IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p11736-d663512.html
   My bibliography  Save this article

Jellyfish Search Optimization Algorithm for MPP Tracking of PV System

Author

Listed:
  • Afroz Alam

    (Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India)

  • Preeti Verma

    (Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India)

  • Mohd Tariq

    (Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India)

  • Adil Sarwar

    (Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India)

  • Basem Alamri

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Noore Zahra

    (Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia)

  • Shabana Urooj

    (Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh 84428, Saudi Arabia)

Abstract

Because of the rapid increase in the depletion rate of conventional energy sources, the energy crisis has become a central problem in the contemporary world. This issue opens the gateway for exploring and developing renewable energy sources to fulfill the exigent energy demand. Solar energy is an abundant source of sustainable energy and hence, nowadays, solar photovoltaic (PV) systems are employed to extract energy from solar irradiation. However, the PV systems need to work at the maximum power point (MPP) to exploit the highest accessible power during varying operating conditions. For this reason, maximum power point tracking (MPPT) algorithms are used to track the optimum power point. Furthermore, the efficient utilization of PV systems is hindered by renowned partial shading conditions (PSC), which generate multiple peaks in the power-voltage characteristic of the PV array. Thus, this article addresses the performance of the newly developed jellyfish search optimization (JSO) strategy in the PV frameworks to follow the global maximum power point (GMPP) under PSC.

Suggested Citation

  • Afroz Alam & Preeti Verma & Mohd Tariq & Adil Sarwar & Basem Alamri & Noore Zahra & Shabana Urooj, 2021. "Jellyfish Search Optimization Algorithm for MPP Tracking of PV System," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11736-:d:663512
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/11736/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/21/11736/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohamed Abdel-Basset & Reda Mohamed & Ripon K. Chakrabortty & Michael J. Ryan & Attia El-Fergany, 2021. "An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models," Energies, MDPI, vol. 14(7), pages 1-33, March.
    2. Saravanan, S. & Ramesh Babu, N., 2016. "Maximum power point tracking algorithms for photovoltaic system – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 192-204.
    3. Verma, Deepak & Nema, Savita & Shandilya, A.M. & Dash, Soubhagya K., 2016. "Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1018-1034.
    4. Mohd Nadhir Ab Wahab & Samia Nefti-Meziani & Adham Atyabi, 2015. "A Comprehensive Review of Swarm Optimization Algorithms," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-36, May.
    5. CH Hussaian Basha & C Rani, 2020. "Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis," Energies, MDPI, vol. 13(2), pages 1-27, January.
    6. Karami, Nabil & Moubayed, Nazih & Outbib, Rachid, 2017. "General review and classification of different MPPT Techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 1-18.
    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. Abdullah Shaheen & Ragab El-Sehiemy & Salah Kamel & Ali Selim, 2022. "Optimal Operational Reliability and Reconfiguration of Electrical Distribution Network Based on Jellyfish Search Algorithm," Energies, MDPI, vol. 15(19), pages 1-14, September.
    2. 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.
    3. Waqas Anjum & Abdul Rashid Husain & Junaidi Abdul Aziz & Syed Muhammad Fasih ur Rehman & Muhammad Paend Bakht & Hasan Alqaraghuli, 2022. "A Robust Dynamic Control Strategy for Standalone PV System under Variable Load and Environmental Conditions," Sustainability, MDPI, vol. 14(8), pages 1-27, April.

