IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i22p2971-d684291.html
   My bibliography  Save this article

Parameter Identification of Optimized Fractional Maximum Power Point Tracking for Thermoelectric Generation Systems Using Manta Ray Foraging Optimization

Author

Listed:
  • Ahmed Fathy

    (Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakaka 72388, Saudi Arabia)

  • Hegazy Rezk

    (Electrical Engineering Department, College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 16278, Saudi Arabia)

  • Dalia Yousri

    (Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt)

  • Essam H. Houssein

    (Faculty of Computers and Information, Minia University, Minia 61519, Egypt)

  • Rania M. Ghoniem

    (Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 84428, Saudi Arabia
    Department of Computer, Mansoura University, Mansoura 35516, Egypt)

Abstract

Thermoelectric generation systems (TEGSs) are used to convert temperature difference and heat flow into DC power based on the Seebeck theorem. The basic unit of TEGS is the thermoelectric module (TEM). TEGSs have gained increasing interest in the research fields of sustainable energy. The output power from TEM is mostly reliant on differential temperature between the hot and cold sides of the TEM added to the value of the load. As such, a robust MPPT strategy (MPPTS) is required to ensure that the TEGS is operating near to the MPP while varying the operating conditions. Two main drawbacks may occur in the conventional MPPTSs: low dynamic response, such as in the incremental resistance (INR) method, and oscillations around MPP at steady state, such as in the hill climbing (HC) method. In the current research work, an optimized fractional MPPTS is developed to improve the tracking performance of the TEGS, and remove the two drawbacks of the conventional MPPTSs. The proposed strategy is based on fractional order control (FOC). The main advantage of FOC is that it offers extra flexible time and frequency responses of the control system consent for better and robust performance. The optimal parameters of the optimized fractional MPPTS are identified by a manta ray foraging optimization (MRFO). To verify the robustness of the MRFO, the obtained results are compared with ten other algorithms: particle swarm optimization; whale optimization algorithm; Harris hawks optimization; heap-based optimizer; gradient-based optimizer; grey wolf optimizer; slime mould algorithm; genetic algorithm; seagull optimization algorithm (SOA); and tunicate swarm algorithm. The maximum average cost function of 4.92934 kWh has been achieved by MRFO, followed by SOA (4.5721 kWh). The lowest STD of 0.04867 was also accomplished by MRFO. The maximum efficiency of 99.46% has been obtained by MRFO, whereas the lowest efficiency of 74.01% was obtained by GA. Finally, the main findings proved the superiority of optimized fractional MPPTS compared with conventional methods for both steady-state and dynamic responses.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2971-:d:684291
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/22/2971/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/22/2971/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. 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.
    3. N. Kanagaraj & Hegazy Rezk & Mohamed R. Gomaa, 2020. "A Variable Fractional Order Fuzzy Logic Control Based MPPT Technique for Improving Energy Conversion Efficiency of Thermoelectric Power Generator," Energies, MDPI, vol. 13(17), pages 1-18, September.
    4. Verma, Vishal & Kane, Aarti & Singh, Bhim, 2016. "Complementary performance enhancement of PV energy system through thermoelectric generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1017-1026.
    5. Mohamed, Mohamed A. & Zaki Diab, Ahmed A. & Rezk, Hegazy, 2019. "Partial shading mitigation of PV systems via different meta-heuristic techniques," Renewable Energy, Elsevier, vol. 130(C), pages 1159-1175.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carlos Andres Ramos-Paja & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña, 2022. "Adaptive Sliding-Mode Controller for Flyback-Based PV Systems Featuring Constant Switching Frequency," Mathematics, MDPI, vol. 10(8), pages 1-27, April.
    2. Hegazy Rezk & Abdul Ghani Olabi & Rania M. Ghoniem & Mohammad Ali Abdelkareem, 2023. "Optimized Fractional Maximum Power Point Tracking Using Bald Eagle Search for Thermoelectric Generation System," Energies, MDPI, vol. 16(10), pages 1-15, May.
