IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i14p3391-d1432573.html
   My bibliography  Save this article

Single-Sensor Global MPPT for PV System Interconnected with DC Link Using Recent Red-Tailed Hawk Algorithm

Author

Listed:
  • Motab Turki Almousa

    (Department of Electrical Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia)

  • Mohamed R. Gomaa

    (Mechanical Engineering Department, Faculty of Engineering, Al-Hussein Bin Talal University, Maan 71110, Jordan)

  • Mostafa Ghasemi

    (Chemical Engineering Section, Faculty of Engineering, Sohar University, Sohar 311, Oman)

  • Mohamed Louzazni

    (Science Engineer Laboratory for Energy, National School of Applied Sciences, Chouaib Doukkali University of El Jadida, El Jadida P.O. Box 20, Morocco)

Abstract

The primary disadvantage of solar photovoltaic systems, particularly in partial shadowing conditions (PSC), is their low efficiency. A power–voltage curve with a homogenous distribution of solar irradiation often has a single maximum power point (MPP). Without a doubt, it can be extracted using any conventional tracker—for instance, perturb and observe. On the other hand, under PSC, the situation is entirely different since, depending on the number of distinct solar irradiation levels, the power–voltage curve has numerous MPPs (i.e., multiple local points and one global point). Conventional MPPTs can only extract the first point since they are unable to distinguish between local and global MPP. Thus, to track the global MPP, an optimized MPPT based on optimization algorithms is needed. The majority of global MPPT techniques seen in the literature call for sensors for voltage and current in addition to, occasionally, temperature and/or solar irradiance, which raises the cost of the system. Therefore, a single-sensor global MPPT based on the recent red-tailed hawk (RTH) algorithm for a PV system interconnected with a DC link operating under PSC is presented. Reducing the number of sensors leads to a decrease in the cost of a controller. To prove the superiority of the RTH, the results are compared with several metaheuristic algorithms. Three shading scenarios are considered, with the idea of changing the shading scenario to change the location of the global MPP to measure the consistency of the algorithms. The results verified the effectiveness of the suggested global MPPT based on the RTH in precisely capturing the global MPP compared with other methods. As an example, for the first shading situation, the mean PV power values varied between 6835.63 W and 5925.58 W. The RTH reaches the highest PV power of 6835.63 W flowing through particle swarm optimization (6808.64 W), whereas greylag goose optimizer achieved the smallest PV power production of 5925.58 W.

Suggested Citation

  • Motab Turki Almousa & Mohamed R. Gomaa & Mostafa Ghasemi & Mohamed Louzazni, 2024. "Single-Sensor Global MPPT for PV System Interconnected with DC Link Using Recent Red-Tailed Hawk Algorithm," Energies, MDPI, vol. 17(14), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3391-:d:1432573
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/14/3391/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/14/3391/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ko, Suk Whan & Ju, Young Chul & Hwang, Hye Mi & So, Jung Hun & Jung, Young-Seok & Song, Hyung-Jun & Song, Hee-eun & Kim, Soo-Hyun & Kang, Gi Hwan, 2017. "Electric and thermal characteristics of photovoltaic modules under partial shading and with a damaged bypass diode," Energy, Elsevier, vol. 128(C), pages 232-243.
    2. Jerry L. Holechek & Hatim M. E. Geli & Mohammed N. Sawalhah & Raul Valdez, 2022. "A Global Assessment: Can Renewable Energy Replace Fossil Fuels by 2050?," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    3. Eltamaly, Ali M., 2021. "A novel musical chairs algorithm applied for MPPT of PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    4. Silvestre, S. & Boronat, A. & Chouder, A., 2009. "Study of bypass diodes configuration on PV modules," Applied Energy, Elsevier, vol. 86(9), pages 1632-1640, September.
    Full references (including those not matched with items on IDEAS)

