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A rolling-horizon cleaning recommendation system for dust removal of industrial PV panels

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  • Zhang, Chao
  • Ma, Yunfeng
  • Mi, Zengqiang
  • Yang, Fan
  • Zhang, Long

Abstract

Periodic cleaning of photovoltaic (PV) panels, such as every three months, is a common industry practice. However, this fixed period may not be optimal for maximizing the profit of a PV power generation system, due to numerous time-variant influencing factors, such as weather, temperature, etc. To increase the overall profit of a solar farm, it is highly desirable to have a flexible cleaning schedule that considers time-variant influencing factors. For this requirement, a rolling-horizon cleaning recommendation system is presented in this paper. Within this cleaning recommendation system, a prediction model and profit model are proposed. The prediction model, called the ensemble long-term and nonlinear autoregressive, can provide a time-variant future horizon by analyzing and compressing the time-variant characteristics in historical information. The profit model based on mathematical constraints, can process time-variant future horizon output from prediction model to generate a flexible optimized recommendation for cleaning schedule. The effectiveness of the proposed system is validated in real farms and all data used in this paper is collected from real world. The two case studies in experiments show that the profit improvement can reach up to 6% and 30%, respectively.

Suggested Citation

  • Zhang, Chao & Ma, Yunfeng & Mi, Zengqiang & Yang, Fan & Zhang, Long, 2024. "A rolling-horizon cleaning recommendation system for dust removal of industrial PV panels," Applied Energy, Elsevier, vol. 353(PB).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pb:s0306261923015325
    DOI: 10.1016/j.apenergy.2023.122168
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    1. Tao, Jacqueline Yujia & Finenko, Anton, 2016. "Moving beyond LCOE: impact of various financing methods on PV profitability for SIDS," Energy Policy, Elsevier, vol. 98(C), pages 749-758.
    2. Mani, Monto & Pillai, Rohit, 2010. "Impact of dust on solar photovoltaic (PV) performance: Research status, challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3124-3131, December.
    3. Gebara, C.H. & Laurent, A., 2023. "National SDG-7 performance assessment to support achieving sustainable energy for all within planetary limits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    4. Prasad, Ravita D. & Bansal, R.C. & Raturi, Atul, 2014. "Multi-faceted energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 686-699.
    5. Salinas, David & Flunkert, Valentin & Gasthaus, Jan & Januschowski, Tim, 2020. "DeepAR: Probabilistic forecasting with autoregressive recurrent networks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1181-1191.
    6. Talavera, D.L. & Muñoz-Cerón, E. & Ferrer-Rodríguez, J.P. & Nofuentes, G., 2016. "Evolution of the cost and economic profitability of grid-connected PV investments in Spain: Long-term review according to the different regulatory frameworks approved," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 233-247.
    7. Prema, V. & Rao, K. Uma, 2015. "Development of statistical time series models for solar power prediction," Renewable Energy, Elsevier, vol. 83(C), pages 100-109.
    8. El-Shobokshy, Mohammad S. & Hussein, Fahmy M., 1993. "Degradation of photovoltaic cell performance due to dust deposition on to its surface," Renewable Energy, Elsevier, vol. 3(6), pages 585-590.
    9. Zakeri, Behnam & Cross, Samuel & Dodds, Paul.E. & Gissey, Giorgio Castagneto, 2021. "Policy options for enhancing economic profitability of residential solar photovoltaic with battery energy storage," Applied Energy, Elsevier, vol. 290(C).
    10. Marzouq, Manal & El Fadili, Hakim & Zenkouar, Khalid & Lakhliai, Zakia & Amouzg, Mohammed, 2020. "Short term solar irradiance forecasting via a novel evolutionary multi-model framework and performance assessment for sites with no solar irradiance data," Renewable Energy, Elsevier, vol. 157(C), pages 214-231.
    11. Zheng, Jianqin & Zhang, Haoran & Dai, Yuanhao & Wang, Bohong & Zheng, Taicheng & Liao, Qi & Liang, Yongtu & Zhang, Fengwei & Song, Xuan, 2020. "Time series prediction for output of multi-region solar power plants," Applied Energy, Elsevier, vol. 257(C).
    12. Lu, Hao & Lu, Lin & Wang, Yuanhao, 2016. "Numerical investigation of dust pollution on a solar photovoltaic (PV) system mounted on an isolated building," Applied Energy, Elsevier, vol. 180(C), pages 27-36.
    13. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    14. Qing, Xiangyun & Niu, Yugang, 2018. "Hourly day-ahead solar irradiance prediction using weather forecasts by LSTM," Energy, Elsevier, vol. 148(C), pages 461-468.
    15. Chow, T.T., 2010. "A review on photovoltaic/thermal hybrid solar technology," Applied Energy, Elsevier, vol. 87(2), pages 365-379, February.
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