A New MPPT Controlling Mechanism based on Adaptive Mongoose Optimization (MO) Algorithm for Grid-PV Systems

S. Marlin, S. D. S. Sundarsingh Jebaseelan
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引用次数: 1

Abstract

Recent years have seen a rise in the use of solar Photovoltaic (PV) systems in numerous application systems because of their effectiveness and affordability. One of the main challenges is producing the maximum energy from PV panels under various environmental circumstances. In order to achieve the highest energy output, numerous optimization-based MPPT controlling systems have been devised in traditional works. Low convergence, computational complexity, the length of time required to discover the optimum solution, and inefficiency are major drawbacks. In order to put a recently created optimization technique called Mongoose Optimization (MO) for MPPT regulating into practise that is the aim of this study. With superior tracking efficiency and enhanced speed, it facilitates obtaining the maximum power from the PV panels. Moreover, a bi-directional converter is employed to control PV output while decreasing switching stress and loss. Also, the voltage source inverter is employed to lower harmonic distortion levels in order to guarantee improved power quality. Performance study evaluates and compares the simulation outcomes and the efficacy of the suggested regulating architecture using a variety of metrics.
一种基于自适应猫鼬优化(MO)算法的并网光伏系统最大功率控制机制
近年来,由于太阳能光伏(PV)系统的有效性和可负担性,在许多应用系统中使用的太阳能光伏系统有所增加。主要的挑战之一是在各种环境条件下最大限度地利用光伏板产生能量。为了获得最高的能量输出,传统工程中设计了许多基于优化的MPPT控制系统。低收敛性、计算复杂性、发现最优解所需的时间长度以及效率低下是主要的缺点。为了将最近创建的一种称为猫鼬优化(MO)的MPPT调节优化技术应用于实践,这是本研究的目的。它具有优越的跟踪效率和提高的速度,有利于从光伏板获得最大的功率。此外,采用双向变换器控制PV输出,同时降低开关应力和损耗。同时,采用电压源逆变器降低谐波失真水平,保证电能质量的提高。性能研究使用各种度量来评估和比较模拟结果和建议的调节体系结构的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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