摘要
针对水轮发电机组调速器PID的参数优化问题,建立了水轮机调节系统仿真模型,引入混沌扰动理论的混合粒子群算法,实现了水轮机调速器PID参数整定优化。仿真表明,混合算法整定PID参数后的调节系统具有超调量小、稳定性好特点,能有效改善水轮机调节系统过渡过程的动态性能,同时算法收敛速度快、准确度高,有效地克服了标准粒子群算法易早熟等缺点,提高了算法的精确性。
Based on the parameter optimization problem of the turbine generator governor PID,the simulation model of the turbine governing system is established,and the hybrid particle swarm optimization algorithm of chaotic perturbation theory is introduced to realize the PID parameter tuning optimization of the turbine governor. The simulation shows that the adjustment system with PID parameters has the characteristics of small overshoot and good stability,which can effectively improve the dynamic performance of the transition process of the turbine governing system. In addition,the algorithm has fast convergence speed and high accuracy,effectively overcoming.The shortcomings of the standard particle swarm algorithm are easy to premature,which improves the accuracy of the algorithm.
作者
张剑焜
李志红
李燕
梁兴
魏志芳
朱政
ZHANG Jian-kun;LI Zhi-hong;LI Yan;LIANG Xin;WEI Zhi-fang;ZHU Zheng(Jiangxi Province Key Laboratory of Precision Drive and Control,Institute of Technology,Nanchang 330099,Jiangxi Province,China;School of Mechanical and Electrical Engineering,Nanchang Institute of Technology,Nanchang 330099,Jiangxi Province,China)
出处
《中国农村水利水电》
北大核心
2019年第1期180-183,192,共5页
China Rural Water and Hydropower
基金
江西省教育厅科技项目(GJJ170988)
江西省精密驱动与控制重点实验室项目(PLPDC-KFKT-201623)
江西省科技厅基金青年项目(20171BAB216054)
南昌工程学院研究生创新基金项目(YJSCX20180028)
关键词
混沌扰动
粒子群算法
调速器
参数优化
chaos perturbation
particle swarm optimization algorithm
governor
parameter optimization
