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A Sine Cosine Algorithm-Based Fractional MPPT for Thermoelectric Generation System

Author

Listed:
  • Hegazy Rezk

    (College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Wadi Addawaser 11911, Saudi Arabia
    Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61517, Egypt)

  • Mohammed Mazen Alhato

    (Research Laboratory in Automatic Control (LARA), National Engineering School of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia)

  • Mujahed Al-Dhaifallah

    (Control and Instrumentation Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
    Interdisciplinary Research Center (lRC) for Renewable Energy and Power Systems, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

  • Soufiene Bouallègue

    (Research Laboratory in Automatic Control (LARA), National Engineering School of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia
    High Institute of Industrial Systems of Gabès (ISSIG), University of Gabès, Gabès 6011, Tunisia)

Abstract

Thermoelectric generators (TEGs) are equipment for transforming thermal power into electricity via the Seebeck effect. These modules have gained increasing interest in research fields related to sustainable energy. The harvested energy is mostly reliant on the differential temperature between the hot and cold areas of the TEGs. Hence, a reliable maximum power point tracker is necessary to operate TEGs too close to their maximum power point (MPP) under an operational and climate variation. In this paper, an optimized fractional incremental resistance tracker (OF-INRT) is suggested to enhance the output performance of a TEG. The introduced tracker is based on the fractional-order PI λ D μ control concepts. The optimal parameters of the OF-INRT are determined using a population-based sine cosine algorithm (SCA). To confirm the optimality of the introduced SCA, experiments were conducted and the results compared with those of particle swarm optimization (PSO) and whale optimization algorithm (WOA) based techniques. The key goal of the suggested OF-INRT is to overcome the two main issues in conventional trackers, i.e., the slow dynamics of traditional incremental resistance trackers (INRT) and the high steady-state fluctuation around the MPP in the prevalent perturb and observe trackers (POTs). The main findings prove the superiority of the OF-INRT in comparison with the INRT and POT, for both dynamic and steady-state responses.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11650-:d:661775
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    References listed on IDEAS

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