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Firefly Algorithm-Based Photovoltaic Array Reconfiguration for Maximum Power Extraction during Mismatch Conditions

Author

Listed:
  • Mohammad Nor Rafiq Nazeri

    (Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, Kangar 01000, Malaysia)

  • Mohammad Faridun Naim Tajuddin

    (Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, Kangar 01000, Malaysia)

  • Thanikanti Sudhakar Babu

    (Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad 500075, India)

  • Azralmukmin Azmi

    (Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, Kangar 01000, Malaysia)

  • Maria Malvoni

    (School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • Nallapaneni Manoj Kumar

    (School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong)

Abstract

This studyaimed at improving the performance and efficiency of conventional static photovoltaic (PV) systems by introducing a metaheuristic algorithm-based approach that involves reconfiguring electrical wiring using switches under different shading profiles. Themetaheuristicalgorithmused wasthe firefly algorithm (FA), which controls the switching patterns under non-homogenous shading profiles and tracks the highest global peak of power produced by the numerous switching patterns. This study aimed to solve the current problems faced by static PV systems, such as unequal dispersion of shading affecting solar panels, multiple peaks, and hot spot phenomena, which can contribute to significant power loss and efficiency reduction. The experimental setup focusedon software development and the system or model developed in the MATLAB Simulink platform. Athorough and comprehensive analysis was done by comparing the proposed method’s overall performance and power generation with thenovel static PVseries–parallel (SP) topology and totalcross-tied (TCT) scheme. The SP configuration is widely used in the PV industry. However, the TCT configuration has superior performance and energy yield generation compared to other static PV configurations, such as the bridge-linked (BL) and honey comb (HC) configurations. The results presented in this paper provide valuable information about the proposed method’s features with regard toenhancing the overall performance and efficiency of PV arrays.

Suggested Citation

  • Mohammad Nor Rafiq Nazeri & Mohammad Faridun Naim Tajuddin & Thanikanti Sudhakar Babu & Azralmukmin Azmi & Maria Malvoni & Nallapaneni Manoj Kumar, 2021. "Firefly Algorithm-Based Photovoltaic Array Reconfiguration for Maximum Power Extraction during Mismatch Conditions," Sustainability, MDPI, vol. 13(6), pages 1-30, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3206-:d:517093
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    References listed on IDEAS

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    1. Deshkar, Shubhankar Niranjan & Dhale, Sumedh Bhaskar & Mukherjee, Jishnu Shekar & Babu, T. Sudhakar & Rajasekar, N., 2015. "Solar PV array reconfiguration under partial shading conditions for maximum power extraction using genetic algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 102-110.
    2. Balato, M. & Costanzo, L. & Vitelli, M., 2015. "Series–Parallel PV array re-configuration: Maximization of the extraction of energy and much more," Applied Energy, Elsevier, vol. 159(C), pages 145-160.
    3. 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.
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    Cited by:

    1. Aljafari, Belqasem & Satpathy, Priya Ranjan & Thanikanti, Sudhakar Babu, 2022. "Partial shading mitigation in PV arrays through dragonfly algorithm based dynamic reconfiguration," Energy, Elsevier, vol. 257(C).
    2. Astitva Kumar & Mohammad Rizwan & Uma Nangia & Muhannad Alaraj, 2021. "Grey Wolf Optimizer-Based Array Reconfiguration to Enhance Power Production from Solar Photovoltaic Plants under Different Scenarios," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    3. Mariana Durango-Flórez & Daniel González-Montoya & Luz Adriana Trejos-Grisales & Carlos Andres Ramos-Paja, 2022. "PV Array Reconfiguration Based on Genetic Algorithm for Maximum Power Extraction and Energy Impact Analysis," Sustainability, MDPI, vol. 14(7), pages 1-14, March.
    4. Fathy, Ahmed & Yousri, Dalia & Babu, Thanikanti Sudhakar & Rezk, Hegazy, 2023. "Triple X Sudoku reconfiguration for alleviating shading effect on total-cross-tied PV array," Renewable Energy, Elsevier, vol. 204(C), pages 593-604.
    5. Naveed Ahmed Malik & Naveed Ishtiaq Chaudhary & Muhammad Asif Zahoor Raja, 2023. "Firefly Optimization Heuristics for Sustainable Estimation in Power System Harmonics," Sustainability, MDPI, vol. 15(6), pages 1-20, March.

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