The adoption of sustainable transportation plays a crucial role in the energy transition and national environmental policies. A rapid and significant increase in electric vehicles (EVs) presents a challenge for the power system, which must be capable of supplying these new demands. However, electric vehicles also offer an opportunity for the power grid by providing services through the modulation of charging power throughout the day or, in some cases, even feeding power back into the grid. In this context, developing technologies that enable electric vehicles to act as tools for providing services to the power grid is of particular interest.

The research presented in this report aimed to optimize and verify the use of electric vehicles as a resource for grid flexibility. The first part of the document describes the development of a new management logic for a group of charging vehicles, based on stochastic optimization techniques. These techniques maximize the profitability of the services offered while accounting for system uncertainties. The problem was formulated to reflect the uncertainties inherent in the model as accurately as possible. The main uncertainties addressed include the initial energy of vehicles at rest, the duration of the stop, the arrival time of the vehicle at the charging station, and market outcome uncertainties. The developed stochastic optimizer was then tested with case studies involving a company fleet and a public parking lot, demonstrating that the stochastic approach effectively accounts for all uncertainties while ensuring the vehicles are charged within a desired range.

The second part of the document presents the charging tests conducted at RSE’s Distributed Generation Test Facility using the bidirectional charging stations in the lab. These tests allowed for the characterization of the entire infrastructure, which includes the previously discussed stochastic optimizer, the management software for the experimental microgrid, and Enel X’s cloud infrastructure. The tests confirmed that the charging stations could deliver the requested active power with negligible errors (less than 1.5 kW under the worst conditions) and an average implementation delay of 44 seconds. Additionally, it was verified that in Vehicle-to-Grid (V2G) applications, the charging stations could provide the requested service throughout the charging period, with an overall bidirectional charging efficiency of 85%.

Finally, the third part of the document illustrates the procedure and test setup developed to assess the impact of V2G charging on the lifespan of vehicle batteries. This testing procedure will be used in future activities to conduct lifespan tests on two vehicle battery modules, with one subjected to a V2G work cycle and the other to a traditional charging cycle.