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Design of Selective TPV Thermal Emitters Based on Bayesian Optimization Nesting Simulated Annealing

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  • Zejia Liu

    (School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China
    These authors contributed equally to this work.)

  • Zigui Zhang

    (School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China
    These authors contributed equally to this work.)

  • Peifeng Xie

    (School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China
    These authors contributed equally to this work.)

  • Zibo Miao

    (School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China)

Abstract

It is vital to further improve the design of TPV thermal emitters since the energy efficiency of thermophotovoltaic (TPV) systems is still not adequately high. In this paper, we propose a novel evaluator for the optimization of TPV thermal emitters, namely the percentage of effective figure (PEF) to replace the figure of merit (FOM). The associated algorithm, Bayesian optimization nesting simulated annealing (BOnSA), is developed to achieve better performance. By searching throughout the whole parameter space and then optimizing in a reduced space, BOnSA can lead to a satisfactory solution numerically for GaSb photovoltaic (PV) cells. When designing the emitter, the aperiodic material structure with an anti-reflection substructure and Fabry–Perot etalon is constructed from the material candidates. In particular, one of the optimal structures determined by BOnSA is {SiO 2 , ZnS, Ge, MgF 2 , W, Si, SiO 2 , W} with the value of PEF = 0.822 , which is better than the previous work by comparison. Moreover, by applying BOnSA to various structures, we have obtained higher values of PEF with less time cost, which thus verifies the efficiency and scalability of BOnSA. The results of our paper show that BOnSA provides an effective approach to the thickness optimization problem and that BOnSA is applicable in other relevant scenarios.

Suggested Citation

  • Zejia Liu & Zigui Zhang & Peifeng Xie & Zibo Miao, 2022. "Design of Selective TPV Thermal Emitters Based on Bayesian Optimization Nesting Simulated Annealing," Energies, MDPI, vol. 16(1), pages 1-16, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:416-:d:1019438
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    References listed on IDEAS

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    1. Fekadu Tolessa Maremi & Namkyu Lee & Geehong Choi & Taehwan Kim & Hyung Hee Cho, 2018. "Design of Multilayer Ring Emitter Based on Metamaterial for Thermophotovoltaic Applications," Energies, MDPI, vol. 11(9), pages 1-9, August.
    2. Eglese, R. W., 1990. "Simulated annealing: A tool for operational research," European Journal of Operational Research, Elsevier, vol. 46(3), pages 271-281, June.
    3. Akhtar, Saad & Khan, Mohammed N. & Kurnia, Jundika C. & Shamim, Tariq, 2017. "Investigation of energy conversion and flame stability in a curved micro-combustor for thermo-photovoltaic (TPV) applications," Applied Energy, Elsevier, vol. 192(C), pages 134-145.
    4. Laird, Frank N. & Stefes, Christoph, 2009. "The diverging paths of German and United States policies for renewable energy: Sources of difference," Energy Policy, Elsevier, vol. 37(7), pages 2619-2629, July.
    5. Koulamas, C & Antony, SR & Jaen, R, 1994. "A survey of simulated annealing applications to operations research problems," Omega, Elsevier, vol. 22(1), pages 41-56, January.
    6. Akhtar, Saad & Kurnia, Jundika C. & Shamim, Tariq, 2015. "A three-dimensional computational model of H2–air premixed combustion in non-circular micro-channels for a thermo-photovoltaic (TPV) application," Applied Energy, Elsevier, vol. 152(C), pages 47-57.
    7. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
    8. Han, Jun & Lu, Lin & Yang, Hongxing, 2010. "Numerical evaluation of the mixed convective heat transfer in a double-pane window integrated with see-through a-Si PV cells with low-e coatings," Applied Energy, Elsevier, vol. 87(11), pages 3431-3437, November.
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