Optimal Parameter Identification of Perovskite Solar Cells Using Modified Bald Eagle Search Optimization Algorithm

Abdul Ghani Olabi; Hegazy Rezk; Mohammad Ali Abdelkareem; Tabbi Awotwe; Hussein M. Maghrabie; Fatahallah Freig Selim; Shek Mohammod Atiqure Rahman; Sheikh Khaleduzzaman Shah; Alaa A. Zaky

doi:10.3390/en16010471

Optimal Parameter Identification of Perovskite Solar Cells Using Modified Bald Eagle Search Optimization Algorithm

Abdul Ghani Olabi^*, Hegazy Rezk, Mohammad Ali Abdelkareem, Tabbi Awotwe, Hussein M. Maghrabie, Fatahallah Freig Selim, Shek Mohammod Atiqure Rahman, Sheikh Khaleduzzaman Shah, Alaa A. Zaky

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, a modified bald eagle search optimization algorithm was applied for the first time to determine the parameters of the triple diode model (TDM) of perovskite solar cells (PSCs). Two experimental datasets are considered; the first is measured I–V points for a PSC at standard conditions. The second consists of the measured I–V points for a modified PSC. In contrast, the cost function to be minimized is the root mean square error (RMSE) between the experimental dataset and the calculated one. To prove the superiority of modified bald eagle search optimization (mBES), a comparison with the original bald eagle search optimization (BES), particle swarm optimizer (PSO), Hunger games search (HGS), and recent Coronavirus Disease Optimization Algorithm (COVIDOA) was implemented. Furthermore, statistical analysis of ANOVA and Tukey tests was performed. The results demonstrate the lead of the recommended mBES in identifying the parameters of the TDM for PSCs, where the RMSE achieved the least value among the used optimization algorithms in this study.

Original language	English
Article number	471
Number of pages	14
Journal	Energies
Volume	16
Issue number	1
DOIs	https://doi.org/10.3390/en16010471
Publication status	Published - 1 Jan 2023

Bibliographical note

Funding Information:
This work was supported by the [University of Sharjah], Project No. [19020406129].

Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Keywords

bald eagle search
perovskite solar cell
triple diode model

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optimal parameter identification
Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/4.0/).
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Cite this

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title = "Optimal Parameter Identification of Perovskite Solar Cells Using Modified Bald Eagle Search Optimization Algorithm",

abstract = "In this paper, a modified bald eagle search optimization algorithm was applied for the first time to determine the parameters of the triple diode model (TDM) of perovskite solar cells (PSCs). Two experimental datasets are considered; the first is measured I–V points for a PSC at standard conditions. The second consists of the measured I–V points for a modified PSC. In contrast, the cost function to be minimized is the root mean square error (RMSE) between the experimental dataset and the calculated one. To prove the superiority of modified bald eagle search optimization (mBES), a comparison with the original bald eagle search optimization (BES), particle swarm optimizer (PSO), Hunger games search (HGS), and recent Coronavirus Disease Optimization Algorithm (COVIDOA) was implemented. Furthermore, statistical analysis of ANOVA and Tukey tests was performed. The results demonstrate the lead of the recommended mBES in identifying the parameters of the TDM for PSCs, where the RMSE achieved the least value among the used optimization algorithms in this study.",

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Optimal Parameter Identification of Perovskite Solar Cells Using Modified Bald Eagle Search Optimization Algorithm

Abstract

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Keywords

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