Efficient ranking-based whale optimizer for parameter extraction of three-diode photovoltaic model: Analysis and validations

Mohamed Abdel-Basset, Reda Mohamed, Attia El-Fergany, Sameh S. Askar, Mohamed Abouhawwash

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
42 Downloads (Pure)

Abstract

Efficient and accurate estimations of unidentified parameters of photovoltaic (PV) models are essential to their simulation. This study suggests two new variants of the whale optimization algorithm (WOA) for identifying the nine parameters of the three-diode PV model. The first variant abbreviated as RWOA is based on integrating the WOA with ranking methods under a novel updating scheme to utilize each whale within the population as much as possible during the optimization process. The second variant, namely HWOA, has been based on employing a novel cyclic exploration-exploitation operator with the RWOA to promote its local and global search for averting stagnation into local minima and accelerating the convergence speed in the right direction of the near-optimal solution. Experimentally, RWOA and HWOA are validated on a solar cell (RTC France) and two PV modules (Photowatt-PWP201 and Kyocera KC200GT). Further, these proposed variants are compared with five well-known parameter extraction models in order to demonstrate their notable advantages over the other existing competing algorithms for minimizing the root mean squared error (RMSE) between experimentally measured data and estimated one. The experimental findings show that RWOA is superior in some observed cases and superior in the other cases in terms of final accuracy and convergence speed; yet, HWOA is superior in all cases.

Original languageEnglish
Article number3729
Pages (from-to)1-20
Number of pages20
JournalEnergies
Volume14
Issue number13
DOIs
Publication statusPublished - 1 Jul 2021
Externally publishedYes

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