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An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System

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  • Muqaddas Elahi

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Hafiz Muhammad Ashraf

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Chul-Hwan Kim

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

Abstract

A PV system’s operation highly depends on weather conditions. In case of varying irradiances or load changes, there is a power mismatch between various modules of the PV array. This power mismatch causes instability in the output of the PV system and deteriorates the overall system efficiency. To overcome instability and lower efficiency problems, and to extract maximum power from the PV system, various maximum power point tracking (MPPT) techniques are employed. The success of these techniques depends on the identification of the actual operating conditions of the system. This article proposes a hybrid maximum power point tracking (MPPT) technique that is capable of efficiently differentiating between uniform irradiance, non-uniform irradiance, and load variations on the PV system. Based on the identified operating conditions, the proposed method uses modified perturb and observe (Modified P&O) to cope with uniform irradiance variations and chimp optimization algorithms (ChOA) for non-uniform conditions to track the oscillation free maximum power-point. The proposed method is implemented and verified using a 4 × 3 PV array model in MATLAB Simulink software. Different cases of uniformly changing irradiance and non-uniformly changing irradiance are applied to test the performance of the proposed hybrid technique. The load varying conditions are performed by applying a variable load resistor. The authenticity of the proposed hybrid technique is critically evaluated against the well-known and most widely used optimization techniques of modified perturb and observe (Modified P&O), particle swarm optimization (PSO), flower pollination algorithm (FPA), and grey wolf optimization (GWO). The results demonstrate the superiority of the proposed technique in oscillation-free tracking of global maximum power point (GMPP) in a minimum tracking time of 0.4 s and 0.15 s, and steady-state MPPT efficiency of 96.92% and 99.54% under uniform and non-uniform irradiance conditions, respectively.

Suggested Citation

  • Muqaddas Elahi & Hafiz Muhammad Ashraf & Chul-Hwan Kim, 2022. "An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System," Energies, MDPI, vol. 15(4), pages 1-26, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1549-:d:753625
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    References listed on IDEAS

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    1. Ahmed, Jubaer & Salam, Zainal, 2015. "A critical evaluation on maximum power point tracking methods for partial shading in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 933-953.
    2. Temitayo O. Olowu & Aditya Sundararajan & Masood Moghaddami & Arif I. Sarwat, 2018. "Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey," Energies, MDPI, vol. 11(7), pages 1-32, July.
    3. Chih-Chiang Hua & Yu-Jun Zhan, 2021. "A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems," Energies, MDPI, vol. 14(18), pages 1-16, September.
    4. Ehab Mohamed Ali & Ahmed K. Abdelsalam & Karim H. Youssef & Ahmed A. Hossam-Eldin, 2021. "An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions," Energies, MDPI, vol. 14(21), pages 1-21, November.
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