Optimal Dynamic Load Altering Attack on Power Grids via Electrical Vehicle Charging Stations

The recently drastically growing electrical vehicles (EV) size has become a novel vulnerability for power grid due to their high charging power consumption. In this paper, a novel type of dynamic load altering attack threat leveraging EV charging stations has been identified to disrupt the frequency of national grid. The attack is designed utilizing optimal control, with the aim of finding the minimum attacking load to trigger underfrequency protection. By taking over a reasonable number of vehicles’ charging schedules, the attacker can successfully trip under-frequency protection relays, potentially causing a power grid blackout. The novel threat is evaluated by computational modeling on the 39 bus infrastructure of IEEE.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/cars61786.2024.10778813
Citations
1
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.33
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article

Optimal Dynamic Load Altering Attack on Power Grids via Electrical Vehicle Charging Stations

Md Imtiaz Faruk, Zejian Zhou, Nishad Tasnim
1 citations
Smart Grid Security and Resilience
0.33
article

Optimal Dynamic Load Altering Attack on Power Grids via Electrical Vehicle Charging Stations

Md Imtiaz Faruk, Zejian Zhou, Nishad Tasnim
article en
1 citations

Abstract

The recently drastically growing electrical vehicles (EV) size has become a novel vulnerability for power grid due to their high charging power consumption. In this paper, a novel type of dynamic load altering attack threat leveraging EV charging stations has been identified to disrupt the frequency of national grid. The attack is designed utilizing optimal control, with the aim of finding the minimum attacking load to trigger underfrequency protection. By taking over a reasonable number of vehicles’ charging schedules, the attacker can successfully trip under-frequency protection relays, potentially causing a power grid blackout. The novel threat is evaluated by computational modeling on the 39 bus infrastructure of IEEE.

University of Wyoming (US)
Affordable and clean energy
Openalex Percentile: Top 38%
Smart Grid Security and Resilience
0.33
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