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Parameter extraction for photovoltaic models with tree seed algorithm
(Elsevier Ltd., 2022) Beşkirli, Ayşe; Dağ, İdiris
Evaluation, simulation and optimization of PV systems is very important for fast and accurate parameter extraction based on current–voltage and power–voltage characteristic curves of photovoltaic models. Therefore, researchers used many metaheuristic algorithms to estimate the parameters of various PV modules. In this study, tree seed algorithm (TSA) was used for parameter estimation of the STM6-40/36 PV module. In the basic TSA, there are two different resolution mechanisms for balancing both local and global search technique. For this reason, basic TSA was preferred for parameter extraction of the PV module. The parameter results obtained by TSA were compared with those found by some other algorithms in the literature. According to the comparison result, the lowest root mean square error (RMSE) was obtained with the TSA algorithm. When the convergence graphs are examined, it is seen that TSA converges faster than other algorithms. When the box plots are analyzed, the results obtained by TSA have fewer outliers than the results of other algorithms, showing that TSA has a stable structure. In addition, a ranking graph was drawn according to the results obtained by all algorithms at each run time, and it was seen that TSA had the lowest RMSE value at all run times. Thus, it is concluded that TSA is a very competitive method for the PV module problem.