Photovoltaic parameter estimation using honey badger algorithm and African vulture optimization algorithm
Ahmed A. Zaki Diab, Mohamed A. Tolba, Ali M. El‐Rifaie, Denis A. Kotin
Abstract
The accurate arithmetical models of solar photovoltaic (PV) modules plays a vital role in the performance, operation, and control of the PV systems as a part of renewable generation. Therefore, the proposed paper develops a novel robust Honey Badger Algorithm (HBA) and African Vulture Optimization algorithm (AVOA) that have been utilized for deducing the unknown parameters of various solar PV units accurately and efficiently. The HBA and AVOA techniques are developed to identify the approximate undefined parameters of different PV system models, namely, single diode model (SDM), double diode model (DDM), and three diode model (TDM). The attained results from the application of HBA and AVOA are to optimize the objective function of the current errors between the measure and the evaluation of the PV modules. Moreover, statistical tests have been presented to demonstrate the effectiveness of HBA and AVOA. The numerical results of the developed HBA and AVOA prove them as competitor methods for the parameters’ extraction of solar PV systems.