Online electric vehicle recharge scheduling under different e-mobility operator's pricing models

Abstract

Electric Vehicles (EV) appear as a clean transportation technology with clear environmental advantages and potential benefits for the grid, being a key element of future modern smart cities. However, autonomy of the vehicle and lack of recharging stations are barriers that need to be overcome in order to make the service reliable and broadly accepted. To tackle this problem, French GreenFeed project is working to define and implement an interoperable and universal architecture to allow EV-recharge roaming. In this work, we consider such architecture and focus on issues faced by the e-mobility operator (EMO) and identified by the GreenFeed project. The EMO, a key actor in the architecture, maintains contracts with EV users to allow EV recharge at any geographical place (recharge roaming) through agreements with charging infrastructure operators. The interest of the EMO is to schedule the recharge demands and fulfil the contracts while maximizing its revenue. We analyse different online EV recharge scheduling under different pricing models, agreed between the EV users and the EMO, to study their impact on the EMO's revenues. In this analysis, we assume recharges arriving at random times and requesting a certain amount of energy during a fixed time period. We simulate a scenario with real day-ahead hourly electricity prices over two years and different scheduling polices to illustrate the feasibility of online recharge scheduling.