Collaborative multi-aggregator electric vehicle charge scheduling with PV-assisted charging stations under variable solar profiles

Abstract

Electric vehicles (EVs) are on the path to becoming a solution to the emissions released by the internal combustion engine vehicles that are on the road. EV charging management integration requires a smart grid platform that allows for communication and control between the aggregator, consumer and grid. This study presents an operational strategy for PV-assisted charging stations (PVCSs) that allows the EV to be charged primarily by PV energy, followed by the EV station's battery storage (BS) and the grid. Multi-Aggregator collaborative scheduling is considered that includes a monetary penalty on the aggregator for any unscheduled EVs. The impact of the PVCS is compared to the case with no PV/BS is included. A variation in the PV profile is included in the evaluation to assess its impact on total profits. Profit results are compared in cases of minimum, average and maximum PV energy output. The results indicate that the inclusion of penalties due to unscheduled EVs resulted in lowered profits. Further, the profits experienced an increase as the number of EVs scheduled through PV/BS increased, implying that a lesser percentage of EVs are scheduled by the grid when a greater amount of PV and battery energy are available.

Keywords

• photovoltaic power systems
• power grids
• electric vehicle charging
• solar power stations
• battery storage plants
• power generation scheduling
• profitability
• power generation economics
• pv-assisted charging stations
• variable solar profiles
• internal combustion engine vehicles
• ev charging management integration
• smart grid platform
• pv energy
• ev station
• battery energy
• collaborative multiaggregator electric vehicle charge scheduling
• pvcs
• bs
• battery storage