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Transient response of a thermoelectric generator to load steps under constant heat flux

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  • Torrecilla, Marcos Compadre
  • Montecucco, Andrea
  • Siviter, Jonathan
  • Strain, Andrew
  • Knox, Andrew R.

Abstract

Most waste heat recovery applications involve a heat source that provides a limited heat flux that can be converted into electricity by a thermoelectric generator (TEG). When a TEG is used under limited or constant heat flux conditions the temperature difference across the device cannot be considered constant and will change depending on the electrical current generated by the TEG. This phenomenon is induced by the Peltier effect, which works against power generation and deviates the optimum operating point from the commonly known maximum power point (MPP). This point, dictated by the maximum power transfer theorem, is achieved when the source equivalent series resistance and the load resistance are equal, in conditions of constant temperature difference. Hence maximum power point tracking (MPPT) algorithms that regulate the TEG at half of the instantaneous open-circuit voltage are optimized only for applications where the TEG operates under constant temperature difference but are not ideal for constant heat flux conditions. Hill climbing MPPT methods, e.g., perturb-and-observe (P&O) or incremental conductance (IC), can reach the MPP more accurately if the sampling time is extended to the thermal time constant of the system.

Suggested Citation

  • Torrecilla, Marcos Compadre & Montecucco, Andrea & Siviter, Jonathan & Strain, Andrew & Knox, Andrew R., 2018. "Transient response of a thermoelectric generator to load steps under constant heat flux," Applied Energy, Elsevier, vol. 212(C), pages 293-303.
  • Handle: RePEc:eee:appene:v:212:y:2018:i:c:p:293-303
    DOI: 10.1016/j.apenergy.2017.12.010
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    References listed on IDEAS

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    Cited by:

    1. Ahmed Fathy & Hegazy Rezk & Dalia Yousri & Essam H. Houssein & Rania M. Ghoniem, 2021. "Parameter Identification of Optimized Fractional Maximum Power Point Tracking for Thermoelectric Generation Systems Using Manta Ray Foraging Optimization," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
    2. Compadre Torrecilla, Marcos & Montecucco, Andrea & Siviter, Jonathan & Knox, Andrew R. & Strain, Andrew, 2019. "Novel model and maximum power tracking algorithm for thermoelectric generators operated under constant heat flux," Applied Energy, Elsevier, vol. 256(C).
    3. Wang, Jian-jun & Deng, Yu-cong & Sun, Wen-biao & Zheng, Xiao-bin & Cui, Zheng, 2023. "Maximum power point tracking method based on impedance matching for a micro hydropower generator," Applied Energy, Elsevier, vol. 340(C).
    4. Daniel Sanin-Villa & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña, 2023. "Material Property Characterization and Parameter Estimation of Thermoelectric Generator by Using a Master–Slave Strategy Based on Metaheuristics Techniques," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    5. Cai, Yeyun & Ding, Ning & Rezania, A. & Deng, Fang & Rosendahl, L. & Chen, Jie, 2023. "A multi-objective optimization in system level for thermoelectric generation system," Energy, Elsevier, vol. 281(C).

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