基于CPSOGSA的水轮机调速系统PID参数优化

PID Parameter Optimization of Hydraulic Turbine Governing System Based on CPSOGSA

为实现水轮机调速系统的智能控制,提出一种基于收敛因子粒子群优化算法(CPSO)与引力搜索优化算法(GSA)的CPSOGSA算法。首先建立水轮机的基本模型,然后利用CPSOGSA算法对PID控制器的参数进行优化并搭建Simulink仿真模型。仿真结果表明,利用CPSOGSA算法能快速得到PID控制器的最佳匹配初始参数,且在频率扰动和风电功率扰动下,基于CPSOGSA算法的PID控制系统相较于传统PID控制系统输出转速波动更小,稳定时间更短,动态响应速度更快。将基于CPSOGSA算法的PID控制策略应用于水轮机调速系统具有较佳的动态稳定性。

In order to achieve intelligent control of the hydraulic turbine speed control system,a CPSOGSA algorithm based on the conver⁃gence factor particle swarm algorithm(CPSO)and the gravitational search optimization algorithm(GSA)is proposed.Firstly,the basic model of the hydraulic turbine is established,and then the parameters of the PID controller are optimized and Simulink simulation model is built us⁃ing the CPSOGSA algorithm.The simulation results show that the best matching initial parameters of the PID controller can be obtained quick⁃ly by using the CPSOGSA algorithm,and the PID control system of the CPSOGSA algorithm has smaller output speed fluctuation,shorter sta⁃bilization time and faster dynamic response than the traditional PID control system under frequency perturbation and wind power perturbation.The PID control based on the CPSOGSA algorithm has better dynamic stability when applied to the turbine speed control system.