Improving the operation of wind energy generation system is a big challenge especially when it operates under unstable weather conditions. Therefore, installing a tracker for monitoring the maximum power expected to be generated from the wind energy system is essential, this controller is known as maximum power point tracker (MPPT). Hill climbing based approaches were applied for simulating the tracker, however they have limitations in tracking speed and efficiency. This paper proposes a recent efficient approach of Archimedes optimization algorithm (AOA) for simulating MPPT installed with the wind energy generation system. The constructed system composes wind turbine (WT) connected to a permanent magnet synchronous generator (PMSG), the AC output power from the generator is converted to DC via 3-phase rectifier, the DC voltage is the input of boost converter which is controlled via its MOSFET duty cycle. The designing process is presented as an optimization problem considering the electrical output power from the system as the target. The proposed AOA tunes the converter duty cycle to maximize the output power. Three scenarios are followed in this work which are fixed wind speed, variable wind speed, and real wind speed recorded at four sites in Saudi Arabia (Sakaka, Riyadh, Jeddah, and Jizan). The obtained results via the proposed approach are compared with the results obtained via cuckoo search (CS), grasshopper optimization algorithm (GOA), and electric charged particle optimization (ECPO). The results confirmed the robustness of the proposed AOA-MPPT in achieving the best performance of wind energy generation system.

改善风能发电系统的运行是一个很大的挑战，尤其是在不稳定的天气条件下运行时。因此，安装一个跟踪器来监测预计从风能系统产生的最大功率是必不可少的，这个控制器被称为最大功率点跟踪器 (MPPT)。基于爬山的方法被应用于模拟跟踪器，但是它们在跟踪速度和效率方面存在局限性。本文提出了一种最新的阿基米德优化算法 (AOA)，用于模拟安装在风力发电系统中的 MPPT。构建的系统由连接到永磁同步发电机 (PMSG) 的风力涡轮机 (WT) 组成，发电机的交流输出功率通过三相整流器转换为直流，直流电压是升压转换器的输入，由其 MOSFET 占空比控制。设计过程以系统的电输出功率为目标呈现为一个优化问题。建议的 AOA 调整转换器占空比以最大化输出功率。在这项工作中遵循三种情景，即固定风速、可变风速和在沙特阿拉伯的四个地点（萨卡卡、利雅得、吉达和吉赞）记录的真实风速。通过所提出的方法获得的结果与通过布谷鸟搜索（CS）、蚱蜢优化算法（GOA）和带电粒子优化（ECPO）获得的结果进行了比较。结果证实了所提出的 AOA-MPPT 在实现风力发电系统的最佳性能方面的鲁棒性。