High-Performance Technique for Estimating the Unknown Parameters of Photovoltaic Cells and Modules Based on Improved Spider Wasp Optimizer

Authors

Safaa Saber, Faculty of Computers and Informatics, Zagazig University, Zagazig, Sharqiyah, 44519, EgyptFollow
Sara Salem, Faculty of Computers and Informatics, Zagazig University, Zagazig, Sharqiyah 44519, EgyptFollow

ORCID

Safaa Saber: https://orcid.org/0009-0009-8019-0847

Sara Salem:https://orcid.org/0009-0008-8315-1248

Article Type

Original Article

Abstract

To better estimate the unknown parameters of the double-diode model, a new optimization technique based on the newly proposed spider wasp optimizer (SWO) is introduced in this study. The performance of SWO was further enhanced by integrating it with a local search strategy to propose a new improved variant called ISWO. This improved variant has a high ability to extensively exploit the solutions surrounding the best-so-far solution in an effort to speed up convergence and produce better results in fewer function evaluations. Using the RTC France solar cell and three PV modules (STM6-40/36, STP6-120/36, and Kyocera KC200GT), ISWO and SWO are evaluated and compared to four well-known metaheuristic optimization methods. The objective values acquired by those algorithms in thirty separate runs are examined using the Wilcoxon rank sum test and a number of performance measures. The experimental findings demonstrate ISWO's exceptional performance for every PV module under consideration.

How to Cite

Saber, Safaa and Salem, Sara (2023) "High-Performance Technique for Estimating the Unknown Parameters of Photovoltaic Cells and Modules Based on Improved Spider Wasp Optimizer," Sustainable Machine Intelligence Journal: Vol. 5: Iss. 1, Article 2.
DOI: https://doi.org/10.61185/SMIJ.2023.55102

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.