基于粒子群优化的同步风力发电机励磁系统的变论域模糊控制

Variable Universe Fuzzy Control of Synchronous Wind Generator Excitation System Based on the Particle Swarm Optimization

针对直接并网型同步风力发电机励磁系统非线性、时变性及风力发电机运行工况多变等特点,提出了一种基于粒子群优化的同步风力发电机励磁系统的变论域模糊控制方法。该方法中,通过分析确定变论域伸缩因子的结构,利用粒子群算法优化其参数,实现伸缩因子参数的智能寻优。将粒子群优化的变论域模糊控制器应用于励磁控制中,根据电压环的性能指标建立目标函数,通过对基本论域自适应调整,实现了同步风力发电机励磁系统在全工况下的自适应控制,提高了发电机端电压的调节精度和运行的稳定性。仿真结果表明,基于粒子群优化的变论域模糊控制在动态性能和稳态性能上优于模糊控制。

According to the characteristics like nonlinear, time-varying and changing operating conditions of the excitation system in synchronous wind generator with directly grid-connected, a variable universe fuzzy control design method of synchro-nous wind generator excitation control system based on PSO is proposed in this paper.With this method, the intelligent optimi-zation of contraction-expansion factor parameters is achieved by analyzing and deciding the structure of the variable universe contraction-expansion factor, and using the particle swarm optimization to optimize its parameters.After applying the opti-mized variable universe fuzzy controller to the excitation control system, the objective function is established according to the voltage loop performance, then adaptive control of synchronous wind generator excitation system is achieved via adjusting basic universe of discourse, which could improve the accuracy of the generator terminal voltage regulation and the stability of run-ning.Simulation results show that the control method is superior to the traditional fuzzy control in both dynamic performance and steady-state performance.