Scalable Real-Time Electric Vehicles Charging With Discrete Charging Rates

Large penetration of electric vehicles (EVs) can have a negative impact on the power grid, e.g., increased peak load and losses, that can be largely mitigated using coordinated charging strategies. In addition to shifting the charging process to the night valley when the electricity price is lower, this paper explicitly considers the EV owner convenience that can be mainly characterized by a desired state of charge at the departure time. To this end, the EV charging procedure is defined as an uninterruptible process that happens at a given discrete charging rate and the coordinated charging is formulated as a scheduling problem. The scalable real-time greedy (S-RTG) algorithm is proposed to schedule a large population of EVs in a decentralized fashion, explicitly considering the EV owner criteria. Unlike the majority of existing approaches, the S-RTG algorithm does not rely on iterative procedures and does not require heavy computations, broadcast messages, or extensive bi-directional communications. Instead, the proposed algorithm schedules one EV at a time with simple computations, only once (i.e., at the time the EV connects to the grid), and only requires low-speed communication capability making it suitable for real-time implementation. Numerical simulations with significant EVs penetration and comparative analysis with scheduling policies demonstrate the effectiveness of the proposed algorithm.