A Modified Triple-Diode Model Parameters Identification for Perovskite Solar Cells via Nature-Inspired Search Optimization Algorithms

Alaa A. Zaky, Ahmed Fathy, Hegazy Rezk, Konstantina Gkini, Polycarpos Falaras and Amlak Abaza
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Alaa A. Zaky: Electrical Engineering Department, Kafrelsheikh University, Kafr El-Sheikh 33511, Egypt
Ahmed Fathy: Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
Hegazy Rezk: Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61517, Egypt
Konstantina Gkini: National Centre for Scientific Research “Demokritos”, Institute of Nanoscience and Nanotechnology, Agia Paraskevi Attikis, 15341 Athens, Greece
Polycarpos Falaras: National Centre for Scientific Research “Demokritos”, Institute of Nanoscience and Nanotechnology, Agia Paraskevi Attikis, 15341 Athens, Greece
Amlak Abaza: Electrical Engineering Department, Kafrelsheikh University, Kafr El-Sheikh 33511, Egypt

Sustainability, 2021, vol. 13, issue 23, 1-22

Abstract: Recently, perovskite solar cells (PSCs) have been widely investigated as an efficient alternative for silicon solar cells. In this work, a proposed modified triple-diode model (MTDM) for PSCs modeling and simulation was used. The Bald Eagle Search (BES) algorithm, which is a novel nature-inspired search optimizer, was suggested for solving the model and estimating the PSCs device parameters because of the complex nature of determining the model parameters. Two PSC architectures, namely control and modified devices, were experimentally fabricated, characterized and tested in the lab. The I–V datasets of the fabricated devices were recorded at standard conditions. The decision variables in the proposed optimization process are the nine and ten unknown parameters of triple-diode model (TDM) and MTDM, respectively. The direct comparison with a number of modern optimization techniques including grey wolf (GWO), particle swarm (PSO) and moth flame (MFO) optimizers, as well as sine cosine (SCA) and slap swarm (SSA) algorithms, confirmed the superiority of the proposed BES approach, where the Root Mean Square Error ( RMSE ) objective function between the experimental data and estimated characteristics achieves the least value.

Keywords: perovskite solar cells; triple-diode model; optimization; energy efficiency (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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