The diffusion of Electric Vehicles (EV) fostered by the evolution of the power system towards the new concept of Smart Grid introduces several technological challenges related to the synergy among electricity-propelled vehicle fleets and the energy grid ecosystem. EVs promise to reduce carbon emissions by exploiting Renewable Energy Sources (RESes) for battery recharge, and could potentially serve as storage bank to flatten the fluctuations of power generation caused by the intermittent nature of RESes by relying on a load aggregator, which intelligently schedules the battery charge/discharge of a fleet of vehicles according to the users' requests and grid's needs. However, the introduction of such vehicle-to-grid (V2G) infrastructure rises also privacy concerns: plugging the vehicles in the recharging infrastructures may expose private information regarding the user's locations and travelling habits. Therefore, this paper proposes a privacy-preserving V2G infrastructure which does not disclose to the aggregator the current battery charge level, the amount of refilled energy, nor the time periods in which the vehicles are actually plugged in. The communication protocol relies on the Shamir Secret Sharing threshold cryptosystem. We evaluate the security properties of our solution and compare its performance to the optimal scheduling achievable by means of an Integer Linear Program (ILP) aimed at maximizing the ratio of the amount of charged/discharged energy to/from the EV's batteries to the grid power availability/request. This way, we quantify the reduction in the effectiveness of the scheduling strategy due to the preservation of data privacy.

In the next decades, Electric Vehicles (EVs) are expected to gain increasing popularity and huge penetration in the automotive mar- ket, thanks to their potentialities for close interaction with the Smart Grid ecosystem. Firstly, recharging EV's batteries with energy produced by renewables will allow for a consistent reduction of pollution due to the carbon emissions of traditional gasoline combustion; secondly, bat- teries could be exploited to store/inject energy from/to the grid in order to compensate the unpredictable uctuations caused by Renewable En- ergy Sources (RES). To this aim, a load aggregator is envisioned as a scheduling entity to plan the EVs' battery recharge/discharge according to the user's needs and the current power generation of the grid. The main drawback of the introduction of such load aggregator is a potential harm of users' privacy: gathering information about the EVs' recharge requests and plug/unplug events could make the scheduler able to infer the private travelling habits of the customers, thus exposing them to the risk of tracking attacks and to other privacy threats. To address this issue, this paper proposes a security infrastructure for privacy-friendly Vehicle-to-Grid (V2G) interactions, which enables the load aggregator to schedule the EV's battery charge/discharge without learning the current battery level, nor the the amount of charged/discharged energy, nor the time periods in which the EVs are available for recharge. Our proposed scheduling protocol is based on the Shamir Secret Sharing scheme. We provide a security analysis of the privacy guarantees provided by our framework and compare its performance to the optimal schedule that would be obtained if the aggregator had full knowledge of the charging- related information