Nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources. If an off-grid nanogrid can supply fullycharged batteries to a battery swapping station(BSS)serving regional electric vehicles(EVs), it will help establish a structure for implementing renewable-energyto-vehicle systems. A capacity planning problem is formulated to determine the optimal sizing of photovoltaic(PV) generation and battery-based energy storage system(BESS) in such a nanogrid. The problem is formulated based on the mixed-integer linear programming(MILP)and then solved by a robust optimization approach. Flexible uncertainty sets are employed to adjust the conservativeness of the robust optimization, and Monte Carlo simulations are carried out to compare the performance of the solutions. Case studies demonstrate the merits of the proposed applications and verify the approach.
The usage of each private electric vehicle(PrEV)is a repeating behavior process composed by driving,parking,discharging and charging,in which PrEV shows obvious procedural characteristics.To analyze the procedural characteristics,this paper proposes a procedural simulation method.The method aggregates the behavior process regularity of the PrEV cluster to model the cluster’s charging load.Firstly,the basic behavior process of each PrEV is constructed by referring the statistical datasets of the traditional private non-electric vehicles.Secondly,all the basic processes are set as a simulation starting point,and they are dynamically reconstructed by several constraints.The simulation continues until the steady state of charge(SOC)distribution and behavior regularity of the PrEV cluster are obtained.Lastly,based on the obtained SOC and behavior regularity information,the PrEV cluster’s behavior processes are simulated again to make the aggregating charging load model available.Examples for several scenarios show that the proposed method can improve the reliability of modeling by grasping the PrEV cluster’s procedural characteristics.