Performance Investigation for Tracking GMPP of Photovoltaic System Under Partial Shading Condition Using Coyote Algorithm

被引：0

作者：

Mostafa, Hazem H. ^{[1
]}

Ibrahim, Amr M. ^{[2
]}

机构：

[1] Egyptian Chinese Univ, Energy & Renewable Energy Dept, Cairo, Egypt

[2] Ain Shams Univ, Elect Power & Machines Dept, Cairo, Egypt

来源：

2019 21ST INTERNATIONAL MIDDLE EAST POWER SYSTEMS CONFERENCE (MEPCON 2019) | 2019年

关键词：

Bio-Inspired algorithm; Coyote optimization algorithm; Maximum power point tracking; Photovoltaic; Partial shading conditions;

D O I：

10.1109/mepcon47431.2019.9008012

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

this paper presents a methodology utilizing Coyote Optimization Algorithm (COA) for Global Maximum Power Point Tracking (GMPPT) considering the impact of partial shading on a PV system. COA is utilized to clarify GMPP by comparing all the existing peaks on the PV curve. COA is also employed to control the boost converter. Different shading patterns are applied to a photovoltaic system. Simulations of this process are established utilizing MATLAB software. The suggested algorithm is compared with enhanced Grey Wolf Optimization (E-GWO), Dragonfly Algorithm (DA), Ant Lion Optimization (ALO), and Particle Swarm Optimization (PSO). According to the results, the suggested COA improves the tracking speed and accuracy of MPPT during partial shading conditions. Also, the suggested methodology is providing high efficiency for solar PV systems in any irradiation conditions.

引用

页码：34 / 40

页数：7

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