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The repercussion of increased electric vehicle (EV) charging demand is notable at the distribution grid especially during the cold morning, while users tend to precondition their vehicles before leaving their premises. Moreover, due to the price declination, a tendency of installing level 2 chargers in residential premises is anticipated, which should stimulate the appearance of a new peak to the residential load profile. Hence, multiple scenarios of preconditioning are simulated, and the corresponding network’s quality metrics (e.g., voltage level and power losses) are assessed to analyze the impact. And a remarkable consequence is observed. As a consequence, to mitigate the consequences and manage the new peak load, the optimal reconfiguration of network is implemented, and unfortunately, with a larger number of EVs, this technique fails to attain the minimum voltage level. Therefore, leveraging this high number of EVs, instead of relying on the network reconfiguration, power is assumed to be injected from idle EVs through vehicle-to-grid (V2G) energy transmission. An integer linear program is formed to schedule a set of EVs in participating in V2G, and the outcome indicates that V2G alone could not compensate for the disturbance in the network. Accordingly, a hybrid method of V2G and reconfiguration is proposed and evaluated to assist the network in handling the new peak load, and this hybrid solution reduces power losses in the network by 50% on average and maintains the voltage level above the operational threshold of 0.95 p.u. [ABSTRACT FROM AUTHOR]

The drive for efficient, reliable, green, and connected smart cities has promoted the use of electric vehicles (EVs) as the main future means of transportation. This resulted in a breakthrough in the anticipated number of adopted EVs by the year 2020, and consequently an urge for an available and trustworthy EV charging infrastructure. The diversity of the involved players, the used technologies, the bulk data exchange, and the widespread nature of the charging network give rise to security concerns in the form of message tampering, spoofing, or delaying among others to disconcert the charging service along with the underlying power layer. Furthermore, confidentiality and privacy of user information (i.e. identity, location, payment information, etc.) is another major concern associated with the deployment and use of the charging infrastructure. Thus, there is a need to identify and classify such concerns, and devise suitable solutions for a secure charging infrastructure. In this paper, we present a security assessment of the EV charging infrastructure. We highlight and categorize cyber threats targeting different players in a charging system, along with the security solutions presented in the literature. Finally, we present a gap analysis and insights into future research directions for EV charging system security. [ABSTRACT FROM AUTHOR]