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

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    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).
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    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.

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