Chance-Constrained Dispatch of Suburban Railway Smart Grids Considering EVs Charging Behaviors

Integration of park and ride (P&R) systems with electrified railways has been demonstrated to effectively reduce traffic congestion and the usage of private vehicles. To reduce operation costs and carbon emissions, this paper investigates suburban railway smart grids (SRSGs) incorporated electric vehicle (EV) charging management and railway energy dispatch. A stochastic optimization model is established, in which EV charging power flow scheduling and the charging/discharging strategies of ultracapacitors (UC) are scheduled. Meanwhile, the uncertainties of EV charging behaviours, such as arrival and departure times and initial states of charge, are captured by chance-constrained programming. The effectiveness of the power flow dispatch approach is demonstrated by the numerical simulation, it is shown that the proposed stochastic dispatch approach can reduce the overall cost by up to 10%.