A Game-Theoretic Framework for Controlled Islanding in the Presence of Adversaries

TL;DR

This paper introduces a game-theoretic framework for controlled islanding in power systems to mitigate cascading failures under adversarial attacks, optimizing strategies for both grid operators and malicious adversaries.

Contribution

It formulates a novel game-theoretic model with a double oracle algorithm, enabling the computation of optimal islanding and attack strategies considering adversarial responses.

Findings

Proposed approach outperforms baseline in 44% of cases.

Achieves approximately 12.27 MW reduction in power flow disruption on average.

Best responses formulated as mixed integer linear programs and submodular maximization.

Abstract

Controlled islanding effectively mitigates cascading failures by partitioning the power system into a set of disjoint islands. In this paper, we study the controlled islanding problem of a power system under disturbances introduced by a malicious adversary. We formulate the interaction between the grid operator and adversary using a game-theoretic framework. The grid operator first computes a controlled islanding strategy, along with the power generation for the post-islanding system to guarantee stability. The adversary observes the strategies of the grid operator. The adversary then identifies critical substations of the power system to compromise and trips the transmission lines that are connected with compromised substations. For our game formulation, we propose a double oracle algorithm based approach that solves the best response for each player. We show that the best responses for the grid operator and adversary can be formulated as mixed integer linear programs. In addition, the best response of the adversary is equivalent to a submodular maximization problem under a cardinality constraint, which can be approximated up to a $(1-\frac{1}{e})$ optimality bound in polynomial time. We compare the proposed approach with a baseline where the grid operator computes an islanding strategy by minimizing the power flow disruption without considering the possible response from the adversary. We evaluate both approaches using IEEE 9-bus, 14-bus, 30-bus, 39-bus, 57-bus, and 118-bus power system case study data. Our proposed approach achieves better performance than the baseline in about $44\%$ of test cases, and on average it incurs about 12.27 MW less power flow disruption.