Publication

Abstract : The smart grid can be realized with the use of new communication technologies and control strategies that fortify accuracy, decreased power costs and provision for supplying real-time customer services. Malicious entities can disrupt smart grid operations by exploiting the cyber susceptibilities created through these technological enhancements. Electric vehicle charging stations are not a special case for these sorts of noxious assaults. Literature have suggested the application of charging station to support the various ancillary support to the grid such as frequency restoration using V2G services. To enable the same, the charging station needs to communicate with the Distribution System Operator in real time using communication facilities and this communication link can be targeted by the attacker. If the charging station receives malicious information about decreased cost or malicious control signals during the grid emergency conditions, this can further worsen the grid stability as the power drawn by the charging station can be in the order of a few megawatts. In this work, an ANN-based Intelligent Controller is employed for anomaly information identification in charging station for supporting the grid in critical situations or cyberattacks. ANN-based control system is designed to select the mode of operation of the charging station based on the system’s local measurements and information from Aggregator or DSO. By using this smart cyber resilient controller, EVSE can work autonomously with least or no communication using the droop control scheme when anomaly information is identified and thereby contributing towards smart grid resilience. The proposed idea is simulated and verified in MATLAB/Simulink.