Development of Impact Indices for Performing Charging of a Large EV Population

Nodal voltages and feeder currents are acquired by running load flows for electric vehicle (EV) charging purposes. The impact of the charging is analyzed by either visually inspecting the voltages and currents or calculating appropriate impact indices. Optimal charging, on the other hand, is performed by incorporating the voltages and currents in charging strategies. Though the impact indices are frequently used for assessing the impact, their usage for optimizing charging has been minimal. Therefore, this paper develops probabilistic impact indices for nodal voltage violations and feeder overloading, which can be applied not only for investigating the impact but also for optimizing charging. Also, aggregated EV load demand of a large EV population is modeled by using a new combined state of charge (SOC)-based charging strategy in time series, for assessing the applicability of the developed impact indices for practical purposes. The combined SOC dynamically integrates arrival and departure of EV and delivered energy. The numerical results show that the proposed impact indices in conjunction with the SOC-based charging have numerous advantages over the conventional charging strategies aided by the load flows.