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Maximum Power Point Tracking Control of a Thermoelectric Generation System Using the Extremum Seeking Control Method

Author

Listed:
  • Ssennoga Twaha

    (Fluids & Thermal Engineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK)

  • Jie Zhu

    (Fluids & Thermal Engineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK)

  • Luqman Maraaba

    (Electrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

  • Kuo Huang

    (Fluids & Thermal Engineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK)

  • Bo Li

    (Fluids & Thermal Engineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK)

  • Yuying Yan

    (Fluids & Thermal Engineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK)

Abstract

This study proposes and implements maximum power Point Tracking (MPPT) control on thermoelectric generation system using an extremum seeking control (ESC) algorithm. The MPPT is applied to guarantee maximum power extraction from the TEG system. The work has been carried out through modelling of thermoelectric generator/dc-dc converter system using Matlab/Simulink. The effectiveness of ESC technique has been assessed by comparing the results with those of the Perturb and Observe (P&O) MPPT method under the same operating conditions. Results indicate that ESC MPPT method extracts more power than the P&O technique, where the output power of ESC technique is higher than that of P&O by 0.47 W or 6.1% at a hot side temperature of 200 °C. It is also noted that the ESC MPPT based model is almost fourfold faster than the P&O method. This is attributed to smaller MPPT circuit of ESC compared to that of P&O, hence we conclude that the ESC MPPT method outperforms the P&O technique.

Suggested Citation

  • Ssennoga Twaha & Jie Zhu & Luqman Maraaba & Kuo Huang & Bo Li & Yuying Yan, 2017. "Maximum Power Point Tracking Control of a Thermoelectric Generation System Using the Extremum Seeking Control Method," Energies, MDPI, vol. 10(12), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2016-:d:121203
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    References listed on IDEAS

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    1. Hegazy Rezk & Mohammed Mazen Alhato & Mujahed Al-Dhaifallah & Soufiene Bouallègue, 2021. "A Sine Cosine Algorithm-Based Fractional MPPT for Thermoelectric Generation System," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    2. Martí Comamala & Ivan Ruiz Cózar & Albert Massaguer & Eduard Massaguer & Toni Pujol, 2018. "Effects of Design Parameters on Fuel Economy and Output Power in an Automotive Thermoelectric Generator," Energies, MDPI, vol. 11(12), pages 1-28, November.

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