Abstract
In the last few years, there has been an exponential increase in the penetration of electric vehicles (EVs) due to their eco-friendly nature and ability to support bidirectional energy exchanges with the power cyber-physical system. However, the existing research only proposes energy management in terms of vehicle-to-grid (V2G) support using fleets of EVs, which lacks research on EV attacks. Motivated by these facts, this paper first introduces a new data integrity attack strategy for a consistent energy management algorithm which considers electric vehicles as energy storage. In particular, we consider EV aggregators as energy storage with source-charge bidirectional characteristics. The attacker carefully constructs false information to manipulate aggregators to participate in scheduling and obtaining additional benefits on the premise of meeting the constraints of microgrid and various devices by attacking the consistent algorithm. Then, we propose a disturbance rejection control strategy combining privacy protection protocols and an isolation mechanism. We analyze the effectiveness of the proposed encryption mechanism and verify the feasibility of the isolation control algorithm by simulation and comparison.
Highlights
Facing the pressure of environmental protection and the shortage of fossil energy, electric vehicles have developed rapidly in recent years
Refs. [2,3,4,5] use electric vehicles as an aggregator [6] to participate in grid peak shaving, time-varying delay frequency modulation, charging planning, and optimal scheduling based on distributed location marginal pricing
We propose a distributed energy management model for distribution networks that considers the bidirectionality of the source and load of electric vehicles, and solve it based on a consensus algorithm
Summary
Facing the pressure of environmental protection and the shortage of fossil energy, electric vehicles have developed rapidly in recent years. Their electricity consumption behavior has caused certain changes in load, such as load volatility, increased randomness, and increased load peak–valley difference. [2,3,4,5] use electric vehicles as an aggregator [6] to participate in grid peak shaving, time-varying delay frequency modulation, charging planning, and optimal scheduling based on distributed location marginal pricing. [7] proposed an “aggregator-based hierarchical control mechanism” for secondary frequency regulation (SFR) using a fleet of EVs. EVs’ scheduling problem has been formulated to provide optimal SFR, while satisfying EVs’ energy demands under battery degradation constraints. There is no research from the perspective of attacking electric vehicle aggregators
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