Day-ahead optimal charging/discharging scheduling for electric vehicles in microgrids

Abstract Microgrid as an important part of smart grid comprises distributed generators (DGs), adjustable loads, energy storage systems (ESSs) and control units. It can be operated either connected with the external system or islanded with the support of ESSs. While the daily output of DGs strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the unbalance between the daily load curve and generation curve. In this paper, a statistic model is presented to describe daily EV charging/discharging behaviors considering the randomness of the initial state of charge (SOC) of EV batteries. The optimization problem is proposed to obtain the economic operation for the microgrid based on this model. In day-ahead scheduling, with the estimated power generation and load demand, the optimal charging/discharging scheduling of EVs during 24 h is achieved by serial quadratic programming. With the optimal charging/discharging scheduling of EVs, the daily load curve can better track the generation curve. The network loss in grid-connected operation mode and required ESS capacity in islanded operation mode are both decreased.