Yang, Bo, Liang, Boxiao, Wu, Shaocong, Li, Hongbiao, Gao, Dengke, Jiang, Lin 
ORCID: 0000-0001-6531-2791 and Wang, Jingbo
(2025)
Optimal power extraction of PV-TEG hybrid system via fitness-distance-balance-based beluga whale optimization
GLOBAL ENERGY INTERCONNECTION-CHINA, 8 (1).
pp. 43-61.
ISSN 2096-5117, 2590-0358
Abstract
This study integrates the individual photovoltaic (PV) and thermoelectric generator (TEG) systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational reliability. However, stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules, which negatively affect the output characteristics of the system, thus presenting a significant challenge to maintaining their optimal performance. To address these challenges, a novel fitness-distance-balance-based beluga whale optimization (FDBBWO) strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenarios. A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO. For this, real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy. Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output, with a remarkable increase of up to 134.25 % with minimal power fluctuations. For instance, the energy obtained by FDBBWO is 47.45 % and 58.34 % higher than BWO and perturb and observe methods, respectively, in the winter season.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Photovoltaic-thermoelectric-generator Hybrid system, Maximum power point tracking, Partial shading conditions, Fitness-distance-balance-based beluga whale optimization, SimuNPS |
| Divisions: | Faculty of Science & Engineering Faculty of Science & Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 03 Jun 2025 07:35 |
| Last Modified: | 16 Jun 2026 20:24 |
| DOI: | 10.1016/j.gloei.2024.10.014 |
| Open Access URL: | https://www.sciencedirect.com/science/article/pii/... |
| Related Websites: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3192968 |
| Disclaimer: | The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate. |
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