Cyber Security of Plug-in Electric Vehicles in Smart Grids: Application of Intrusion Detection Methods

Abstract

With emerging penetration of Plug-in Electric Vehicles (PEVs) into smart grids, system operators face new challenges regarding the system security. The security involves all parties in the energy system, because PEVs are not only considered as loads, but also as demand response or distributed energy resources, with bidirectional power flow into the distribution network. Furthermore, due to the random time, amount and location of the PEVs utilization, their behavior is inherently uncertain. In this context, monitoring and control of PEVs utilization necessitate the real-time data communication with control centers throughout the smart grid. The security and reliability of power system will be dependent on how the PEVs data are collected and managed. Hence, assuring data confidentiality, integrity and availability are significant parts of PEV-integrated cyber-physical systems (CPS). This chapter aims at exploring the cyber security issues of PEVs in the smart grid and review some of the state-of-the-art analysis methods to detect the cyber-attacks. We study the model-based and signal-based intrusion detection methods to detect any anomalies, followed by a specific application to PEVs false data injection in the smart grid. The chi-square test and discrete wavelet transform (DWT) are used for anomaly detection.