Local Power Grids at Risk – An Experimental and Simulation-based Analysis of Attacks on Vehicle-To-Grid Communication


연구 분야: Infrastructure



학회: ACSAC '22: Proceedings of the 38th Annual Computer Security Applications Conference


초록

With Electric Vehicles (EVs) becoming more prevalent, their battery recharge creates significant loads on power grids. Especially in local grids with a high share of households that own an EV, this additional energy demand can stress existing power distribution systems that were not designed for this kind of loads. The unexpected peak consumption may reduce service quality, damage sensitive equipment, cause power failures and even local blackouts. To mitigate this risk, grid components must be either significantly upgraded to match the increased demand, or the demand must be managed to avoid critical situations. Vehicle-to-Grid (V2G) technology is a major emerging trend for enabling load management in connection with EV charging. A key component of V2G is the ISO 15118 protocol allowing to set grid-friendly charging schedules for EVs. This standard is further supported by backend protocols like OCPP to permit corrective actions by a network operator. In this paper, we analyze conditions under which V2G insecurity can lead to grid collapse. We use quantitative analysis and dynamic simulations of a typical European suburban grid to determine the scope and impact of EV charging manipulation. We then review shortcomings of existing V2G protocols, analyze attack strategies able to cause overloads and validate known attacks based on experiments with off-the-shelf products. While load management is vital to future cost-effective grid operation, we show that it is also critical to consider the impact of known and unknown attacks, and consider possible mitigations and fallback positions.


Author Profile
Maria Zhdanova

Fraunhofer SIT Germany

Germany
Author Profile
Julian Urbansky

Fraunhofer UMSICHT Germany

Germany
Author Profile
Anne Hagemeier

Fraunhofer UMSICHT Germany

Germany

📄 논문 정보

발행 연도 2022년
인용수 11
출판 국가 Germany
사이트 ACM
좋아요 수 0

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