Determination of thermal emission spectra maximizing thermophotovoltaic performance using a genetic algorithm

作者：DeSutter John^*; Bernardi Michael P; Francoeur Mathieu^*

来源：Energy Conversion and Management, 2016, 108: 429-438.

DOI：10.1016/j.enconman.2015.11.029

• Thermophotovoltaic power generation
• Optimal emission spectrum
• Thermal impacts
• Genetic algorithm

Optimal radiator thermal emission spectra maximizing thermophotovoltaic (TPV) conversion efficiency and output power density are determined when thermal effects in the cell are considered. For this purpose, a framework is designed in which a TPV model that accounts for radiative, electrical and thermal losses is coupled with a genetic algorithm. The TPV device under study involves a spectrally selective radiator at a temperature of 2000 K, a gallium antimonide cell, and a cell thermal management system characterized by a fluid temperature and a heat transfer coefficient of 293 K and 600 Wm(-2) K-1. It is shown that a maximum conversion efficiency of 38.8% is achievable with an emission spectrum that has emissivity of unity between 0.719 eV and 0.763 eV and zero elsewhere. This optimal spectrum is less than half of the width of the spectra obtained when thermal losses in the cell are neglected. A maximum output power density of 41,708 Wm(-2) is achievable with a radiator spectrum having emissivity values of unity between 0.684 eV and 1.082 eV and zero elsewhere when thermal losses are accounted for. These emission spectra are shown to greatly outperform blackbody and tungsten radiators, and could be obtained using artificial structures such as metamaterials or photonic crystals.

• 出版日期2016-1-15