Privacy-preserving scheme for unbalanced PSI-based charging demand matching in V2G networks

With the increasing integration of electric vehicles in smart grids, V2G (vehicle-to-grid) technology is becoming a key factor in improving energy efficiency and implementing demand-side management. Promoting the widespread application of V2G technology is an important step in promoting the development of society towards intelligence, environmental friendliness and low carbon, and represents an inevitable trend of global progress in the energy and transportation industries. However, there is a risk of leakage of a large amount of users’ personal information during V2G implementation, such as driving records, charging data and location information, etc. In this paper, we propose an unbalanced PSI-based charging demand matching privacy-preserving scheme in V2G networks, which aims to achieve a balance between user privacy protection and grid optimization scheduling, and allows EV users to share the necessary charging demand information with the grid operator without disclosing their personal driving and charging data. This scheme uses the unbalanced PSI technique, which takes EV users with smaller aggregates as receivers and grid servers with larger aggregates as senders, to intelligently recommend optimal charging strategies for users without disclosing their privacy information. Meanwhile, the combination of full homomorphic encryption greatly improves the efficiency of PSI solving; Finally, the feasibility of the scheme is proved through security.