Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation

This paper presents mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation in an extreme fast charging station (XFCS) reduce the annualized total cost. The proposed model characterizes typical year with eight representative scenarios obtains management BESS operation exploit arbitrage each scenario. Contrasting extant literature, this proposes constant power voltage (CPCV) based improved probabilistic approach XFCS demand weekdays weekends. also accounts monthly annual charges on realistic utility tariffs. Furthermore, life degradation is considered ensure no replacement needed during planning horizon. Different from offers pragmatic MILP tally charge/discharge cycles using cumulative concept. McCormick relaxations Big-M method are utilized relax bi-linear terms operational constraints. Finally, robust optimization-based leveraged account uncertainties electricity price, generation, demand. Case studies were performed signify efficacy of formulations.