solar irradiation conditions in India: A way towards sustainable development and growth. Energy reports 7 (2021), 8534–8547.
47. Abdallah Mohammed, Omar Saif, Maged Abo-Adma, Ashraf Fahmy, and Rasha Elazab. 2024. Strategies and sustainability in fast charging station deployment for electric vehicles. Nature
Scientific Reports 14, 1 (2024), 283
48. FM Mulder. 2014. Implications of diurnal and seasonal variations in renewable energy generation for large scale energy storage. Journal of Renewable and Sustainable Energy 6, 3 (2014).
49. National Grid ESO. 2023. Carbon Intensity API. Retrieved May 1, 2023 from https://carbonintensity.org.uk
73. P. Sreedharan, J. Farbes, E. Cutter, C.K. Woo, and J. Wang. 2016. Microgrid and renewable generation integration: University of California, San Diego. Applied Energy 169 (2016), 709–720.
https://doi.org/10.1016/j.apenergy.2016.02.053
1.Renewable Energy is not always available anytime anywhere
Renewable energy, despite its clean nature, is subject to fluctuation due
to variation [7, 48], and varying levels of infrastructure penetration
[49].
2.Electricity loss during transmission
Microgrid connections are ranging from exclusively renewable to
non-renewable or a combination of both [27, 47, 73].
3.Charging Station Navigation + Renewable Energy Availability
How would end users react?

7. Within-Subject Method

8. N=50 CHI-Square Statistics
Time & Money matters more
than sustainability: when
choosing charging stations
(powered or not powered by green
energy)
Sustainability
Not Significant
?????? = 0.838
Time
Significant
?????? = 0.027
Money
Significant
?????? = 0.009

9. Eco-feedback Influence
However, half of the users
(N=50) switched from
non-renewable to the green
ones.

Suggesting eco-feedbacks can
make an influence.

10. 10 EV Drivers Interview

11. I want to go home; F the planet
Disregarding Sustainability
I have no money; F the planet.

12. I want to go home; If the green
charging station is fast and near, I
will pay extra to go.

I have no money; If the green
charging station is cheap, I can drive
a little further.
Choosing Green Charging Stations

13. Discussion
• Sometimes in a Rush; Sometimes not
Such two major preference changes based on reality
• I remember which station is near
Users may rely on their spatial memory; thus voice assistant might work
• Weather, Traffic, Remaining Available Spots, & Surrounding
Weather and Traffic would require higher battery usage; Remaining available spots requires queuing
hassle; Surrounding would influence users routines.

User Context

14. Bonn-Rhein-Sieg University
of Applied Science
Delong Du
University of Siegen
Apostolos K. Vavouris
University of Strathclyde
Omid Veisi
University of Toronto
Lu Jin
Fraunhofer FIT
Prof. Dr. Gunnar Stevens
University of Siegen
Prof. Dr. Lina Stankovic
University of Strathclyde
Prof. Dr. Vladimir Stankovic
University of Strathclyde
Prof. Dr. Alexander Boden
Verbraucher Informatik