Hybrid Global Maximum Power Point Tracking Algorithm for a Thermoelectric Generation System

被引：2

作者：

Jang, Yohan ^{[1
]}

Lee, Chaeeun ^{[1
]}

Ji, Sanghyuk ^{[1
]}

Bae, Sungwoo ^{[1
]}

机构：

[1] Hanyang Univ, Dept Elect Engn, Seoul, South Korea

来源：

2021 24TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2021) | 2021年

关键词：

Thermoelectric generation system; Maximum power point tracking; Non-uniform temperature conditions; MPPT;

D O I：

10.23919/ICEMS52562.2021.9634344

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes a new hybrid global maximum power point (GMPP) tracking algorithm which is a linear extrapolation-based grey wolf optimization algorithm (LEGWO). The LEGWO combines the advantages of a grey wolf optimization algorithm (GWO) and a linear extrapolation-based maximum power point tracking algorithm. As a result, this algorithm enables fast and accurate tracking of the GMPP. The proposed algorithm is verified by comparison simulation results of a perturbation and observation algorithm and the GWO in MATLAB/Simulink. The results validate that the LEGWO does not converge at the local maximum power point and tracks the exact GMPP. Also, the tracking time of the LEGWO is 53.09% faster than the GWO.

引用

页码：267 / 271

页数：5

共 7 条

[1] A Linear Extrapolation-Based MPPT Algorithm for Thermoelectric Generators Under Dynamically Varying Temperature Conditions [J].