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Multi-dimensional optimization of In0.53Ga0.47As thermophotovoltaic cell using real coded genetic algorithm

Gamel MMA 1 , Ker PJ 2 , Lee HJ 3 , Rashid WESWA 1 , Hannan MA 1 , David JPR 4 Show all authors , Jamaludin MZ 3

Affiliations 

  • 1 Institute of Sustainable Energy, Universiti Tenaga Nasional, 43000, Kajang, Selangor, Malaysia
  • 2 Institute of Sustainable Energy, Universiti Tenaga Nasional, 43000, Kajang, Selangor, Malaysia. pinjern@uniten.edu.my
  • 3 Institute of Power Engineering, Universiti Tenaga Nasional, 43000, Kajang, Selangor, Malaysia
  • 4 Department of Electronic and Electrical Engineering, The University of Sheffield, Firth Court, Western Bank, Sheffield, S10 2TN, UK
Sci Rep, 2021 Apr 08;11(1):7741.
PMID: 33833263 DOI: 10.1038/s41598-021-86175-5

Abstract

The optimization of thermophotovoltaic (TPV) cell efficiency is essential since it leads to a significant increase in the output power. Typically, the optimization of In0.53Ga0.47As TPV cell has been limited to single variable such as the emitter thickness, while the effects of the variation in other design variables are assumed to be negligible. The reported efficiencies of In0.53Ga0.47As TPV cell mostly remain 

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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