An Optimal Power Management Strategy Based on the Parking Time for Electric Vehicles Charging Station Powered by PV-Based DC Microgrid.

In the context of the energy transition and the imperative to reduce greenhouse gas emissions, promoting electric mobility has become a priority. Electric vehicles (EVs), primarily reliant on the power grid for battery charging, pose potential consequences if not carefully managed. To meet this challenge, the integration of EVs charging stations powered by photovoltaic panels (PVCS) appears to be a promising solution. This work contributes to understanding and improving the power management for a PV-powered DC microgrid (MG) dedicated to recharge EVs, enabling more efficient use of energy resources and better integration of PV charging infrastructure into the existing power grid. The objective is to investigate a two layers power management algorithm. The first layer is dedicated to managing the power flow in the MG respecting the physical constraints of the system. The second layer focuses on modulating the charging profile for the EVs. The charging profile is determined based on the EVs characteristics communicated by the users, such as parking time, charging mode, initial and desired departure state of charge. For this, several scenarios are presented and analyzed. Analysis of these scenarios enables to determine the benefits of parking time knowledge for optimizing the use of PV energy, to reduce dependence on the power grid, and illustrating the impact of charging mode on the participation rate of PV production.