This article introduces an optimal PI controller optimized by elephant herding algorithm (EHA) to control the grid-tied four-phase 8/6 switched reluctance generator (SRG). This controller is introduced for enhancing the low voltage ride through (LVRT) capability of the grid-tied SRG during faulty conditions that affect the SRG output voltage by regulating the off-delay angle of the generator. These faulty conditions include faults taken place at the point of connection (POC) of the SRG to the grid and wind speed variations. The proposed optimized PI controller regulates the off-delay angle of the generator to keep the voltage at the POC within acceptable limits. Maintaining these acceptable voltage limits during faulty conditions that keeps the generator in connection to the grid and makes the generator complying with the grid codes. Comparison between EHA optimization technique, cuckoo search optimization and particle swarm optimization (PSO) were presented to illustrate the effectiveness of the modern optimization technique used, EHA. An experimental verification of the proposed system is introduced by rewinding the stator and reshaping the rotor of three-phase induction machine to form four-phase, 8/6 SRG. Finite element method (FEM) based on ANSYS software is utilized to get the magnetic characteristics of the reconstructed 8/6 SRG after drawing the 3-D geometrical dimension in AUTOCAD.

本文介绍了一种通过大象羊群算法（EHA）优化的最优PI控制器，以控制并网四相8/6开关磁阻发电机（SRG）。引入此控制器的目的是通过调节发电机的断开延迟角，在影响SRG输出电压的故障条件下增强并网SRG的低压穿越（LVRT）能力。这些故障条件包括SRG与电网的连接点（POC）发生的故障以及风速变化。提出的优化PI控制器可调节发电机的断开延迟角，以将POC处的电压保持在可接受的范围内。在故障情况下保持这些可接受的电压限制，使发电机保持与电网的连接，并使发电机符合电网法规。对EHA优化技术，布谷鸟搜索优化和粒子群优化（PSO）进行了比较，以说明所使用的现代优化技术EHA的有效性。通过对三相感应电机的定子进行重绕并对其转子进行整形以形成四相，8/6 SRG，对所提出的系统进行了实验验证。在AUTOCAD中绘制3-D几何尺寸后，利用基于ANSYS软件的有限元方法（FEM）来获得重建的8/6 SRG的磁特性。通过对三相感应电机的定子进行重绕并对其转子进行整形以形成四相，8/6 SRG，对所提出的系统进行了实验验证。在AUTOCAD中绘制3-D几何尺寸后，利用基于ANSYS软件的有限元方法（FEM）来获得重建的8/6 SRG的磁特性。通过对三相感应电机的定子进行重绕并对其转子进行整形以形成四相，8/6 SRG，对所提出的系统进行了实验验证。在AUTOCAD中绘制3-D几何尺寸后，利用基于ANSYS软件的有限元方法（FEM）来获得重建的8/6 SRG的磁特性。