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A modified cat swarm optimization based maximum power point tracking method for photovoltaic system under partially shaded condition

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  • Guo, Lei
  • Meng, Zhuo
  • Sun, Yize
  • Wang, Libiao

Abstract

When photovoltaic (PV) array is operated under partially shaded condition (PSC), power-voltage curve will show multiply peaks. This causes the inability of conventional maximum power point tracking (MPPT) methods such as hill climbing (HC). To deal with this problem, this paper proposes a new MPPT method based on a modified cat swarm optimization (MCSO) to achieve global maximum power point (GMPP) tracking. To assess the performance of proposed method, different simulations and experiments have been carried out. The proposed method can successfully track GMPP under different PSCs. Furthermore, MCSO based MPPT method shows a high tracking accuracy and convergence speed as compared with other MPPT methods.

Suggested Citation

  • Guo, Lei & Meng, Zhuo & Sun, Yize & Wang, Libiao, 2018. "A modified cat swarm optimization based maximum power point tracking method for photovoltaic system under partially shaded condition," Energy, Elsevier, vol. 144(C), pages 501-514.
    • Handle: RePEc:eee:energy:v:144:y:2018:i:c:p:501-514
    DOI: 10.1016/j.energy.2017.12.059
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    References listed on IDEAS

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    1. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
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    5. Ishaque, Kashif & Salam, Zainal & Shamsudin, Amir & Amjad, Muhammad, 2012. "A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 99(C), pages 414-422.
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    Cited by:

    1. Dalia Yousri & Thanikanti Sudhakar Babu & Dalia Allam & Vigna. K. Ramachandaramurthy & Eman Beshr & Magdy. B. Eteiba, 2019. "Fractional Chaos Maps with Flower Pollination Algorithm for Partial Shading Mitigation of Photovoltaic Systems," Energies, MDPI, vol. 12(18), pages 1-27, September.
    2. Kishore, D.J. Krishna & Mohamed, M.R. & Sudhakar, K. & Peddakapu, K., 2023. "Swarm intelligence-based MPPT design for PV systems under diverse partial shading conditions," Energy, Elsevier, vol. 265(C).
    3. Hou, Hui & Xu, Tao & Wu, Xixiu & Wang, Huan & Tang, Aihong & Chen, Yangyang, 2020. "Optimal capacity configuration of the wind-photovoltaic-storage hybrid power system based on gravity energy storage system," Applied Energy, Elsevier, vol. 271(C).
    4. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    5. Ahmad, Riaz & Murtaza, Ali F. & Sher, Hadeed Ahmed, 2019. "Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 82-102.
    6. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    7. Sampath Kumar Vankadara & Shamik Chatterjee & Praveen Kumar Balachandran & Lucian Mihet-Popa, 2022. "Marine Predator Algorithm (MPA)-Based MPPT Technique for Solar PV Systems under Partial Shading Conditions," Energies, MDPI, vol. 15(17), pages 1-16, August.

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