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

Zakarya Ziani (), Moustafa Yassine Mahdad, Mohammed Zakaria Bessenouci, Mohammed Chakib Sekkal and Nacera Ghellai
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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
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
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
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
Nacera Ghellai: Research Unit for Materials and Renewable Energies (URMER), University of Tlemcen, BP-119, Tlemcen 13000, Algeria

Energies, 2024, vol. 17, issue 18, 1-25

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.

Keywords: multi-junction solar cells; Silvaco TCAD tools; III-V tandem solar cells; statistical modeling; layer thickness optimization; electrical yield; copper indium gallium selenide (CIGS); photovoltaic efficiency; spectral absorption; current–voltage characteristics; material engineering; renewable energy technologies; correlation coefficients (R 2 values) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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