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A GMPPT design using the following optimization algorithm for PV systems
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2021-05-24 , DOI: 10.1002/2050-7038.12794
Morteza Taherkhani 1 , Jalal Faraji 2 , Mehdi Khanjanianpak 3 , Ehsan Aliyan 2 , Mohammad Iman Ghiyasi 4
Affiliation  

In this study, the problem of tracking the global maximum power point (GMPP) in partially shaded conditions (PSCs) is considered as an optimization problem and solved by a novel optimization algorithm on the basis of the following optimization algorithm (FOA). This article examines a new way of using social relations based on optimization among members of a community in which members of the community as search factors try to improve the community by “following” each other. The proposed FOA has only one adjustable parameter, which leads to a simple structure and easy to implement. To validate the suggested method, some PSC scenarios with several peaks in the P-V curve are executed. The MATLAB/SIMULINK is employed to implement a photovoltaic (PV) system comprising a PV array, a boost converter, and the suggested FOA. Besides, the effectiveness of the suggested method is confirmed by an experimental set-up. The main limitation of the proposed approach is the accuracy of the measuring sensors.

中文翻译:

使用以下光伏系统优化算法的 GMPPT 设计

在本研究中,在部分阴影条件 (PSC) 下跟踪全局最大功率点 (GMPP) 的问题被视为优化问题,并通过基于以下优化算法 (FOA) 的新型优化算法解决。本文研究了一种基于社区成员之间优化的社会关系使用新方法,其中社区成员作为搜索因素试图通过“跟随”彼此来改善社区。所提出的FOA只有一个可调参数,结构简单,易于实现。为了验证建议的方法,执行了一些在 PV 曲线中有几个峰值的 PSC 场景。MATLAB/SIMULINK 用于实现光伏 (PV) 系统,该系统包括光伏阵列、升压转换器和建议的 FOA。除了,所建议的方法的有效性得到了实验装置的证实。所提出的方法的主要限制是测量传感器的精度。
更新日期:2021-07-02
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