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Transient real-weather 4E optimization of two-stage segmented thermoelectric generators for enhanced solar energy conversion

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  • Maduabuchi, Chika
  • Okoli, Kingsley

Abstract

As global energy demands rise, this study introduces a novel approach to thermoelectric generator (TEG) modeling and optimization. We pioneer the optimization of Two-stage Segmented TEGs (TSSTEGs) for concentrated solar energy conversion under transient real-weather conditions, employing stage geometry ratios to capture real-world dynamics. The optimization focuses on four geometric parameters: height ratio, stage cross-sectional area ratio, stage skutterudite ratio, and intermediate alumina height. The optimal height ratio of 2.33 led to a power output of 22.43 W, exergy efficiency of 11.25%, and CO2 savings of 10.65 kg/year. Similarly, a stage cross-sectional area ratio of 0.50 and a stage skutterudite ratio of 0.49 produced significant improvements. Notably, the optimized TSSTEG module achieved a 62.39% increase in power output and 27.52% increase in exergy efficiency under steady-state conditions compared to unoptimized modules. Under transient real-weather conditions, the optimized module surpassed the unoptimized module by 6.67% in power output, 22.5% in efficiency, 6.60% in CO2 savings, and 14.6% in dollars per watt. This groundbreaking approach advances TEG optimization and contributes to sustainable energy solutions, aligning with the United Nations' Sustainable Development Goals. By addressing transient weather conditions and optimizing geometric parameters, this study represents a significant step towards higher efficiency and sustainability in thermoelectric generators.

Suggested Citation

  • Maduabuchi, Chika & Okoli, Kingsley, 2024. "Transient real-weather 4E optimization of two-stage segmented thermoelectric generators for enhanced solar energy conversion," Applied Energy, Elsevier, vol. 373(C).
    • Handle: RePEc:eee:appene:v:373:y:2024:i:c:s0306261924012649
    DOI: 10.1016/j.apenergy.2024.123881
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    References listed on IDEAS

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    5. Chika Maduabuchi & Hassan Fagehi & Ibrahim Alatawi & Mohammad Alkhedher, 2022. "Predicting the Optimal Performance of a Concentrated Solar Segmented Variable Leg Thermoelectric Generator Using Neural Networks," Energies, MDPI, vol. 15(16), pages 1-25, August.
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