基于最小二乘和自适应蛇优化算法的直驱风机LVRT特性辨识

Identification of LVRT Characteristic of Direct-driven Wind Turbine Generator Based on LS and ASO Algorithms

为提高直驱风机低电压穿越LVRT(low voltage ride through)控制参数辨识精度,提出了一种基于最小二乘LS(least square)和自适应蛇优化ASO(adaptive snake optimization)算法的直驱风机LVRT特性辨识方法。首先,利用最小二乘法拟合出直驱风机LVRT待辨识参数初值,以确定待辨识参数的寻优范围;然后,分析了蛇优化SO(snake optimization)算法分阶段寻优的边界条件,设计了分阶段自适应学习因子,并引入Levy飞行策略,提出了适用于直驱风机LVRT控制参数辨识的ASO算法;最后,将ASO算法多次辨识平均值作为最终结果。结果表明,所提方法能快速、准确辨识直驱风机LVRT控制参数。

To increase the identification accuracy of low voltage ride through(LVRT)control parameters for a directdriven wind turbine generator,an identification method based on the least square(LS)and adaptive snake optimization(ASO)algorithms is proposed.First,the LS algorithm is used to fit the initial values of LVRT parameters which are to be identified,thus determining the searching range of these parameters.Then,the boundary conditions of the snake op⁃timization(SO)algorithm for staged optimization are analyzed,and the staged adaptive learning factors are designed.In addition,the Levy strategy is introduced,and an ASO algorithm suitable for the identification of LVRT control pa⁃rameters of direct-driven wind turbine generator is put forward.Finally,the average value of multiple identifications by the ASO algorithm is taken as the final result.Results show that the proposed method can quickly and accurately identi⁃fy the LVRT control parameters of direct-driven wind turbine generator.