IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i5p2380-d1085282.html
   My bibliography  Save this article

The Maximum Power Point Tracking (MPPT) of a Partially Shaded PV Array for Optimization Using the Antlion Algorithm

Author

Listed:
  • Muhammad Jamshed Abbass

    (Faculty of Electrical Engineering, Wrocław University of Science and Technology, 50-370 Wroclaw, Poland)

  • Robert Lis

    (Faculty of Electrical Engineering, Wrocław University of Science and Technology, 50-370 Wroclaw, Poland)

  • Faisal Saleem

    (Department of Measurements and Control Systems, Silesian University of Technology, 44-100 Gliwice, Poland)

Abstract

The antlion optimizer (ALO) algorithm is used in this article for maximum power point tracking (MPPT) of a solar array. The solar array consists of a single module, while there are 20 cells in the module. The voltage and current ratings of each cell are 2 V and 2.5 A, making a 100 W array in ideal condition. However, the voltage and current characteristics of the PV cell are unable to achieve maximum power. Therefore, the ALO was used for MPPT. The results of the ALO are compared with the traditional metaheuristic approaches, perturb and observe ( P & O ) and flower pollination (FP) algorithms. Comparison of the ALO with the stated algorithms is conducted for two cases: when solar irradiance is 1000 W/m 2 and when it drops to 200 W/m 2 at first then reaches 1000 W/m 2 . The change of irradiance is performed to simulate the partial shading condition. The simulation results depict that maximum power for the first case using the ALO reaches 91.3 W in just 0.05 s, while the P & O and PFA reach 90 W after 0.64 and 2 s, respectively. For the case of partial shading, maximum power using the ALO drops to 55 W when irradiance decreases to 200 W/m 2 and then increases with the increase in irradiance reaching 91.3 W which clearly shows that the ALO outperforms the P&O and FPA.

Suggested Citation

  • Muhammad Jamshed Abbass & Robert Lis & Faisal Saleem, 2023. "The Maximum Power Point Tracking (MPPT) of a Partially Shaded PV Array for Optimization Using the Antlion Algorithm," Energies, MDPI, vol. 16(5), pages 1-13, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2380-:d:1085282
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/5/2380/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/5/2380/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hong, Ying-Yi & Beltran, Angelo A. & Paglinawan, Arnold C., 2018. "A robust design of maximum power point tracking using Taguchi method for stand-alone PV system," Applied Energy, Elsevier, vol. 211(C), pages 50-63.
    2. Mohanty, Parimita & Bhuvaneswari, G. & Balasubramanian, R. & Dhaliwal, Navdeep Kaur, 2014. "MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 581-593.
    3. Zahedi, A., 2010. "Australian renewable energy progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2208-2213, October.
    4. Pan, Jeng-Shyang & Tian, Ai-Qing & Snášel, Václav & Kong, Lingping & Chu, Shu-Chuan, 2022. "Maximum power point tracking and parameter estimation for multiple-photovoltaic arrays based on enhanced pigeon-inspired optimization with Taguchi method," Energy, Elsevier, vol. 251(C).
    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. Rahat Javaid & Umair Yaqub Qazi, 2023. "Advances in CO 2 -Free Energy Technologies," Energies, MDPI, vol. 16(13), pages 1-3, June.

