Detection and Mitigation of Cyberattacks on Volt-Var Control

Abstract

Cyberattacks are becoming more frequent, and attackers can use different mechanisms, such as denial of service (DoS) and false data injection (FDI). Furthermore, multiple attack types can be launched simultaneously, known as hybrid attacks, to cause more damage. Volt-Var control algorithms are widely used in the distribution system to maintain the voltage within a nominal range. This work uses an artificial neural network (ANN)-based method to detect and mitigate hybrid cyberattacks on the Volt-VAr control algorithm.