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)servi...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.展开更多
基金jointly supported by the National Natural Science Foundation of China (No. 51377035)the China-UK NSFC/EPSRC EV project (No. 51361130153)
文摘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.