Bi-Objective Optimization of EV Charging in a Workplace Parking Lot

The dissemination of Electric Vehicles (EVs) is essential to decarbonizing the transportation sector. However, the uncoordinated charging of EVs can negatively interfere with the power grid. An adequate scheduling scheme is crucial for Charging Managers (CMs) to avert undesirable effects. This study aims to develop a bi-objective optimization model for the scheduling of EVs in Charging Stations (CS) in workplace Parking Lots (PL) addressing the EV users' preferences. Two bi-objective optimization models are proposed to address the economic and Quality-of-Service (QoS) dimensions by means of minimizing both cost and the deviation from desired State-of-Charge (SoC). Two perspectives to minimize this deviation are considered: minimizing the sum of deviations and minimizing the worst deviation (a fairness criterion based on a min-max approach). The Epsilon-constraint method is used to obtain a representation of the non-dominated solution set corresponding to the scheduling plan for each EV. This study further conducts a sensitivity analysis to investigate the influence of selling energy prices in Vehicle-to-Grid (V2G) mode. The findings indicate that the model aiming to minimize the charging cost and the sum of deviations is more sensitive to variations in selling energy prices, highlighting the impact of price variations in scheduling plans.