    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. Mostafa Esmaeili Shayan & Gholamhassan Najafi & Barat Ghobadian & Shiva Gorjian & Mohamed Mazlan & Mehdi Samami & Alireza Shabanzadeh, 2022. "Flexible Photovoltaic System on Non-Conventional Surfaces: A Techno-Economic Analysis," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
    2. 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).
    3. Ridha, Hussein Mohammed & Gomes, Chandima & Hizam, Hashim & Ahmadipour, Masoud & Heidari, Ali Asghar & Chen, Huiling, 2021. "Multi-objective optimization and multi-criteria decision-making methods for optimal design of standalone photovoltaic system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    4. Martins, Ana Cravinho & Marques, Rui Cunha & Cruz, Carlos Oliveira, 2011. "Public-private partnerships for wind power generation: The Portuguese case," Energy Policy, Elsevier, vol. 39(1), pages 94-104, January.
    5. Kaldellis, John K. & Zafirakis, D., 2011. "The wind energy (r)evolution: A short review of a long history," Renewable Energy, Elsevier, vol. 36(7), pages 1887-1901.
    6. Vavilapalli, Sridhar & Umashankar, S. & Sanjeevikumar, P. & Ramachandaramurthy, Vigna K. & Mihet-Popa, Lucian & Fedák, Viliam, 2018. "Three-stage control architecture for cascaded H-Bridge inverters in large-scale PV systems – Real time simulation validation," Applied Energy, Elsevier, vol. 229(C), pages 1111-1127.
    7. Hua, Yaping & Oliphant, Monica & Hu, Eric Jing, 2016. "Development of renewable energy in Australia and China: A comparison of policies and status," Renewable Energy, Elsevier, vol. 85(C), pages 1044-1051.
    8. 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.
    9. Byrnes, Liam & Brown, Colin & Foster, John & Wagner, Liam D., 2013. "Australian renewable energy policy: Barriers and challenges," Renewable Energy, Elsevier, vol. 60(C), pages 711-721.
    10. Aleksandra Sus & Rafał Trzaska & Maciej Wilczyński & Joanna Hołub-Iwan, 2023. "Strategies of Energy Suppliers and Consumer Awareness in Green Energy Optics," Energies, MDPI, vol. 16(4), pages 1-23, February.
    11. Li, Shaowu, 2016. "Linear equivalent models at the maximum power point based on variable weather parameters for photovoltaic cell," Applied Energy, Elsevier, vol. 182(C), pages 94-104.
    12. Sajid Sarwar & Muhammad Annas Hafeez & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Krzysztof Ejsmont, 2022. "A Horse Herd Optimization Algorithm (HOA)-Based MPPT Technique under Partial and Complex Partial Shading Conditions," Energies, MDPI, vol. 15(5), pages 1-22, March.
    13. Yasir Alsaedi & Gurudeo Anand Tularam & Victor Wong, 2020. "Impact of Solar and Wind Prices on the Integrated Global Electricity Spot and Options Markets: A Time Series Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 337-353.
    14. Bahadori, Alireza & Zendehboudi, Sohrab & Zahedi, Gholamreza, 2013. "A review of geothermal energy resources in Australia: Current status and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 29-34.
    15. 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).
    16. Boukenoui, R. & Ghanes, M. & Barbot, J.-P. & Bradai, R. & Mellit, A. & Salhi, H., 2017. "Experimental assessment of Maximum Power Point Tracking methods for photovoltaic systems," Energy, Elsevier, vol. 132(C), pages 324-340.
    17. Gao, Fang & Hu, Rongzhao & Yin, Linfei, 2023. "Variable boundary reinforcement learning for maximum power point tracking of photovoltaic grid-connected systems," Energy, Elsevier, vol. 264(C).
    18. Prasad, Ramendra & Ali, Mumtaz & Kwan, Paul & Khan, Huma, 2019. "Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation," Applied Energy, Elsevier, vol. 236(C), pages 778-792.
    19. Byrne, John & Taminiau, Job & Kurdgelashvili, Lado & Kim, Kyung Nam, 2015. "A review of the solar city concept and methods to assess rooftop solar electric potential, with an illustrative application to the city of Seoul," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 830-844.
    20. Chapman, Andrew J. & McLellan, Benjamin & Tezuka, Tetsuo, 2016. "Residential solar PV policy: An analysis of impacts, successes and failures in the Australian case," Renewable Energy, Elsevier, vol. 86(C), pages 1265-1279.

    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:16:y:2023:i:5:p:2380-:d:1085282. 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.