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Lowest-threshold solar laser operation under cloudy sky condition

Author

Listed:
  • Garcia, Dário
  • Liang, Dawei
  • Almeida, Joana
  • Catela, Miguel
  • Costa, Hugo
  • Tibúrcio, Bruno D.
  • Guillot, Emmanuel
  • Vistas, Cláudia R.

Abstract

Classical solar-pumped lasers often demand a significant amount of concentrated solar power for laser emission, which is only attainable under clear sky condition, limiting their applicability. In this research, we report the first solar laser emission at very low threshold solar power under cloudy sky condition by end-side-pumping a 2.5 mm diameter, 25 mm length Ce:Nd:YAG rod at the focus of a parabolic mirror concentrator. The Ce:Nd:YAG solar laser performance was also evaluated under clear sky condition for comparison. Low threshold pump power of 32.4 W for continuous-wave solar-pumped laser was obtained under clear sky condition, being two times lower than the previous record. However, the cloud-filtered infrared sunlight enabled notable improvements in the solar laser performance by lessening the thermal lensing effects in the laser medium. The threshold pump power was further reduced to 29.2 W and maximum solar laser output of 14 W was successfully measured. This nearly doubled the focal slope efficiency from 4.03% during clear weather to 7.71% under a cloudy sky. The solar-to-laser conversion efficiency of 6.32% was nearly tripled compared to the 2.32% on a clear sky, while the solar laser conversion efficiency of 21.47 W/m2 was nearly twice the value of 12.62 W/m2 obtained on a clear day. This demonstrates that a cloudy environment could be an asset for solar laser research.

Suggested Citation

  • Garcia, Dário & Liang, Dawei & Almeida, Joana & Catela, Miguel & Costa, Hugo & Tibúrcio, Bruno D. & Guillot, Emmanuel & Vistas, Cláudia R., 2023. "Lowest-threshold solar laser operation under cloudy sky condition," Renewable Energy, Elsevier, vol. 210(C), pages 127-133.
    • Handle: RePEc:eee:renene:v:210:y:2023:i:c:p:127-133
    DOI: 10.1016/j.renene.2023.03.124
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    References listed on IDEAS

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    1. Nespoli, Alfredo & Niccolai, Alessandro & Ogliari, Emanuele & Perego, Giovanni & Collino, Elena & Ronzio, Dario, 2022. "Machine Learning techniques for solar irradiation nowcasting: Cloud type classification forecast through satellite data and imagery," Applied Energy, Elsevier, vol. 305(C).
    2. Cheng, Hsu-Yung, 2017. "Cloud tracking using clusters of feature points for accurate solar irradiance nowcasting," Renewable Energy, Elsevier, vol. 104(C), pages 281-289.
    3. Rodríguez-Benítez, Francisco J. & López-Cuesta, Miguel & Arbizu-Barrena, Clara & Fernández-León, María M. & Pamos-Ureña, Miguel Á. & Tovar-Pescador, Joaquín & Santos-Alamillos, Francisco J. & Pozo-Váz, 2021. "Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery," Applied Energy, Elsevier, vol. 292(C).
    4. Joana Almeida & Dawei Liang & Dário Garcia & Bruno D. Tibúrcio & Hugo Costa & Miguel Catela & Emmanuel Guillot & Cláudia R. Vistas, 2022. "40 W Continuous Wave Ce:Nd:YAG Solar Laser through a Fused Silica Light Guide," Energies, MDPI, vol. 15(11), pages 1-10, May.
    5. Cláudia R. Vistas & Dawei Liang & Dário Garcia & Miguel Catela & Bruno D. Tibúrcio & Hugo Costa & Emmanuel Guillot & Joana Almeida, 2022. "Uniform and Non-Uniform Pumping Effect on Ce:Nd:YAG Side-Pumped Solar Laser Output Performance," Energies, MDPI, vol. 15(10), pages 1-12, May.
    6. Li, Mengying & Chu, Yinghao & Pedro, Hugo T.C. & Coimbra, Carlos F.M., 2016. "Quantitative evaluation of the impact of cloud transmittance and cloud velocity on the accuracy of short-term DNI forecasts," Renewable Energy, Elsevier, vol. 86(C), pages 1362-1371.
    7. Dário Garcia & Dawei Liang & Cláudia R. Vistas & Hugo Costa & Miguel Catela & Bruno D. Tibúrcio & Joana Almeida, 2022. "Ce:Nd:YAG Solar Laser with 4.5% Solar-to-Laser Conversion Efficiency," Energies, MDPI, vol. 15(14), pages 1-15, July.
    8. Stavros-Andreas Logothetis & Vasileios Salamalikis & Bijan Nouri & Jan Remund & Luis F. Zarzalejo & Yu Xie & Stefan Wilbert & Evangelos Ntavelis & Julien Nou & Niels Hendrikx & Lennard Visser & Manaji, 2022. "Solar Irradiance Ramp Forecasting Based on All-Sky Imagers," Energies, MDPI, vol. 15(17), pages 1-17, August.
    9. Tzoumanikas, P. & Nikitidou, E. & Bais, A.F. & Kazantzidis, A., 2016. "The effect of clouds on surface solar irradiance, based on data from an all-sky imaging system," Renewable Energy, Elsevier, vol. 95(C), pages 314-322.
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    1. Dário Garcia & Dawei Liang & Joana Almeida & Miguel Catela & Hugo Costa & Bruno D. Tibúrcio & Emmanuel Guillot & Cláudia R. Vistas, 2023. "Efficient Production of Doughnut-Shaped Ce:Nd:YAG Solar Laser Beam," Sustainability, MDPI, vol. 15(18), pages 1-16, September.

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