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Global analysis of optimal cleaning cycle and profit of soiling affected solar panels

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  • Mithhu, Md. Mahamudul Hasan
  • Rima, Tahmina Ahmed
  • Khan, M. Ryyan

Abstract

The photovoltaics (PV) industry is poised to capture most of the energy sector within the next few decades. As the installed PV capacity increases, even the smallest improvements on the system and operations of the solar farms can accumulate to a significant gain in revenue. One such scope is efficient mitigation of dust accumulation on panels or soiling. While installed capacities are two of the highest in Asia and around US deserts, these locations are also dust prone. The Middle East and North Africa (MENA) regions having good insolation are also highly potential candidates for PV farms with the added complexity of soiling losses. Therefore, while soiling may not be an issue in many locations over the globe, it is in fact relevant to the majority of the PV installation sites. The analysis of the effects of soiling losses on energy yield and economics are of great importance for these locations. In this work, we have extended the empirical soiling model found in the literature to include the effects of temporal variation on soiling and insolation. Our study on variation in revenue with unoptimized cleaning intervals estimates the soiling loss, which can particularly interest PV farms with accessibility issues such as agrophotovoltaic systems. We analyze the optimal cleaning cycle and corresponding normalized revenue (cash inflow normalized to the rated clean farm revenue). A numerical model is used to explain the effects under seasonal and sudden (e.g., sand storm or rain) variations in soiling and insolation. Our closed-form analytical expressions can predict the cleaning cycle and normalized revenue within 0.1% of the numerical results by using the soiling and insolation data averaged over the seasons. Finally, we discuss these results in a global scenario using our estimated world-map for soiling rates. This predicts the worldwide revenue loss under location-specific optimal cleaning cycles, assuming one of the lowest cleaning costs seen globally. In Asia and MENA regions, for example, median revenue loss due to soiling is 2.5% even after optimal cleaning every 5–6 days. This loss is 1.5% in the US for 12 days of cleaning interval. Considering region-specific cleaning costs, the revenue loss of optimally cleaned PV farm is 2%–5% for Asia, MENA, North America, and Europe.

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  • Mithhu, Md. Mahamudul Hasan & Rima, Tahmina Ahmed & Khan, M. Ryyan, 2021. "Global analysis of optimal cleaning cycle and profit of soiling affected solar panels," Applied Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:appene:v:285:y:2021:i:c:s0306261921000039
    DOI: 10.1016/j.apenergy.2021.116436
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    References listed on IDEAS

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    1. Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Rodríguez-Suanzes, C., 2022. "Analysis of the tilt and azimuth angles of photovoltaic systems in non-ideal positions for urban applications," Applied Energy, Elsevier, vol. 305(C).
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    3. Marta Redondo & Carlos A. Platero & Antonio Moset & Fernando Rodríguez & Vicente Donate, 2023. "Soiling Modelling in Large Grid-Connected PV Plants for Cleaning Optimization," Energies, MDPI, vol. 16(2), pages 1-13, January.
    4. Huang, Maoquan & Yang, Rui & Tang, G.H. & Pu, Jin Huan & Sun, Qie & Du, Mu, 2025. "Quantifying the effects of dust characteristics on the performance of radiative cooling PV systems," Applied Energy, Elsevier, vol. 377(PD).
    5. Fang, Mingyu & Qian, Weixing & Qian, Tao & Bao, Qiwei & Zhang, Haocheng & Qiu, Xiao, 2024. "DGImNet: A deep learning model for photovoltaic soiling loss estimation," Applied Energy, Elsevier, vol. 376(PB).
    6. Lucia Cattani & Paolo Cattani & Anna Magrini, 2021. "Photovoltaic Cleaning Optimization: A Simplified Theoretical Approach for Air to Water Generator (AWG) System Employment," Energies, MDPI, vol. 14(14), pages 1-17, July.
    7. Lina Alhmoud, 2023. "Why Does the PV Solar Power Plant Operate Ineffectively?," Energies, MDPI, vol. 16(10), pages 1-38, May.
    8. Micheli, Leonardo & Muller, Matthew & Theristis, Marios & Smestad, Greg P. & Almonacid, Florencia & Fernández, Eduardo F., 2024. "Quantifying the impact of inverter clipping on photovoltaic performance and soiling losses," Renewable Energy, Elsevier, vol. 225(C).
    9. Zhang, Chao & Ma, Yunfeng & Yang, Guolin & Chen, Tao, 2025. "An integrated industrial PV panel cleaning recommendation system for optimal dust removal," Applied Energy, Elsevier, vol. 377(PD).
    10. Chanchangi, Yusuf N. & Ghosh, Aritra & Micheli, Leonardo & Fernández, Eduardo F. & Sundaram, Senthilarasu & Mallick, Tapas K., 2022. "Soiling mapping through optical losses for Nigeria," Renewable Energy, Elsevier, vol. 197(C), pages 995-1008.
    11. Kaiss, El-Cheikh Amer & Hassan, Noha M., 2024. "Optimizing the cleaning frequency of solar photovoltaic (PV) systems using numerical analysis and empirical models," Renewable Energy, Elsevier, vol. 228(C).
    12. Isaacs, Stewart & Kalashnikova, Olga & Garay, Michael J. & van Donkelaar, Aaron & Hammer, Melanie S. & Lee, Huikyo & Wood, Danielle, 2023. "Dust soiling effects on decentralized solar in West Africa," Applied Energy, Elsevier, vol. 340(C).
    13. M. Ryyan Khan & Intekhab Alam & M. Rezwan Khan, 2023. "Inverter-Less Integration of Roof-Top Solar PV with Grid Connected Industrial Drives," Energies, MDPI, vol. 16(4), pages 1-14, February.
    14. Abdulla, Hind & Sleptchenko, Andrei & Nayfeh, Ammar, 2024. "Photovoltaic systems operation and maintenance: A review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).
    15. Honey Brahma & Shraiya Pant & Leonardo Micheli & Greg P. Smestad & Nabin Sarmah, 2022. "Effect of Environmental Factors on Photovoltaic Soiling: Experimental and Statistical Analysis," Energies, MDPI, vol. 16(1), pages 1-22, December.

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