基于改进免疫遗传算法的双馈风机控制系统PI参数优化

PI Parameters Optimization of DFIG Control System Based on Improved Immune Genetic Algorithm

鉴于双馈风机(DFIG)在故障期间的控制性能依赖干控制参数的选取,将免疫遗传算法(IGA)引入DFIG控制系统PI参数的优化设计中,以DFIG的控制目标作为PI参数的优化目标,选取极点配置法整定值作为初值提高优化效率,根据DFIG控制系统自身特点对编码、交叉和变异算子、免疫算子进行自适应改进.形成了适用干DFIG控制系统PI参数优化的改进免疫遗传算法(IIGA)。该算法可以同时实现控制系统的多目标优化和转子侧变换器与网侧变换器的协调配合,在电压跌落过程中较极点配置法可获得更好的控制性能。最后,在MATLAB,Simulink中搭建了含风电场的系统仿真模型,仿真结果验证了本文所提方法的有效性。

In view of the dependence of control performances of doubly fed induction generator(DFIG) on control parameters selection during the fault period,immune genetic algorithm(IGA) is introduced for the PI parameters optimization design of DFIG control system.The control targets of the DFIG are regarded as the optimization function of the PI parameters,and the setting values of pole placement method are used as the initial antibody to improve the optimization efficiency.Adaptive improvements are made on coding,crossover and mutation operators,immune operator according to the characteristics of the DFIG control system,forming the improved immune genetic algorithm(IIGA) that applies to the PI parameters optimization of the DFIG control system.This algorithm can achieve both the multi-objective optimization of the control system and the coordination of rotor side and grid side converter,and make better control performance than that of the pole placement method during the voltage sag.Finally,the system simulation model containing the wind farm is built in MATLAB/Simulink and simulation results verify the effectiveness of the proposed method.