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Enhancing Multi-Junction Solar Cell Performance: Advanced Predictive Modeling and Cutting-Edge CIGS Integration Techniques

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  • Zakarya Ziani

    (Laboratory for the Sustainable Management of Natural Resources in Arid and Semi-Arid Zones, University Center Salhi Ahmed, BP-66, Naama 45000, Algeria
    Research Unit for Materials and Renewable Energies (URMER), University of Tlemcen, BP-119, Tlemcen 13000, Algeria
    Department of SNV, Institute of Sciences, University Center of Salhi Ahmed Naama, BP-66, Naama 45000, Algeria)

  • Moustafa Yassine Mahdad

    (Laboratory for the Sustainable Management of Natural Resources in Arid and Semi-Arid Zones, University Center Salhi Ahmed, BP-66, Naama 45000, Algeria
    Laboratory of Applied Genetic in Agriculture, Ecology and Public Health, Department of Biology, Faculty of SNV/STU, Tlemcen University, Tlemcen 13000, Algeria)

  • Mohammed Zakaria Bessenouci

    (Laboratory for the Sustainable Management of Natural Resources in Arid and Semi-Arid Zones, University Center Salhi Ahmed, BP-66, Naama 45000, Algeria
    Research Unit for Materials and Renewable Energies (URMER), University of Tlemcen, BP-119, Tlemcen 13000, Algeria
    Department of Mechanical Engineering, Institute of Technology, University Center of Salhi Ahmed, BP-66, Naama 45000, Algeria)

  • Mohammed Chakib Sekkal

    (Laboratory for the Sustainable Management of Natural Resources in Arid and Semi-Arid Zones, University Center Salhi Ahmed, BP-66, Naama 45000, Algeria
    Department of Electrical Engineering, Institute of Technology, University Center of Salhi Ahmed, BP-66, Naama 45000, Algeria)

  • Nacera Ghellai

    (Research Unit for Materials and Renewable Energies (URMER), University of Tlemcen, BP-119, Tlemcen 13000, Algeria)

Abstract

Historically, multi-junction solar cells have evolved to capture a broader spectrum of sunlight, significantly enhancing efficiency beyond conventional solar technologies. In this study, we utilized Silvaco TCAD tools to optimize a five-junction solar cell composed of AlInP, AlGaInP, AlGaInAs, GaInP, GaAs, InGaAs, and Ge, drawing on advancements documented in the literature. Our research focused on optimizing these cells through sophisticated statistical modeling and material innovation, particularly examining the relationship between layer thickness and electrical yield under one sun illumination. Employing III-V tandem solar cells, renowned for their superior efficiency in converting sunlight to electricity, we applied advanced statistical models to a reference solar cell configured with predefined layer thicknesses. Our analysis revealed significant positive correlations between layer thickness and electrical performance, with correlation coefficients (R 2 values) impressively ranging from 0.86 to 0.96 across different regions. This detailed statistical insight led to an improvement in overall cell efficiency to 44.2. A key innovation in our approach was replacing the traditional germanium (Ge) substrate with Copper Indium Gallium Selenide (CIGS), known for its adjustable bandgap and superior absorption of long-wavelength photons. This strategic modification not only broadened the absorption spectrum but also elevated the overall cell efficiency to 47%. Additionally, the optimization process involved simulations using predictive profilers and Silvaco Atlas tools, which systematically assessed various configurations for their spectral absorption and current–voltage characteristics, further enhancing the cell’s performance. These findings underscore the critical role of precise material engineering and sophisticated statistical analyses in advancing solar cell technology, setting new efficiency benchmarks, and driving further developments in the field.

Suggested Citation

  • Zakarya Ziani & Moustafa Yassine Mahdad & Mohammed Zakaria Bessenouci & Mohammed Chakib Sekkal & Nacera Ghellai, 2024. "Enhancing Multi-Junction Solar Cell Performance: Advanced Predictive Modeling and Cutting-Edge CIGS Integration Techniques," Energies, MDPI, vol. 17(18), pages 1-25, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4669-:d:1481233
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    References listed on IDEAS

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    1. Wang, Xiao-Lei & Zhao, Yu-Na & Yang, Jian-Feng & Liu, Min-Qian, 2017. "Construction of (nearly) orthogonal sliced Latin hypercube designs," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 174-180.
    2. Ifigenia Efthimiou & Stelios Georgiou & Min-Qian Liu, 2015. "Construction of nearly orthogonal Latin hypercube designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(1), pages 45-57, January.
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