Dynamic reconfiguration design of hybrid photovoltaic-thermoelectric generation systems - Wang, Yutong; Yang, Bo; Li, Junpeng (Applied thermal engineering, 2024)
•A hybrid photovoltaic-thermoelectric generation system model is introduced and constructed.•A modular reconfiguration scheme for hybrid photovoltaic-thermoelectric generation systems is proposed.•Thephotovoltaic and thermoelectric generation array components are modularized to reduce the overall costs.•Devises a reconfiguration method for hybrid systems based on enhanced artificial bee colony algorithm.•The hardware-in-loop experiment proves the feasibility of the reconfiguration strategy. An enhanced artificial bee colony algorithm is presented for optimal reconfiguration of a photovoltaic-thermoelectric generation hybrid system, especially under partial shading conditions. The goal is to achieve real-time maximum power extraction. To address the limitation of the original artificial bee colony algorithm of susceptibility to local optima, a second-order oscillatory perturbation tactic is integrated for a more refined balance between local exploitation and global exploration during iterations. For the performance evaluation of the modified enhanced artificial bee colony algorithm, its performance is validated and compared against eleven other meta-heuristic strategies under three distinct array configurations: 4 × 4, 15 × 15, and 15 × 20, exposed to varied shading situations. The maximum power of 15 × 15 and 20 × 20 arrays after enhanced artificial bee colony algorithm reconfiguration increased by 22.63 % and 22.90 %, respectively, than before the reconfiguration. enhanced artificial bee colony algorithm significantly reduced the adverse effects of multiple peak power distributions generated by partial shading conditions, achieving the lowest mismatch power loss, with 15 × 15 and 20 × 20 arrays improving by 3.44 % and 5.20 % over the gravity search algorithm, respectively. Additionally, the practical hardware implementation feasibility of enhanced artificial bee colony algorithm is confirmed through a hardware-in-loop analysis utilizing the RTLAB platform, emphasizing its relevance in real-world engineering scenarios.