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Multi-objective optimization of a novel photovoltaic-thermoelectric generator system based on hybrid enhanced algorithm

Author

Listed:
  • Zhao, Ru
  • Zhu, Na
  • Zhao, Xudong
  • Luo, Zhenyu
  • Chang, Jianpei

Abstract

To address low efficiency of traditional photovoltaic-thermoelectric generator (PV-TEG) systems, a novel PV-MCHP-PCM-TEG system was proposed. In this study, waste heat from back of PV cells is transferred to the hot side of TEG modules via a microchannel heat pipe (MHCP), while phase change material (PCM) is incorporated for thermal storage to extend operating time of TEG modules without solar radiation. The electrical efficiency and total life cycle cost were defined as multi-objective functions, and a comprehensive analysis, including sensitivity analysis and system optimization, was conducted to achieve global optimization over the entire life cycle. The mathematical model of PV-MCHP-PCM-TEG system was developed and experimentally validated in Wuhan, China. Sensitive factors, including PV reference efficiency, quantity of TEG modules, thickness of inner and outer PCM plates, and melting temperatures of PCM plates, were identified using Sobol global sensitivity analysis and subsequently optimized using the Non-dominated Sorting Genetic Algorithm II coupled with Multi-Objective Particle Swarm Optimization (NSGA II-MOPSO) algorithm. After determining weights of the two objectives using entropy weighting method, Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) solution indicated that optimal electrical efficiency reached 25.6 %, while the minimum total life cycle cost was 335.4 CNY.

Suggested Citation

  • Zhao, Ru & Zhu, Na & Zhao, Xudong & Luo, Zhenyu & Chang, Jianpei, 2025. "Multi-objective optimization of a novel photovoltaic-thermoelectric generator system based on hybrid enhanced algorithm," Energy, Elsevier, vol. 319(C).
    • Handle: RePEc:eee:energy:v:319:y:2025:i:c:s0360544225006887
    DOI: 10.1016/j.energy.2025.135046
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