    3. Alma Y. Alanis, 2022. "Bioinspired Intelligent Algorithms for Optimization, Modeling and Control: Theory and Applications," Mathematics, MDPI, vol. 10(13), pages 1-2, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kanagaraj N, 2021. "Photovoltaic and Thermoelectric Generator Combined Hybrid Energy System with an Enhanced Maximum Power Point Tracking Technique for Higher Energy Conversion Efficiency," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    2. Rezk, Hegazy & AL-Oran, Mazen & Gomaa, Mohamed R. & Tolba, Mohamed A. & Fathy, Ahmed & Abdelkareem, Mohammad Ali & Olabi, A.G. & El-Sayed, Abou Hashema M., 2019. "A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(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. Nassef, Ahmed M. & Olabi, A.G. & Rodriguez, Cristina & Abdelkareem, Mohammad Ali & Rezk, Hegazy, 2021. "Optimal operating parameter determination and modeling to enhance methane production from macroalgae," Renewable Energy, Elsevier, vol. 163(C), pages 2190-2197.
    5. Ghazi A. Ghazi & Hany M. Hasanien & Essam A. Al-Ammar & Rania A. Turky & Wonsuk Ko & Sisam Park & Hyeong-Jin Choi, 2022. "African Vulture Optimization Algorithm-Based PI Controllers for Performance Enhancement of Hybrid Renewable-Energy Systems," Sustainability, MDPI, vol. 14(13), pages 1-26, July.
    6. Yin, Ershuai & Li, Qiang & Xuan, Yimin, 2018. "Optimal design method for concentrating photovoltaic-thermoelectric hybrid system," Applied Energy, Elsevier, vol. 226(C), pages 320-329.
    7. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    8. Tanveer, Waqas Hassan & Rezk, Hegazy & Nassef, Ahmed & Abdelkareem, Mohammad Ali & Kolosz, Ben & Karuppasamy, K. & Aslam, Jawad & Gilani, Syed Omer, 2020. "Improving fuel cell performance via optimal parameters identification through fuzzy logic based-modeling and optimization," Energy, Elsevier, vol. 204(C).
    9. Kane, Aarti & Verma, Vishal & Singh, Bhim, 2017. "Optimization of thermoelectric cooling technology for an active cooling of photovoltaic panel," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1295-1305.
    10. 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.
    11. N. Kanagaraj & Hegazy Rezk & Mohamed R. Gomaa, 2020. "A Variable Fractional Order Fuzzy Logic Control Based MPPT Technique for Improving Energy Conversion Efficiency of Thermoelectric Power Generator," Energies, MDPI, vol. 13(17), pages 1-18, September.
    12. Yang, Bo & Wu, Shaocong & Li, Qiang & Yan, Yingjie & Li, Danyang & Luo, Enbo & Zeng, Chunyuan & Chen, Yijun & Guo, Zhengxun & Shu, Hongchun & Li, Zilin & Wang, Jingbo, 2023. "Jellyfish search algorithm based optimal thermoelectric generation array reconfiguration under non-uniform temperature distribution condition," Renewable Energy, Elsevier, vol. 204(C), pages 197-217.
    13. Sairam, Seshapalli & Seshadhri, Subathra & Marafioti, Giancarlo & Srinivasan, Seshadhri & Mathisen, Geir & Bekiroglu, Korkut, 2022. "Edge-based Explainable Fault Detection Systems for photovoltaic panels on edge nodes," Renewable Energy, Elsevier, vol. 185(C), pages 1425-1440.
    14. Tian, B. & Loonen, R.C.G.M. & Bognár, Á. & Hensen, J.L.M., 2022. "Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas," Renewable Energy, Elsevier, vol. 198(C), pages 804-824.
    15. Samir Ezzitouni & Pablo Fernández-Yáñez & Luis Sánchez Rodríguez & Octavio Armas & Javier de las Morenas & Eduard Massaguer & Albert Massaguer, 2021. "Electrical Modelling and Mismatch Effects of Thermoelectric Modules on Performance of a Thermoelectric Generator for Energy Recovery in Diesel Exhaust Systems," Energies, MDPI, vol. 14(11), pages 1-15, May.
    16. Mohamed R. Gomaa & Hegazy Rezk & Ramadan J. Mustafa & Mujahed Al-Dhaifallah, 2019. "Evaluating the Environmental Impacts and Energy Performance of a Wind Farm System Utilizing the Life-Cycle Assessment Method: A Practical Case Study," Energies, MDPI, vol. 12(17), pages 1-25, August.
    17. Jouda Arfaoui & Hegazy Rezk & Mujahed Al-Dhaifallah & Mohamed N. Ibrahim & Mami Abdelkader, 2020. "Simulation-Based Coyote Optimization Algorithm to Determine Gains of PI Controller for Enhancing the Performance of Solar PV Water-Pumping System," Energies, MDPI, vol. 13(17), pages 1-17, August.
    18. Fathy, Ahmed, 2023. "Efficient energy valley optimization approach for reconfiguring thermoelectric generator system under non-uniform heat distribution," Renewable Energy, Elsevier, vol. 217(C).
    19. Ali Kareem Abdulrazzaq & Balázs Plesz & György Bognár, 2020. "A Novel Method for Thermal Modelling of Photovoltaic Modules/Cells under Varying Environmental Conditions," Energies, MDPI, vol. 13(13), pages 1-23, June.
    20. Hegazy Rezk & Asmaa A. Elghany & Mujahed Al-Dhaifallah & Abo Hashema M. El Sayed & Mohamed N. Ibrahim, 2019. "Numerical Estimation and Experimental Verification of Optimal Parameter Identification Based on Modern Optimization of a Three Phase Induction Motor," Mathematics, MDPI, vol. 7(12), pages 1-13, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2971-:d:684291. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.