This paper proposes a hybrid algorithm-based control model for enhancing the low voltage ride through (LVRT) capability of the doubly fed induction generator (DFIG) system. The hybrid algorithm is the combined execution of both modified elephant herding algorithm (MEHA) and random forest (RF) algorithm, and hence the technique is named as MEHRFA. The purpose of the proposed control technique ensures the LVRT capability in the DFIG-based WECS at voltage drop and fault conditions. Here, MEHA approach is used as offline manner to identify the ideal solutions from the available searching space and creates the training dataset. In the MEHA technique, multiple parameters are considered which are related to LVRT such as, voltage, real and reactive powers and current. Utilizing these parameters, the objective function is characterized and solved by MEHA method. In light of the accomplished dataset, the RF performs and predicts the best possible control signals for machine-side converter and grid-side converter. In this manner, the LVRT capability of DFIG system and power quality issues has been enhanced with the assistance of proposed technique. The proposed procedure is implemented in MATLAB/Simulink working platform, and the exhibition is assessed by utilizing the comparison analysis with existing techniques.

本文提出了一种基于混合算法的控制模型，用于增强双馈感应发电机（DFIG）系统的低压穿越（LVRT）能力。混合算法是修改后的大象放牧算法（MEHA）和随机森林（RF）算法的组合执行，因此该技术称为MEHRFA。所提出的控制技术的目的是确保在基于DFIG的WECS中在压降和故障条件下具有LVRT功能。在这里，MEHA方法用作脱机方式，以从可用搜索空间中识别理想解决方案并创建训练数据集。在MEHA技术中，考虑了与LVRT相关的多个参数，例如电压，有功功率和无功功率以及电流。利用这些参数，通过MEHA方法对目标函数进行表征和求解。根据已完成的数据集，RF可以执行并预测机器侧转换器和电网侧转换器的最佳控制信号。以这种方式，借助于所提出的技术，增强了DFIG系统的LVRT能力和电能质量问题。拟议的程序在MATLAB / Simulink工作平台上实现，并通过与现有技术的比较分析对展览进行评估。