Research Article

Predictions on Flexible CdTe Solar Cell Performances by Artificial Neural Networks

Volume: 44 Number: 4 December 28, 2023
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Predictions on Flexible CdTe Solar Cell Performances by Artificial Neural Networks

Abstract

CdTe solar cells on ultra-thin glass substrates are light and flexible. Flexible cells are widely preferred modules in technological fields. The flexibility of these cells enables them to cope with deformations. The efficiency of these has reached 19%. In this work, we used artificial neural network (ANN) method for the determination the performance of flexible CdTe solar cells despite bending and time. The performances of the solar cell before and after bending have been predicted. According to the results from the ANN calculations using the experimental data in the literature, MSE values of ANN estimates range from 0.06% to 0.28%.

Keywords

References

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Details

Primary Language

English

Subjects

Atomic, Molecular and Optical Physics (Other)

Journal Section

Research Article

Authors

Sevinj Ganbarova
0009-0004-0913-0060
Azerbaijan

Vusal Mamedov
0009-0007-8084-3436
Azerbaijan

Huseyn Mamedov
0000-0002-9980-9189
Azerbaijan

Publication Date

December 28, 2023

Submission Date

June 9, 2023

Acceptance Date

October 2, 2023

Published in Issue

Year 2023 Volume: 44 Number: 4

DOI

https://doi.org/10.17776/csj.1312021

IZ

https://izlik.org/JA44GP45LC

Cite

RIS / Bibtex
APA
Ganbarova, S., Akkoyun, S., Mamedov, V., & Mamedov, H. (2023). Predictions on Flexible CdTe Solar Cell Performances by Artificial Neural Networks. Cumhuriyet Science Journal, 44(4), 768-774. https://doi.org/10.17776/csj.1312021

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