TY - GEN
T1 - Uberizing the Charging Ecosystem for Electric Vehicles
AU - Krishna, Aakash
AU - Narayanan, Ajay
AU - Krishnakumar, Sunil
AU - Misra, Prasant
AU - Vasan, Arunchandar
AU - Sarangan, Venkatesh
AU - Sivasubramaniam, Anand
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/6/12
Y1 - 2020/6/12
N2 - In many metropolitan cities, multi-unit residential buildings (MURB) are becoming more common than single-family independent homes due to lack of urban space. MURB residents (around 42% in Europe) are potential adopters of electric vehicles (EV), but lack a private garage for EV charging. They need to exclusively rely on public charging, which currently serves only 5% of EVs. As EVs become more prevalent, the lack of extensive public charging can create a short-term demand-supply mismatch in specific city neighbourhoods, as well as preclude long-term growth in EV adoption. We believe that uberization of private garage chargers that are typically under-utilized during day-time can alleviate this problem. In this work, we examine how a charging service provider can match public charging demand with private suppliers while using a demand-response based pricing model. We base our study on real-world traffic patterns for the city of Luxembourg by augmenting the Luxembourg SUMO traffic scenario (LuST) simulator. Specifically, an EV's charging demand is modeled by a state machine with charge/discharge dynamics based on Tesla Model-S. Our preliminary results suggest that the proposed uberization strategy has the potential to gracefully handle demand spikes with higher revenue yield for a charging service provider, even while handling different categories of service users.
AB - In many metropolitan cities, multi-unit residential buildings (MURB) are becoming more common than single-family independent homes due to lack of urban space. MURB residents (around 42% in Europe) are potential adopters of electric vehicles (EV), but lack a private garage for EV charging. They need to exclusively rely on public charging, which currently serves only 5% of EVs. As EVs become more prevalent, the lack of extensive public charging can create a short-term demand-supply mismatch in specific city neighbourhoods, as well as preclude long-term growth in EV adoption. We believe that uberization of private garage chargers that are typically under-utilized during day-time can alleviate this problem. In this work, we examine how a charging service provider can match public charging demand with private suppliers while using a demand-response based pricing model. We base our study on real-world traffic patterns for the city of Luxembourg by augmenting the Luxembourg SUMO traffic scenario (LuST) simulator. Specifically, an EV's charging demand is modeled by a state machine with charge/discharge dynamics based on Tesla Model-S. Our preliminary results suggest that the proposed uberization strategy has the potential to gracefully handle demand spikes with higher revenue yield for a charging service provider, even while handling different categories of service users.
UR - http://www.scopus.com/inward/record.url?scp=85088505287&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85088505287&partnerID=8YFLogxK
U2 - 10.1145/3396851.3397758
DO - 10.1145/3396851.3397758
M3 - Conference contribution
AN - SCOPUS:85088505287
T3 - e-Energy 2020 - Proceedings of the 11th ACM International Conference on Future Energy Systems
SP - 156
EP - 160
BT - e-Energy 2020 - Proceedings of the 11th ACM International Conference on Future Energy Systems
PB - Association for Computing Machinery, Inc
T2 - 11th ACM International Conference on Future Energy Systems, e-Energy 2020
Y2 - 22 June 2020 through 26 June 2020
ER -