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Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm

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  • Timmidi Nagadurga

    (Department of Electrical and Electronics Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram 521230, India
    Department of Electrical and Electronics Engineering, University College of Engineering, Jawaharlal Nehru Technological University, Kakinada 533003, India)

  • Pasumarthi Venkata Ramana Lakshmi Narasimham

    (Department of Electrical and Electronics Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Kanuru 520007, India)

  • V. S. Vakula

    (Department of Electrical and Electronics Engineering, JNTUK-University College of Engineering, Vizianagaram 535003, India)

  • Ramesh Devarapalli

    (Department of Electrical Engineering, Birsa Institute of Technology Sindri, Dhanbad 828123, India)

  • Fausto Pedro García Márquez

    (Ingenium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, Spain)

Abstract

This paper proposes the application of a metaheuristic algorithm inspired by the social behavior of chimps in nature, called Chimp Optimization Algorithm (ChOA), for the maximum power point tracking of solar photovoltaic (PV) strings. In this algorithm, the chimps hunting process is mathematically articulated, and new mechanisms are designed to perform the exploration and exploitation. To evaluate the ChOA, it is applied to some fixed dimension benchmark functions and engineering problem application of tracking maximum power from solar PV systems under partial shading conditions. Partial shading condition is a common problem that appears in the solar PV modules installed in domestic areas. This shading alters the power developed by the solar PV panel, and exhibits multiple peaks on the power variation with voltage (P-V) characteristic curve. The dynamics of the solar PV system have been considered, and the mathematical model of a single objective function has been framed for tuning the optimal control parameter with the suggested algorithm. Implementing various practical shading patterns of solar PV systems with the ChOA algorithm has shown improved solar power point tracking performance compared to other algorithms in the literature.

Suggested Citation

  • Timmidi Nagadurga & Pasumarthi Venkata Ramana Lakshmi Narasimham & V. S. Vakula & Ramesh Devarapalli & Fausto Pedro García Márquez, 2021. "Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm," Energies, MDPI, vol. 14(14), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4086-:d:589729
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    References listed on IDEAS

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    1. Ramli, Makbul A.M. & Twaha, Ssennoga & Ishaque, Kashif & Al-Turki, Yusuf A., 2017. "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 144-159.
    2. Sachin Angadi & Udaykumar R. Yaragatti & Yellasiri Suresh & A. B. Raju, 2021. "System Parameter Based Performance Optimization of Solar PV Systems with Perturbation Based MPPT Algorithms," Energies, MDPI, vol. 14(7), pages 1-20, April.
    3. Peinado Gonzalo, Alfredo & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2020. "Survey of maintenance management for photovoltaic power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    4. Ali M. Eltamaly, 2021. "An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions," Energies, MDPI, vol. 14(4), pages 1-26, February.
    5. Alfredo Gil-Velasco & Carlos Aguilar-Castillo, 2021. "A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions," Energies, MDPI, vol. 14(9), pages 1-12, April.
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    Cited by:

    1. Asfand Y. Khan & Zeshan Ahmad & Tipu Sultan & Saad Alshahrani & Khazar Hayat & Muhammad Imran, 2022. "Optimization of Photovoltaic Panel Array Configurations to Reduce Lift Force Using Genetic Algorithm and CFD," Energies, MDPI, vol. 15(24), pages 1-15, December.
    2. Bilal Naji Alhasnawi & Basil H. Jasim & Arshad Naji Alhasnawi & Bishoy E. Sedhom & Ali M. Jasim & Azam Khalili & Vladimír Bureš & Alessandro Burgio & Pierluigi Siano, 2022. "A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA," Energies, MDPI, vol. 15(22), pages 1-29, November.

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