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Optimized spectral splitting in thermo-photovoltaic system for maximum conversion efficiency

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  • Rabady, Rabi Ibrahim

Abstract

Frequency conversion of the solar spectrum in thermo-photovoltaic systems improves the sunlight conversion efficiency by two means: moving the photovoltaic conversion to a different spectrum with better response, and the ability to recycle the frequency converted photons that exhibit insufficient conversion efficiency. In this work a theoretical optimization of the thermo-photovoltaic system was attempted in order to reach maximum conversion efficiency by an optimal choice of the emitter's operating temperature and the pass band wavelengths of the optical filter that is used to reflect the inefficient frequency converted photons back to the absorber-emitter unit to be recycled. We report that our optimization model, which accounts for the power leakage from the recycling process and the thermalization losses that associate the photovoltaic conversion, predicts for promising conversion efficiencies of sunlight to electricity which is as high as 44.3% for a thermo-photovoltaic system that employs absorber-emitter unit with 70% photon recycling efficiency and photovoltaic cell with 1.6 μm cutoff wavelength and is optimized at emitter's temperature of 3045 K and optical filter passband of (0.626–1.6 μm).

Suggested Citation

  • Rabady, Rabi Ibrahim, 2017. "Optimized spectral splitting in thermo-photovoltaic system for maximum conversion efficiency," Energy, Elsevier, vol. 119(C), pages 852-859.
    • Handle: RePEc:eee:energy:v:119:y:2017:i:c:p:852-859
    DOI: 10.1016/j.energy.2016.11.055
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    References listed on IDEAS

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    1. Crisostomo, Felipe & Taylor, Robert A. & Surjadi, Desiree & Mojiri, Ahmad & Rosengarten, Gary & Hawkes, Evatt R., 2015. "Spectral splitting strategy and optical model for the development of a concentrating hybrid PV/T collector," Applied Energy, Elsevier, vol. 141(C), pages 238-246.
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    Cited by:

    1. Gao, Mingming & Li, Jianjing & Hong, Feng & Long, Dongteng, 2019. "Day-ahead power forecasting in a large-scale photovoltaic plant based on weather classification using LSTM," Energy, Elsevier, vol. 187(C).
    2. Shan, Shiquan & Huang, Huadong & Chen, Binghong & Tian, Jialu & Zhang, Yanwei & Zhou, Zhijun, 2023. "A novel oxy-enrich near-field thermophotovoltaic system for sustainable fuel: Design guidelines and thermodynamic parametric analysis," Renewable Energy, Elsevier, vol. 211(C), pages 494-507.

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