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A Maximum Power Point Tracker Using the Bald Eagle Search Technique for Grid-Connected Photovoltaic Systems

Author

Listed:
  • Waleed Al Abri

    (Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman)

  • Rashid Al Abri

    (Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman
    Sustainable Energy Research Center (SERC), Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman)

  • Hassan Yousef

    (Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman)

  • Amer Al-Hinai

    (Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman)

Abstract

Maximum power point tracker (MPPT) methods work to maximize the output power of a PV system under changes in meteorological conditions. The performance of these methods depends on the complexity of the algorithm and the number of used variable inputs for obtaining the MPP value. Moreover, they oscillate around the MPP in steady-state operations, causing a waste of power and power loss. Moreover, they do not work perfectly for a PV system running under partial shading conditions. Therefore, this paper proposes modifications to the global maximum power point bald eagle search-based (GMPP BES) method so that it runs as an MPPT as well. The modifications enable the GMPP BES method to detect minor changes in insolation and temperature by observing the changes in the PV array output voltage and, accordingly, trigger the search for the suitable MPP voltage. An experimental setup using a real-time digital simulator (RTDS) was utilized to evaluate the modified GMPP BES-based method under real changes in insolation and ambient temperature. The RTDS simulations confirm the capability of the modified method to accurately and efficiently locate the MPP values. Furthermore, the results demonstrate that the proposed method performs better than the perturb and observe (PO) method concerning its ability to respond to changes in insolation and ambient temperature and its ability to arrive at correct MPP values with nearly zero oscillation around the maximum power point. Thus, with these advantages, the proposed method can be considered a practical solution for solar farms that have to harvest large amounts of energy.

Suggested Citation

  • Waleed Al Abri & Rashid Al Abri & Hassan Yousef & Amer Al-Hinai, 2022. "A Maximum Power Point Tracker Using the Bald Eagle Search Technique for Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 15(23), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9185-:d:992976
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    References listed on IDEAS

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    1. Tehzeeb-ul Hassan & Rabeh Abbassi & Houssem Jerbi & Kashif Mehmood & Muhammad Faizan Tahir & Khalid Mehmood Cheema & Rajvikram Madurai Elavarasan & Farman Ali & Irfan Ahmad Khan, 2020. "A Novel Algorithm for MPPT of an Isolated PV System Using Push Pull Converter with Fuzzy Logic Controller," Energies, MDPI, vol. 13(15), pages 1-20, August.
    2. Muhammad Annas Hafeez & Ahmer Naeem & Muhammad Akram & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Yong Wang, 2022. "A Novel Hybrid MPPT Technique Based on Harris Hawk Optimization (HHO) and Perturb and Observer (P&O) under Partial and Complex Partial Shading Conditions," Energies, MDPI, vol. 15(15), pages 1-18, July.
    3. Faiçal Hamidi & Severus Constantin Olteanu & Dumitru Popescu & Houssem Jerbi & Ingrid Dincă & Sondess Ben Aoun & Rabeh Abbassi, 2020. "Model Based Optimisation Algorithm for Maximum Power Point Tracking in Photovoltaic Panels," Energies, MDPI, vol. 13(18), pages 1-20, September.
    4. Li, Guiqiang & Jin, Yi & Akram, M.W. & Chen, Xiao & Ji, Jie, 2018. "Application of bio-inspired algorithms in maximum power point tracking for PV systems under partial shading conditions – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 840-873.
    5. Marwen Bjaoui & Brahim Khiari & Ridha Benadli & Mouad Memni & Anis Sellami, 2019. "Practical Implementation of the Backstepping Sliding Mode Controller MPPT for a PV-Storage Application," Energies, MDPI, vol. 12(18), pages 1-22, September.
    6. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
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