Secure Integration of Electric Vehicles with the Power Grid

TL;DR

This paper introduces a novel cyber-physical anomaly detection system for securely integrating electric vehicles with the power grid, combining cyber message analysis, power data monitoring, and timing checks to prevent intrusions.

Contribution

It presents the first integrated anomaly detection engine that monitors EV charging protocols, cyber network activity, and physical power data simultaneously for enhanced grid security.

Findings

Effective detection of anomalies in EV-grid systems

Real-time monitoring of cyber and physical data

Enhanced security for V2G systems

Abstract

This paper focuses on the secure integration of distributed energy resources (DERs), especially pluggable electric vehicles (EVs), with the power grid. We consider the vehicle-to-grid (V2G) system where EVs are connected to the power grid through an aggregator. In this paper, we propose a novel Cyber-Physical Anomaly Detection Engine that monitors system behavior and detects anomalies almost instantaneously. This detection engine ensures that the critical power grid component (viz.,aggregator)remains secure by monitoring(a)cyber messages for various state changes and data constraints along with (b)power data on the V2G cyber network using power measurements from sensors on the physical/power distribution network. Since the V2G system is time-sensitive, the anomaly detection engine also monitors the timing requirements of the protocol messages to enhance the safety of the aggregator. To the best of our knowledge, this is the first piece of work that combines(a)the EV charging/discharging protocols, the(b)cyber network and(c)power measurements from physical network to detect intrusions in the EV to power grid system.