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Because of the rise in solar electricity, photovoltaic research has increased. A precise model of the PV-based cell/unit is ideal for conceptually examining the capabilities of alternative control approaches. Extraction of precise values for relevant unknown elements of solar photovoltaic models is crucial for modeling PV systems. Optimization strategies for this topic have been increasingly important and dynamic in recent history due to their efficiency in dealing with extremely nonlinear multidimensional optimization challenges. The strategy avoids stalling by deleting the best solution; this keeps the engine diverse and increases global search capacity. Pattern searching, on either side, is a multiobjective approach that has a high convergence speed as well as good stability, which can increase the whale optimization algorithm’s traditional optimization ability. As a result, combining these two mechanisms can considerably improve the whale optimization algorithm capacity to find the optimal answer. The modified whale optimization algorithm may also be used to evaluate parameters in single-diode models, double-diode models, and photovoltaic panels, as well as to find independent variables in two distinct methods of PV modules under various light temperature and pressure circumstances. The analytical results show that the modified whale optimization algorithm is both valid and practical for predicting solar cell and photovoltaic unit characteristics. The study goes into great depth on a new optimization approach for changing the parameter unit of solar PV cells.

A Novel Optimization Algorithm for Modifying the Parameter Unit of Solar PV Cell