The Smart Grid (SG) is an emerging modernized electrical power system with advanced monitoring and control mechanism, and improved faulttolerance. The SG converges traditional power grid with a bidirectional communication and information system into the same infrastructure. Electric Vehicles (EVs), with their energy storage capacity and bidirectional communication capability, are envisioned to be an essential component of the SG. EVs can play the role of distributed energy resources by storing energy in off-peak hours and providing energy to the grid during peak hours or system contingencies. The energy stored by an EV is equivalent to the average energy drawn by multiple residential houses. As a result, simultaneous charging by a large number of EVs can create sudden energy imbalance in the grid. The mismatch between the energy generation and demand can create cascading faults resulting in load shedding. To prevent such situation, EVs are required to pre-schedule charging events at a Charging Station (CS). To efficiently manage a scheduled event, an EV is required to transmit information such as a valid ID, state-of-charge, distance from a CS, location, speed, etc. However, the data transmitted by an EV can be used to reveal information such as the movement of the vehicle, visits to a hospital,
time to arrive at office, etc. The transmitted information can be used to create profiles of the owners of the EVs, breaching their location privacy.
In the existing literature, it is recommended to use pseudonyms for different transactions by an EV to achieve location privacy. The majority of the works in the literature are based on anonymous authentication mechanism, where missing a charging event by an EV is considered as malicious and the corresponding EV is penalized (e.g., blacklisted). However, missing a charging event may happen due to many valid reasons and flexibility of scheduling can encourage consumer participation. On the other hand, missing charging events results in monetary loss to the CSs. In this thesis, an authentication method is developed to provide anonymity to EVs. The proposed method also addresses the cost-effectiveness of flexibility in charging events for the EVs and the CSs. A network setup that sub-divides
a regional area into smaller zones to achieve better privacy, is proposed. A MATLAB simulation is designed to demonstrate the Degree of Anonymity (DoA) achieved in different stages of the proposed method and the optimal number of missed charging events. Additionally, a method to determine sub-division of zones from the simulation results, is studied.
Computer Engineering (MS)
Department, Program, or Center
Computer Engineering (KGCOE)
Afrin, Sabrina, "A Privacy-Preserving Method with Flexible Charging Schedules for Electric Vehicles in the Smart Grid" (2017). Thesis. Rochester Institute of Technology. Accessed from
RIT – Main Campus