An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels

Musa Balcı; Andaç Fındıkçı; Mustafa Yasin Erten; Hüseyin Aydilek

doi:10.5152/tepes.2025.25020

An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels

Abstract

Solar energy plays a pivotal role in renewable energy systems; however, dust accumulation on photovoltaic panels substantially reduces energy production efficiency. Manual cleaning methods at large-scale plants are costly and impractical, highlighting the need for automated detection techniques. This study presents a novel image processing and deep learning-based approach to accurately detect dusty PV panels. Images underwent preprocessing, including Hue, Saturation, Value color space conversion, and morphological operations to precisely segment dust-affected regions. Individual performances of DenseNet169, Xception, and InceptionV3 models were evaluated, and an ensemble model—Deep Solar Ensemble—was developed via soft voting. Experimental results demonstrated that the proposed ensemble achieved a superior classification accuracy of 97.02%, a precision of 97.29%, a recall of 96.56%, and an F1 score of 96.92% on a binary classification task. To address real-world applicability and robustness, the study was extended to include comparisons with lightweight architectures and testing on a more diverse, multi-class dataset containing various fault types, where the ensemble continued to show robust performance. The proposed methodology offers significant potential for automating solar panel maintenance, thereby enhancing operational efficiency, while also considering the tradeoffs between accuracy and computational cost for practical deployment.

Keywords

References

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Details

Primary Language

English

Subjects

Photovoltaic Power Systems

Journal Section

Research Article

Authors

Musa Balcı
0009-0001-8539-8083
Türkiye

Andaç Fındıkçı
0009-0006-4789-6029
Türkiye

Mustafa Yasin Erten ^*
0000-0002-5140-1213
Türkiye

Hüseyin Aydilek
0000-0003-3051-4259
Türkiye

Publication Date

February 27, 2026

Submission Date

June 10, 2025

Acceptance Date

August 5, 2025

Published in Issue

Year 2026 Volume: 6 Number: 1

DOI

https://doi.org/10.5152/tepes.2025.25020

IZ

https://izlik.org/JA45GX56DS

Cite

RIS / Bibtex

APA

Balcı, M., Fındıkçı, A., Erten, M. Y., & Aydilek, H. (2026). An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels. Turkish Journal of Electrical Power and Energy Systems, 6(1), 1-12. https://doi.org/10.5152/tepes.2025.25020

AMA

1.Balcı M, Fındıkçı A, Erten MY, Aydilek H. An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels. TEPES. 2026;6(1):1-12. doi:10.5152/tepes.2025.25020

Chicago

Balcı, Musa, Andaç Fındıkçı, Mustafa Yasin Erten, and Hüseyin Aydilek. 2026. “An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels”. Turkish Journal of Electrical Power and Energy Systems 6 (1): 1-12. https://doi.org/10.5152/tepes.2025.25020.

EndNote

Balcı M, Fındıkçı A, Erten MY, Aydilek H (February 1, 2026) An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels. Turkish Journal of Electrical Power and Energy Systems 6 1 1–12.

IEEE

[1]M. Balcı, A. Fındıkçı, M. Y. Erten, and H. Aydilek, “An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels”, TEPES, vol. 6, no. 1, pp. 1–12, Feb. 2026, doi: 10.5152/tepes.2025.25020.

ISNAD

Balcı, Musa - Fındıkçı, Andaç - Erten, Mustafa Yasin - Aydilek, Hüseyin. “An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels”. Turkish Journal of Electrical Power and Energy Systems 6/1 (February 1, 2026): 1-12. https://doi.org/10.5152/tepes.2025.25020.

JAMA

1.Balcı M, Fındıkçı A, Erten MY, Aydilek H. An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels. TEPES. 2026;6:1–12.

MLA

Balcı, Musa, et al. “An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels”. Turkish Journal of Electrical Power and Energy Systems, vol. 6, no. 1, Feb. 2026, pp. 1-12, doi:10.5152/tepes.2025.25020.

Vancouver

1.Musa Balcı, Andaç Fındıkçı, Mustafa Yasin Erten, Hüseyin Aydilek. An Ensemble-Based Deep Learning Framework for Efficient Soiling Detection on Photovoltaic Panels. TEPES. 2026 Feb. 1;6(1):1-12. doi:10.5152/tepes.2025.25020