Optimal charging strategy for electric trucks with vehicle-to-grid at a wind-powered electric vehicle charging hub

The transportation sector is a major contributor to greenhouse gas emissions. To address this, the European Union is promoting the integration of Electric Vehicle (EV) charging infrastructures with Renewable Energy Sources (RESs). The intermittency of RESs can be mitigated through the use of Battery Energy Storage Systems (BESSs) and advanced EV charging strategies such as Vehicle-to-Grid (V2G), which require effective energy management. Accurate implementation of RES inverter capability curves is essential to minimize discrepancies between theoretical models and real-world performance. This study presents an Energy Management System (EMS) based on a Mixed Integer Linear Programming (MILP) model to optimize overnight charging of electric trucks at an Electric Vehicle Charging Hub (EVCH) powered by RESs. The EMS is developed in Matlab/Yalmip and solved using Gurobi. The model is applied to a real EVCH connected to a large-scale wind farm in Liguria, Italy, with integration of Photovoltaic (PV) and BESS units. Validation is performed through comparison with HOMER Grid simulations. Several sensitivity analyses are conducted, varying RES availability, truck presence, and electricity prices, to assess EVCH performance. Results show that V2G enables a 13.3 % cost reduction compared to constant-power charging. If the BESS is out of service, the increase in facility net costs is limited to 3.6 %. However, if trucks are available during the day, the V2G benefit is nullified due to overlap with RES production peaks. Conversely, higher electricity prices lead to a 6.7 % increase in the V2G contribution.