细菌觅食算法混合PSO的阻尼控制器参数优化

Optimization of Damping Controller Parameters Through Bacterial Foraging Algorithm and PSO

为了在多机电力系统中设计最优电力系统稳定器从而阻尼低频振荡,提出了一种基于细菌觅食算法和粒子群优化的混合方法。首先,给出了优化阻尼因数和阻尼比的基于特征值的目标函数;然后,利用PSO引入细菌的变异算子;最后,运用BSO搜索和迭代得到最优控制器参数。仿真结果表明,相比原始BFOA算法和PSO算法,算法在提高电力系统稳定性方面取得了更好的性能。

In order to design an optimal power system stabilizer in multi-machine power systems to damp low-frequency oscillation, this paper presents a hybrid approach based on bacterial foraging algorithm （ BFOA） and particle swarm optimization. First, it gives the feature based objective function optimizing the damping factor and the damping ratio. Then, PSO is used to bring in bacterial mutation operators. Finally, BSO and iteration is used to search the optimal controller parameters. Experimental results show that the proposed algorithm has better performance than original BFOA and PSO algorithm in improving power system stability.