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Hybrid Global Maximum Power Point Tracking Algorithm for a Thermoelectric Generation System
- Authors
- Jang, Yohan; Lee, Chaeeun; Ji, Sanghyuk; Bae, Sungwoo
- Issue Date
- Dec-2021
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Maximum power point tracking; Non-uniform temperature conditions; Thermoelectric generation system
- Citation
- ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems, pp.267 - 271
- Indexed
- SCOPUS
- Journal Title
- ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems
- Start Page
- 267
- End Page
- 271
- ISSN
- 0000-0000
- Abstract
- 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.
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Related Researcher
- Bae, Sung Woo
- COLLEGE OF ENGINEERING (MAJOR IN ELECTRICAL ENGINEERING)