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Robust Fractional MPPT-Based Moth-Flame Optimization Algorithm for Thermoelectric Generation Applications

Author

Listed:
  • Hegazy Rezk

    (Department of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
    Electrical Engineering Department, Faculty of Engineering, Minia University, Minya 61519, Egypt)

  • Magdy M. Zaky

    (Engineering Department, Nuclear Research Center, Atomic Energy Authority (EAEA), Cairo 11787, Egypt)

  • Mohemmed Alhaider

    (Department of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia)

  • Mohamed A. Tolba

    (Reactors Department, Nuclear Research Center, Egyptian Atomic Energy Authority (EAEA), Cairo 11787, Egypt)

Abstract

Depending on the temperature difference between the hot and cold sides of the thermoelectric generator (TEG), the output performance of the TEG can be produced. This means that it is necessary to force a TEG based on robust maximum power point tracking (MPPT) to operate close to its MPP at any given temperature or load. In this paper, an improved fractional MPPT (IFMPPT) is proposed in order to increase the amount of energy that can be harvested from TEGs. According to the suggested method, fractional order control is used. A moth-flame optimizer (MFO) was used to determine IFMPPT’s optimal parameters. A comparison of the results obtained by the MFO is made with those obtained by a particle swarm optimizer, genetic algorithm, gray wolf optimizer, seagull optimization algorithm, and tunicate swarm algorithm in order to demonstrate MFO’s superiority. IFMPPT’s primary objective is to enhance dynamic responses and exclude steady-state oscillations. Consequently, incremental resistance and perturb and observe are compared with the proposed strategy’s performance. It was revealed that IFMPPT provides superior tracking results both in dynamic and steady-state conditions when compared with traditional methods.

Suggested Citation

  • Hegazy Rezk & Magdy M. Zaky & Mohemmed Alhaider & Mohamed A. Tolba, 2022. "Robust Fractional MPPT-Based Moth-Flame Optimization Algorithm for Thermoelectric Generation Applications," Energies, MDPI, vol. 15(23), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8836-:d:981482
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    References listed on IDEAS

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    1. Liang, Gaowei & Zhou, Jiemin & Huang, Xuezhang, 2011. "Analytical model of parallel thermoelectric generator," Applied Energy, Elsevier, vol. 88(12), pages 5193-5199.
    2. Hegazy Rezk & Ziad Mohammed Ali & Omer Abdalla & Obai Younis & Mohamed Ramadan Gomaa & Mauia Hashim, 2019. "Hybrid Moth-Flame Optimization Algorithm and Incremental Conductance for Tracking Maximum Power of Solar PV/Thermoelectric System under Different Conditions," Mathematics, MDPI, vol. 7(10), pages 1-21, September.
    3. Olabi, A.G. & Abdelkareem, Mohammad Ali, 2022. "Renewable energy and climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Nouman Akram & Laiq Khan & Shahrukh Agha & Kamran Hafeez, 2022. "Global Maximum Power Point Tracking of Partially Shaded PV System Using Advanced Optimization Techniques," Energies, MDPI, vol. 15(11), pages 1-29, May.
    5. Kim, Shiho, 2013. "Analysis and modeling of effective temperature differences and electrical parameters of thermoelectric generators," Applied Energy, Elsevier, vol. 102(C), pages 1458-1463.
    6. Ding, L.C. & Akbarzadeh, A. & Tan, L., 2018. "A review of power generation with thermoelectric system and its alternative with solar ponds," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 799-812.
    7. Rowe, D.M., 1999. "Thermoelectrics, an environmentally-friendly source of electrical power," Renewable Energy, Elsevier, vol. 16(1), pages 1251-1256.
    8. Gou, Xiaolong & Xiao, Heng & Yang, Suwen, 2010. "Modeling, experimental study and optimization on low-temperature waste heat thermoelectric generator system," Applied Energy, Elsevier, vol. 87(10), pages 3131-3136, October.
    9. Ando Junior, O.H. & Maran, A.L.O. & Henao, N.C., 2018. "A review of the development and applications of thermoelectric microgenerators for energy harvesting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 376-393.
    10. Montecucco, A. & Siviter, J. & Knox, A.R., 2017. "Combined heat and power system for stoves with thermoelectric generators," Applied Energy, Elsevier, vol. 185(P2), pages 1336-1342.
    11. Loise Rissini Kramer & Anderson Luis Oliveira Maran & Samara Silva de Souza & Oswaldo Hideo Ando Junior, 2019. "Analytical and Numerical Study for the Determination of a Thermoelectric Generator’s Internal Resistance," Energies, MDPI, vol. 12(16), pages 1-12, August.
    12. Zhe Zhang & Yuqi Zhang & Xiaomei Sui & Wenbin Li & Daochun Xu, 2020. "Performance of Thermoelectric Power-Generation System for Sufficient Recovery and Reuse of Heat Accumulated at Cold Side of TEG with Water-Cooling Energy Exchange Circuit," Energies, MDPI, vol. 13(21), pages 1-18, October.
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