Defending the power grid by segmenting the EV charging cyber infrastructure

TL;DR

This paper proposes a cyber infrastructure segmentation strategy for electric vehicle charging stations to protect the power grid from load-altering cyber-attacks, validated with real data and optimization methods.

Contribution

It introduces a novel optimization-based segmentation approach that minimizes segments while preventing grid overloads during cyber-attacks.

Findings

Segmentation can prevent overloads caused by cyber-attacks on charging stations.

Heuristic methods perform close to optimal solutions in large-scale scenarios.

Even segmentation schemes based on capacity are nearly as effective as optimized solutions.

Abstract

This paper examines defending the power grid against load-altering attacks using electric vehicle charging. It proposes to preventively segment the cyber infrastructure that charging station operators (CSOs) use to communicate with and control their charging stations, thereby limiting the impact of successful cyber-attacks. Using real German charging station data and a reconstructed transmission grid model, a threat analysis shows that without segmentation, the successful hack of just two CSOs can overload two transmission grid branches, exceeding the N-1 security margin and necessitating defense measures. A novel defense design problem is then formulated that minimizes the number of imposed segmentations while bounding the number of branch overloads under worst-case attacks. The resulting IP-MILP bi-level problem can be solved with an exact column and constraint generation algorithm and with heuristics for fast computation on large-scale instances. For the near-real-world Germany case, the applicability of the heuristics is demonstrated and validated under relevant load and dispatch scenarios. It is found that the simple scheme of segmenting CSOs evenly by their installed capacity leads to only 23% more segments compared to the heuristic optimization result, suggesting potential relevance as a regulatory measure.