Fault reconstruction of ship ring power network based on improved particle swarm optimization algorithm

In order to analyze and solve the problem of reconfiguration of power system after fault occurs during ship sailing, a fault self-healing model of ship ring power network is established, which takes load power, switch action and generator efficiency as optimization objectives, and an improved binary particle swarm optimization algorithm is proposed. Aiming at the disadvantages of traditional binary particle swarm optimization, chaotic mapping is added. Secondly, the inertia weight is changed dynamically according to the number of iterations, and the contraction factor is improved by sinusoidal function, which makes the contraction factor decay slowly in the early stage of the algorithm and accelerate the decay speed in the later stage. Finally, the particle position is discretized to make it suitable for the fault reconstruction of ship power system. In the case of generator fault and load fault, the improved algorithm has better load recovery and switching times than the traditional algorithm, and has some advantages in iteration times and convergence speed. It shows that the proposed method can obtain a better reconstruction scheme, overcome the problems of poor population diversity and local optimality of the traditional binary particle swarm optimization algorithm, and ensure the safe operation of the ship better.