A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies

This study proposes a multi-objective optimization model to determine the optimal charging infrastructure for transition plug-in electric vehicles (PEVs) at workplaces. The developed considers all cost aspects of workplace station, i.e., daily levelized vehicle supply equipment (EVSE) cost, PEV energy and demand charges. These single-objective functions are aggregated in framework find Pareto solutions. Smart strategies with interrupted uninterrupted power profiles proposed maximize use EVSE units. behavior is based on collected data. tested various scheduling policies investigate their impact behaviors types from different perspectives. Finally, sensitivity analysis performed assess impacts battery sizes onboard charger ratings behavior. It shown that can achieve up 7.8% 14.6% savings as compared models current practice, respectively. unit found be more sensitive than strategies. also flexibility ratio policy gives best lowest most efficient grid assets. • A infrastructure. configurations investigated. on-board levels probed. analyzed. performance