基于改进粒子群算法的PSS与TCSC控制器参数优化  

Parameter Optimization of PSS and TCSC Damping Controller Using Modified Particle Swarm Optimization Algorithm

作　　者：宁琳[1] 谭建成[1] 梁志坚[1] 秦砺寒[1] 

机构地区：[1]广西大学电气工程学院,广西南宁530004

出　　处：《现代电力》2008年第2期18-23,共6页Modern Electric Power

摘　　要：电力系统中同时装有单独设计的电力系统稳定器(PSS)和可控串联补偿装置(TCSC)时,两者之间可能产生一定的交互影响,导致阻尼低频振荡的效果不佳。针对这一问题,采用改进粒子群算法(MPSO)对PSS和TCSC的控制器进行协调设计,此方法在PSO算法的基础上,通过改变惯性权重对其进行改进,保持了群体搜索的多样性。通过收敛性分析证明,此方法能收敛于全局最优。在IEEE-4机11节点的系统上进行了测试。时域仿真与特征值分析表明,该算法能有效地将系统特征根移到复平面目标函数限定的区域内,很好地抑制低频振荡。对不同优化方法的收敛性及计算时间进行了比对,结果表明改进粒子群算法的性能优于常规遗传算法以及模拟退火算法。When power system stabilizer （PSS） and thyristor controlled series compensators （TCSC） are both installed in power system, the interaction maybe exist, which may result in inufficient damping to low-frequency oscillations. To overcome this problem, Modified Particle Swarm Optimization （MPSO） is used to coordinated design PSS and TCSC controllers, which remains the diversity of the particle swarm by changing the weight of the inertia on the basic of PSO. Convergence analysis results show that the presented algorithm can converge to optimal solution. A valid example is demonstrated on a 4-generator 11-bus test system. Eigenvalue analysis and nonlinear simulation results verify that the proposed method can displace eigenvalues into the specified area on the complex plane, and the PSS and TCSC controllots can provide sufficient damping to low frequency oscillation. Compared with the genetic algorithm and the simulated annealing algorithm, the result shows that MPSO has better performance on convergence and time cost.

关 键 词：电力系统稳定器 可控串联补偿器 改进粒子群算法 阻尼低频振荡 参数优化 

分 类 号：TM762[电气工程—电力系统及自动化]