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Performance optimization and thermodynamic analysis of irreversibility in a contemporary solar thermoelectric generator

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  • Maduabuchi, Chika C.
  • Ejenakevwe, Kevwe A.
  • Mgbemene, Chigbo A.

Abstract

In this paper, a model based on the first and second laws of thermodynamics is developed in MATLAB R2020a Simulink software and is utilized in thermodynamically optimizing a bismuth telluride based solar thermoelectric generator (STEG) while estimating all system irreversibilities. This study aims at presenting a cheaper and simpler method of optimizing the performance of traditional STEGs without using segmentation or cascading. This is achieved by studying the effects of operating thermal and electric parameters such as load-resistance ratio (LRR), optical concentration ratio (OCR), thermal concentration ratio (TCR), hot junction temperature (Th), cold junction temperature, current and voltage on STEG power output, energy and exergy efficiencies, respectively. The results obtained are validated with experimental and numerical data from previous studies. Results indicate that for an OCR of 30, a STEG exergy efficiency of about 6.5% is obtained from a conventional bismuth-telluride single-stage module. Also, a means of maximising STEG performance while reducing system irreversibilities to the barest minimum is presented. The results obtained herein will provide useful information in the maximisation of conventional and complex STEG systems employing segmentation or cascading.

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  • Maduabuchi, Chika C. & Ejenakevwe, Kevwe A. & Mgbemene, Chigbo A., 2021. "Performance optimization and thermodynamic analysis of irreversibility in a contemporary solar thermoelectric generator," Renewable Energy, Elsevier, vol. 168(C), pages 1189-1206.
    • Handle: RePEc:eee:renene:v:168:y:2021:i:c:p:1189-1206
    DOI: 10.1016/j.renene.2020.12.130
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    References listed on IDEAS

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    Cited by:

    1. Shi, Zijie & Zhang, Kai & Jiang, Kaiyu & Li, Haoran & Ye, Peiliang & Yang, Haibin & Mahian, Omid, 2023. "Maximizing energy generation: A study of radiative cooling-based thermoelectric power devices," Energy, Elsevier, vol. 274(C).
    2. Maduabuchi, Chika, 2022. "Thermo-mechanical optimization of thermoelectric generators using deep learning artificial intelligence algorithms fed with verified finite element simulation data," Applied Energy, Elsevier, vol. 315(C).
    3. Hong, Bing-Hua & Huang, Xiao-Yan & He, Jian-Wei & Cai, Yang & Wang, Wei-Wei & Zhao, Fu-Yun, 2023. "Round-the-clock performance of solar thermoelectric wall with phase change material in subtropical climate: Critical analysis and parametric investigations," Energy, Elsevier, vol. 272(C).
    4. Yu, Gang & He, Lipeng & Wang, Hongxin & Sun, Lei & Zhang, Zhonghua & Cheng, Guangming, 2023. "Research of rotating piezoelectric energy harvester for automotive motion," Renewable Energy, Elsevier, vol. 211(C), pages 484-493.

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