Angle Modulated Particle Swarm Optimization Based Defensive Islanding of Large Scale Power Systems

Abstract

Power system defensive islanding is an efficient way to avoid catastrophic wide area blackouts, such as the 2003 North American blackout. Finding defensive islands of large scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal solution, if it exists, within reasonable time using analytical methods. This paper proposes utilizing the computational efficiency property of an angle modulated particle swarm optimization to find some efficient islanding solutions for large scale power systems. The solutions are referred to as optimal according to a fitness function considering the real power balance between generations and loads in islands, the relative importance of customers, and the desired number of islands. The algorithm can also provide necessary load shedding information. Furthermore, the algorithm can provide a number of candidate solutions for the check of transmission system capacity constraint. Simulations with power systems of different scales demonstrate the accuracy and effectiveness of the proposed algorithm.