基于蝙蝠算法的PSS参数优化研究

Research on Optimization of PSS Parameters Based on Bat Algorithm

为了抑制故障发生时,在多机电力系统中的低频振荡,文中提出了一种协调优化(Power System Stabilizer,PSS电力系统稳定器)参数的IBA算法(Improved Bat Algorithm,改进的蝙蝠算法)。首先采用Prony算法辨识系统低频振荡的机电模式,并采用IBA算法将PSS的设计过程转化为一组参数进行寻优,最后通过算例证明了该算法的合理性。结果表明:IBA算法可以有效的适用于多种运行方式下的阻尼控制器参数优化,且具有良好的鲁棒性,可以有效地抑制低频振荡。此外,通过比较多机电力系统基于IBA算法、粒子群优化算法(Particle Swarm Optimization,PSO)算法和基本BA算法的PSS参数优化结果,可知基于IBA算法设计的PSS在抑制低频振荡方面具有最佳的效果,且该算法克服了基本BA算法容易陷入局部最优、后期收敛速度慢等缺点。

In order to suppress the low frequency oscillation in multi machine power systems,this paper presents a kind of improved bat algorithm (IBA)which is used to coordinate and optimize the parameters of PSS (power system stabilizer).Firstly,the Prony algorithm is used to identify the electromechanical modes of low frequency oscillation,and the IBA algorithm is used to transform the design process of PSS into a set of parameters to find the optimal parameters.Finally,the rationality of the algorithm is verified by an example, results show that the IBA algorithm can be effectively applied to parameter optimization of the damping controller under various operating conditions,and it has good robustness,and can effectively suppress low frequency oscillation.In addition,by comparing the multi machine power system based on the IBA algorithm, the PSO algorithm and the basic BA algorithm of the PSS parameters optimization results,it can be known that the PSS based on the IBA algorithm has the best effect in suppressing low frequency oscillation,and this algorithm overcomes the shortcomings of the basic BA algorithm,such as easy to fall into local optimum and slow convergence etc.