Assessment of Quantitative Cyber-Physical Reliability of SCADA Systems in Autonomous Vehicle to Grid (V2G) Capable Smart Grids

• URL: http://arxiv.org/abs/2507.21154v1
• Date: Thu, 24 Jul 2025 06:57:10 GMT
• Title: Assessment of Quantitative Cyber-Physical Reliability of SCADA Systems in Autonomous Vehicle to Grid (V2G) Capable Smart Grids
• Authors: Md Abdul Gaffar,
• Abstract summary: The integration of electric vehicles (EVs) into power grids via Vehicle-to-Grid (V2G) system technology is increasing day by day.<n>V2G can increase grid reliability by providing distributed energy storage and ancillary services.<n>It has a scope that encompasses the cyber-physical attack surface of the national power grid, introducing new vulnerabilities in monitoring and supervisory control and data acquisition (SCADA) systems.<n>This paper investigates the maliciousness caused by Autonomous Vehicle to Grid (AV2G) communication infrastructures and assesses their impacts on SCADA system reliability.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The integration of electric vehicles (EVs) into power grids via Vehicle-to-Grid (V2G) system technology is increasing day by day, but these phenomena present both advantages and disadvantages. V2G can increase grid reliability by providing distributed energy storage and ancillary services. However, on the other hand, it has a scope that encompasses the cyber-physical attack surface of the national power grid, introducing new vulnerabilities in monitoring and supervisory control and data acquisition (SCADA) systems. This paper investigates the maliciousness caused by Autonomous Vehicle to Grid (AV2G) communication infrastructures and assesses their impacts on SCADA system reliability. This paper presents a quantitative reliability assessment using Bayesian attack graph combined with probabilistic capacity outage modeling based on IEEE RTS-79 system data. This work presents how AV2G-based attacks degrade system performance by using Monte Carlo simulations method, highlighting the need for cybersecurity-hardening strategies in smart grid design.

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