@article{article_1648962, title={Tasmanian devil optimization for optimal identification of photovoltaic model parameters}, journal={Journal of the Institute of Science and Technology}, volume={15}, pages={1297–1310}, year={2025}, DOI={10.21597/jist.1648962}, author={Boylu Ayvaz, Birsen and Doğan, Zafer}, keywords={Fotovoltaik hücreler, Parametre tahmini, Metasezgisel algoritmalar, Tazmanya canavarı optimizasyonu, Optimizasyon}, abstract={In the whole world, when the distribution of electricity generation according to resources is examined, it is seen that photovoltaic (PV) systems constitute an important part of electricity generation. Considering this situation, to improve the PV system efficiency, high-accuracy models for PV cells should be developed depending on the current-voltage measurement data of the PV cell. In literature studies, single-diode and two-diode circuits are often utilized as PV cell models. The precision of the models is frequently determined by the accuracy of the characteristic parameters. These parameters need to be estimated effectively and accurately using PV cell measurement data. To get the optimal parameters that provide the best match between the estimated and experimental measurement data, metaheuristics are the most preferred optimization methods. This study proposed the Tasmanian devil optimization (TDO) algorithm for identifying the optimal PV model parameters. The proposed method is applied to solar cells that are frequently used in literature. The performance of the proposed method is evaluated by comparing it with other literature methods. It is seen that the PV cell models obtained by using TDO for two diode circuits, i.e. single-diode and two-diode, and PV module, demonstrate higher accuracy in matching experimental data compared to other models obtained by different methods.}, number={4}, publisher={Iğdır Üniversitesi}