Particle Swarm Optimization based Defensive Islanding of Large Scale Power System

Defensive islanding is an efficient way to avoid catastrophic failures and wide area blackouts. Power system splitting especially for large scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal solution (if one exists) for large scale power system in real time. This paper proposes to utilize the computational efficiency property of binary particle swarm optimization (BPSO) to find some efficient splitting solutions in limited timeframe. The solutions are optimized based on a cost function considering the balance between real power generation and consumption, the relative importance of customers, the capacities of distribution and transmission systems, and possibility of region to be impacted, etc. The solutions not only provide the lines to cut but also the corresponding load shedding information in each island. Simulations with large scale power system demonstrate the effectiveness of the proposed algorithm.