An Optimal Day-Ahead Scheduling Framework for E-Mobility Ecosystem Operation With Drivers’ Preferences

The future e-mobility ecosystem will be a complex structure with different stakeholders seeking to optimize their operation and benefits. In this paper, day-ahead grid-to-vehicle (G2V) vehicle-to-grid (V2G) scheduling framework is proposed including electric vehicles (EVs), charging stations (CSs), retailers. To facilitate V2G services avoid congestion at CSs, two types of trips, i.e., mandatory optional are defined formulated. Also, EV drivers’ preferences added the model as cost/revenue threshold extra driving distance enhance practical aspects framework. An iterative process solve non-cooperative Stackelberg game by determining optimal routes CS for each EV, retailers, G2V prices. Extensive simulation studies carried out ecosystems multiple retailers CSs well numerous EVs based on real data from San Francisco, USA. results show that trips not only reduces cost PV curtailment 8.8-24.2% 26.4-28.5% average, respectively, in scenarios, but also mitigates during specific hours while respecting preferences. Moreover, revealed significant impact drivers' solutions stakeholders.