We have constructed a mathematical model for electric vehicle charging and discharging scheduling with the optimization objectives of minimizing the charging and discharging costs of electric vehicles and maximizing the revenue of Charging piles.
How to plan the capacity of charging piles?
The capacity planning of charging piles is restricted by many factors. It not only needs to consider the construction investment cost, but also takes into account the charging demand, vehicle flow, charging price and the impact on the safe operation of the power grid (Bai & Feng, 2022; Campaa et al., 2021).
Can fast charging piles improve the energy consumption of EVs?
According to the taxi trajectory and the photovoltaic output characteristics in the power grid, Reference Shan et al. (2019) realized the matching of charging load and photovoltaic power output by planning fast charging piles, which promoted the consumption of new energy while satisfying the charging demand of EVs.
How do fast/slow charging piles help EVs in a multi-microgrid?
Considering the power interdependence among the microgrids in commercial, office, and residential areas, the fast/slow charging piles are reasonably arranged to guide the EVs to arrange the charging time, charging location, and charging mode reasonably to realize the cross-regional consumption of renewable energy among multi-microgrids.
How important is EV charging infrastructure?
A well-developed EV charging infrastructure plays a key role in facilitating the widespread adoption of EVs 8, 9. Approximately 26% of EV charging stations worldwide are situated within parking lots 10.
It develops an optimal configuration model for charging stations across multiple microgrids and implements differentiated electricity pricing in various zones to promote orderly charging. The lower layer aims to minimize EVs' charging costs.
Efficient and reliable EV charging strategies enhance power quality and stability 30, but many fail to incorporate real-time energy adjustments or prioritize user preferences, both of which are critical for scalable applications in CPLs.