改进粒子群优化算法在同步发电机励磁参数整定中的应用  

Application Study of Improved PSO Algorithm in Excitation Parameter Tuning for Synchronous Generator

作　　者：彭继慎[1] 韩云涛[1] 

机构地区：[1]辽宁工程技术大学电气与控制工程学院,辽宁葫芦岛125105

出　　处：《计算机测量与控制》2013年第5期1341-1343,1359,共4页Computer Measurement &Control

基　　金：辽宁省高等学校优秀人才支持计划(2008RC25);辽宁省创新团队项目(LT2010047)

摘　　要：为了优化传统励磁控制系统中比例—积分—微分控制参数,文章在介绍了PSO算法的基础上,一方面引入自适应惯性权重,另一方面通过添加扰动项改进速度更新方程,提出了一种改进粒子群优化算法,并改进了适应度函数,将其应用于励磁控制系统中;在建立非线性励磁控制系统模型的基础上,设计了一种改进PSO-PID控制器,对励磁控制系统的PID参数进行整定;激励信号分别施加零起升压和负载电压扰动,新方法适应度函数为0.013,超调量为0.03%,计算时间为30.2s,均为最小,相对于一般的粒子群优化方法具有更好的收敛速度和精度,且鲁棒性更好,能有效改善励磁控制系统空载起励动态性能。To optimize the parameters of proportional integral differential （PID） controller in excitation control system, we present an improved PSO algorithm based on the basic PSO algorithm and improve the fitness function. On the one hand we add the adaptive inertia weight, on the other hand we improve the velocity update equation by adding the disturbance. Based on the nonlinear model of excitation con- trol system we design an improved PSO--PID controller in order to tuning the PID parameters of excitation control system. Zero boost and load voltage disturbance are applied as the excitation signals. An experimental result which the data is 0. 013, the over shoot is 0.03 %, the computation time is 30. 2s, shows that the new method is proved to have better convergence speed and accuracy compared to the conventional particle swarm optimization. It can effectively improve the dynamic performance of excitation control system on the state of no--load excitation and has a strong anti--jamming capability.

关 键 词：励磁控制系统 PSO算法 自适应惯性权重 零起升压 负载电压扰动 

分 类 号：TP303[自动化与计算机技术—计算机系统结构]