Optimization based graph theoretic approach for corrective control strategies to mitigate overloads

This paper presents a novel Optimization based corrective strategy based on graph theory to mitigate overloads during contingencies. Generator rescheduling and/or load shedding is performed locally, to restore the system from abnormal to normal operating state. The directed acyclic graph (DAG) technique is used to identify the participating generators and load buses for corrective control action with respect to a contingency. Particle swarm optimization (PSO) is used to compute the optimal adjustments of generation and loads with security constraints such as line flows and bus voltage limits. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 14- and 30-bus systems. The result shows that the proposed approach is computationally fast, reliable and efficient, in restoring the system to normal state after a contingency with minimal control actions. Copyright © 2009 John Wiley & Sons, Ltd.