Slow Coherency and Angle Modulated Particle Swarm Optimization Based Islanding of Large Scale Power Systems

Abstract

Power system islanding is an efficient way to avoid catastrophic wide area blackouts, such as the 2003 North American blackout. Islanding of large-scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal solution within reasonable time using analytical methods. This paper presents a new method to solve this problem. In the proposed method, angle modulated particle swarm optimization (AMPSO) is utilized to find a number of efficient islanding solutions for large-scale power systems due to its computational efficiency. First, desired generators groups is obtained using slow coherency algorithm. AMPSO is then used to optimize a fitness function defined according to both generation/load balance and similarity to the desired generator grouping. In doing so, the resulted islanding solutions provide good static and dynamic stability. Simulations for power systems of different scales demonstrate the effectiveness of the proposed algorithm.