A Hybrid Approach for Photovoltaic Maximum Power Tracking under Partial Shading Using Honey Badger and Genetic Algorithms

被引：1

作者：

Fan, Zhi-Kai ^{[1
]}

Setianingrum, Annisa ^{[1
]}

Lian, Kuo-Lung ^{[1
]}

Suwarno, Suwarno ^{[2
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Dept Elect Engn, Sect 4,43 Keelung Rd, Taipei 106, Taiwan

[2] Bandung Inst Technol, Sch Elect Engn & Informat, Dept Elect Power Engn, Jalan Ganesha 10, Bandung 40132, Indonesia

来源：

ENERGIES | 2024年 / 17卷 / 16期

关键词：

maximum power point tracking; photovoltaic system; honey badger algorithm; genetic algorithm; partial shading condition; MPPT ALGORITHM; GLOBAL MPPT; SYSTEMS; OPTIMIZATION; PERTURB;

D O I：

10.3390/en17163935

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 study presents a new approach for Maximum Power Point Tracking (MPPT) by combining the honey badger algorithm (HBA) with a Genetic Algorithm (GA). The integration aims to optimize photovoltaic (PV) system performance in partial shading conditions (PSCs). Initially, the HBA is utilized to explore extensively and identify potential solutions while avoiding local optima. If necessary, the GA is then employed to escape local optima through selection, crossover, and mutation operations. On average, this proposed method has a 40% improvement in tracking time and 0.77% in efficiency compared with the HBA. In a dynamic case, the proposed method achieves a 4.81% improvement compared to HBA.

引用

页数：16

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