Modular reconfiguration of hybrid PV-TEG systems via artificial rabbit algorithm: Modelling, design and HIL validation

• Published in: Applied energy Vol. 351; p. 121868
• Main Authors: Yang, Bo, Li, Yulin, Huang, Jianxiang, Li, Miwei, Zheng, Ruyi, Duan, Jinhang, Fan, Tingsheng, Zou, He, Liu, Tao, Wang, Jingbo, Shu, Hongchun, Jiang, Lin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2023
• Subjects: adverse effects; algorithms; Artificial rabbit optimization; energy; Hardware-in-the-loop; Hybrid PV-TEG systems; hybrids; Modular reconfiguration; power generation; rabbits; solar collectors; standard deviation; theoretical models; Artificial rabbit optimization; Modular reconfiguration; Hybrid PV-TEG systems; Hardware-in-the-loop
• ISSN: 0306-2619
• DOI: 10.1016/j.apenergy.2023.121868

To further improve the power generation efficiency of traditional photovoltaic (PV) systems, this paper designs a theoretical model of a hybrid power generation system that consists of the individual PV system and thermoelectric generation (TEG) system. Meanwhile, partial shielding condition (PSC) is a common but serious problem during operation that might lead to power loss and component mismatch in hybrid PV-TEG system. Therefore, a reconfiguration method for the hybrid PV-TEG system based on artificial rabbit optimization (ARO) algorithm is proposed in this study to alleviate the negative impact caused by PSC and thus improve the power generation efficiency of the hybrid system. ARO algorithm is applied to adjust the switching matrix of the hybrid system to change the electrical connection among PV arrays and TEG arrays, and thus further to reduce the adverse effect of PSC and maximize the output power of the hybrid system. To verify the effectiveness of the proposed method, simulation tests are carried out on 4 × 4 and 20 × 15 arrays, respectively. For a quantitative and fair comparison, this work employs maximum output power, average output power, mismatch loss, and standard deviation as evaluation indexes, upon which four different algorithms including GA, PSO, WOA, AOA and ACO are thoroughly compared. Simulation results show that the output power of the hybrid system after ARO algorithm based reconfiguration is improved by 34.05% in the 4 × 4 array and 23.10% in the 20 × 15 array, respectively. In addition, hardware-in-the-loop (HIL) experiments are carried out based on RTLAB platform to verify the hardware feasibility of the proposed reconfiguration strategy. •A hybrid PV-TEG system model is introduced and constructed in this work;•A modular reconfiguration scheme for hybrid PV-TEG systems is proposed, in which the PV and TEG array components are modularized to reduce the overall costs;•This work devises a reconfiguration method for hybrid systems based on ARO algorithm;•The HIL experiment based on RTLAB platform is undertaken to further prove the implementation feasibility of the reconfiguration strategy.