    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. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    2. Julio López Seguel & Seleme I. Seleme, 2021. "Robust Digital Control Strategy Based on Fuzzy Logic for a Solar Charger of VRLA Batteries," Energies, MDPI, vol. 14(4), pages 1-27, February.
    3. Haoming Liu & Muhammad Yasir Ali Khan & Xiaoling Yuan, 2023. "Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review," Energies, MDPI, vol. 16(15), pages 1-64, July.
    4. Memon, Mudasir Ahmed & Mekhilef, Saad & Mubin, Marizan & Aamir, Muhammad, 2018. "Selective harmonic elimination in inverters using bio-inspired intelligent algorithms for renewable energy conversion applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2235-2253.
    5. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    6. Julio López Seguel & Seleme I. Seleme & Lenin M. F. Morais, 2022. "Comparative Study of Buck-Boost, SEPIC, Cuk and Zeta DC-DC Converters Using Different MPPT Methods for Photovoltaic Applications," Energies, MDPI, vol. 15(21), pages 1-26, October.
    7. Jately, Vibhu & Azzopardi, Brian & Joshi, Jyoti & Venkateswaran V, Balaji & Sharma, Abhinav & Arora, Sudha, 2021. "Experimental Analysis of hill-climbing MPPT algorithms under low irradiance levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    8. Gang Zhang & Zhongbei Tian & Huiqing Du & Zhigang Liu, 2018. "A Novel Hybrid DC Traction Power Supply System Integrating PV and Reversible Converters," Energies, MDPI, vol. 11(7), pages 1-24, June.
    9. Sajib Chakraborty & Mohammed Mahedi Hasan & Imane Worighi & Omar Hegazy & M. Abdur Razzak, 2018. "Performance Evaluation of a PID-Controlled Synchronous Buck Converter Based Battery Charging Controller for Solar-Powered Lighting System in a Fishing Trawler," Energies, MDPI, vol. 11(10), pages 1-26, October.
    10. Çelik, Özgür & Teke, Ahmet & Tan, Adnan, 2018. "Overview of micro-inverters as a challenging technology in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3191-3206.
    11. Singh, Bhuwan Pratap & Goyal, Sunil Kumar & Siddiqui, Shahbaz Ahmed & Saraswat, Amit & Ucheniya, Ravi, 2022. "Intersection Point Determination Method: A novel MPPT approach for sudden and fast changing environmental conditions," Renewable Energy, Elsevier, vol. 200(C), pages 614-632.
    12. Kermadi, Mostefa & Berkouk, El Madjid, 2017. "Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 369-386.
    13. Messalti, Sabir & Harrag, Abdelghani & Loukriz, Abdelhamid, 2017. "A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 221-233.
    14. Yinxiao Zhu & Moon Keun Kim & Huiqing Wen, 2018. "Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics," Energies, MDPI, vol. 12(1), pages 1-20, December.
    15. Mostafa Ahmed & Ibrahim Harbi & Ralph Kennel & José Rodríguez & Mohamed Abdelrahem, 2022. "Evaluation of the Main Control Strategies for Grid-Connected PV Systems," Sustainability, MDPI, vol. 14(18), pages 1-20, September.
    16. Haidar Islam & Saad Mekhilef & Noraisyah Binti Mohamed Shah & Tey Kok Soon & Mehdi Seyedmahmousian & Ben Horan & Alex Stojcevski, 2018. "Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems," Energies, MDPI, vol. 11(2), pages 1-24, February.
    17. Venkateswari, R. & Sreejith, S., 2019. "Factors influencing the efficiency of photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 376-394.
    18. Muhammad Hafeez Mohamed Hariri & Mohd Khairunaz Mat Desa & Syafrudin Masri & Muhammad Ammirrul Atiqi Mohd Zainuri, 2020. "Grid-Connected PV Generation System—Components and Challenges: A Review," Energies, MDPI, vol. 13(17), pages 1-28, August.
    19. Obeidi, Nabil & Kermadi, Mostefa & Belmadani, Bachir & Allag, Abdelkrim & Achour, Lazhar & Mesbahi, Nadhir & Mekhilef, Saad, 2023. "A modified current sensorless approach for maximum power point tracking of partially shaded photovoltaic systems," Energy, Elsevier, vol. 263(PA).
    20. Cabrera-Tobar, Ana & Bullich-Massagué, Eduard & Aragüés-Peñalba, Mònica & Gomis-Bellmunt, Oriol, 2016. "Review of advanced grid requirements for the integration of large scale photovoltaic power plants in the transmission system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 971-987.

    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:jsusta:v:13:y:2021:i:21:p:11736-:d:663512. 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.