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

被引：1
|
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
收藏
页码：267 / 271
页数：5
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