Parameter Extraction of Solar Photovoltaic Modules Using a Novel Bio-Inspired Swarm Intelligence Optimisation Algorithm

For extracting the equivalent circuit parameters of solar photovoltaic (PV) panels, a unique bio-inspired swarm intelligence optimisation algorithm (OA) called dandelion (DOA) is proposed in this study. The suggested approach has been used to analyse well-known single-diode (SD) and double-diode (DD) PV models for several module types, including monocrystalline SF430M, polycrystalline SG350P, thin-film Shell ST40. DOA adopted by minimizing sum squares errors at three locations (short-circuit, open-circuit, maximum power points). Different runs are conducted nature extracted V–I characteristics panels under consideration. Obtained results show that Mono error SD model 2.5118e-19, DD 2.0463e-22; Poly 9.4824e-21, 2.1134e-20; ST40, 1.7621e-20, 7.9361e-22. produced from method yield least amount across executions, which suggests its better implementation current situation. Furthermore, statistical analysis using also carried out compared with two hybrid OAs literature. Statistical standard deviation, sum, mean, variance various lower those other OAs.