    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. Woo Gyun Shin & Suk Whan Ko & Hyung Jun Song & Young Chul Ju & Hye Mi Hwang & Gi Hwan Kang, 2018. "Origin of Bypass Diode Fault in c-Si Photovoltaic Modules: Leakage Current under High Surrounding Temperature," Energies, MDPI, vol. 11(9), pages 1-11, September.
    2. Romênia G. Vieira & Fábio M. U. de Araújo & Mahmoud Dhimish & Maria I. S. Guerra, 2020. "A Comprehensive Review on Bypass Diode Application on Photovoltaic Modules," Energies, MDPI, vol. 13(10), pages 1-21, May.
    3. Bressan, M. & Gutierrez, A. & Garcia Gutierrez, L. & Alonso, C., 2018. "Development of a real-time hot-spot prevention using an emulator of partially shaded PV systems," Renewable Energy, Elsevier, vol. 127(C), pages 334-343.
    4. Teo, J.C. & Tan, Rodney H.G. & Mok, V.H. & Ramachandaramurthy, Vigna K. & Tan, ChiaKwang, 2020. "Impact of bypass diode forward voltage on maximum power of a photovoltaic system under partial shading conditions," Energy, Elsevier, vol. 191(C).
    5. Yadav, Anurag Singh & Mukherjee, V., 2021. "Conventional and advanced PV array configurations to extract maximum power under partial shading conditions: A review," Renewable Energy, Elsevier, vol. 178(C), pages 977-1005.
    6. Chanuri Charin & Dahaman Ishak & Muhammad Ammirrul Atiqi Mohd Zainuri & Baharuddin Ismail & Turki Alsuwian & Adam R. H. Alhawari, 2022. "Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking," Energies, MDPI, vol. 15(19), pages 1-30, October.
    7. Wei Wang & Leonid Melnyk & Oleksandra Kubatko & Bohdan Kovalov & Luc Hens, 2023. "Economic and Technological Efficiency of Renewable Energy Technologies Implementation," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    8. Zhang, Chao & Zhao, Yangsheng & Feng, Zijun & Meng, Qiaorong & Wang, Lei & Lu, Yang, 2023. "Thermal maturity and chemical structure evolution of lump long-flame coal during superheated water vapor–based in situ pyrolysis," Energy, Elsevier, vol. 263(PC).
    9. Hasan, M.A. & Parida, S.K., 2016. "An overview of solar photovoltaic panel modeling based on analytical and experimental viewpoint," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 75-83.
    10. Ahmed Hussain Elmetwaly & Ramy Adel Younis & Abdelazeem Abdallah Abdelsalam & Ahmed Ibrahim Omar & Mohamed Metwally Mahmoud & Faisal Alsaif & Adel El-Shahat & Mohamed Attya Saad, 2023. "Modeling, Simulation, and Experimental Validation of a Novel MPPT for Hybrid Renewable Sources Integrated with UPQC: An Application of Jellyfish Search Optimizer," Sustainability, MDPI, vol. 15(6), pages 1-30, March.
    11. Elfarra, Barakat & Yasmeen, Rizwana & Shah, Wasi Ul Hassan, 2024. "The impact of energy security, energy mix, technological advancement, trade openness, and political stability on energy efficiency: Evidence from Arab countries," Energy, Elsevier, vol. 295(C).
    12. Hagreaves Kumba & Oludolapo A. Olanrewaju & Ratidzo Pasipamire, 2024. "Integration of Renewable Energy Technologies for Sustainable Development in South Africa: A Focus on Grid-Connected PV Systems," Energies, MDPI, vol. 17(12), pages 1-22, June.
    13. Bressan, M. & El Basri, Y. & Galeano, A.G. & Alonso, C., 2016. "A shadow fault detection method based on the standard error analysis of I-V curves," Renewable Energy, Elsevier, vol. 99(C), pages 1181-1190.
    14. Gao, Dan & Zhao, Yang & Liang, Kai & He, Shuyu & Zhang, Heng & Chen, Haiping, 2022. "Energy and exergy analyses of a low-concentration photovoltaic/thermal module with glass channel," Energy, Elsevier, vol. 253(C).
    15. Daiva Makutėnienė & Algirdas Justinas Staugaitis & Bernardas Vaznonis & Gunta Grīnberga-Zālīte, 2023. "The Relationship between Energy Consumption and Economic Growth in the Baltic Countries’ Agriculture: A Non-Linear Framework," Energies, MDPI, vol. 16(5), pages 1-22, February.
    16. Junqiu Fan & Jing Zhang & Long Yuan & Rujing Yan & Yu He & Weixing Zhao & Nang Nin, 2024. "Deep Low-Carbon Economic Optimization Using CCUS and Two-Stage P2G with Multiple Hydrogen Utilizations for an Integrated Energy System with a High Penetration Level of Renewables," Sustainability, MDPI, vol. 16(13), pages 1-20, July.
    17. Evgeny Chupakhin & Olga Babich & Stanislav Sukhikh & Svetlana Ivanova & Ekaterina Budenkova & Olga Kalashnikova & Alexander Prosekov & Olga Kriger & Vyacheslav Dolganyuk, 2022. "Bioengineering and Molecular Biology of Miscanthus," Energies, MDPI, vol. 15(14), pages 1-14, July.
    18. Ju, Xing & Pan, Xinyu & Zhang, Zheyang & Xu, Chao & Wei, Gaosheng, 2019. "Thermal and electrical performance of the dense-array concentrating photovoltaic (DA-CPV) system under non-uniform illumination," Applied Energy, Elsevier, vol. 250(C), pages 904-915.
    19. Merino, S. & Sánchez, F.J. & Sidrach de Cardona, M. & Guzmán, F. & Guzmán, R. & Martínez, J. & Sotorrío, P.J., 2018. "Optimization of energy distribution in solar panel array configurations by graphs and Minkowski’s paths," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 48-58.
    20. Muhannad Alaraj & Astitva Kumar & Ibrahim Alsaidan & Mohammad Rizwan & Majid Jamil, 2022. "An Advanced and Robust Approach to Maximize Solar Photovoltaic Power Production," Sustainability, MDPI, vol. 14(12), pages 1-20, June.

    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:jeners:v:17:y:2024:i:14:p:3391-:d:1432573. 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.