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Archimedes optimization algorithm (AOA)-Based global maximum power point tracking for a photovoltaic system under partial and complex shading conditions

Author

Listed:
  • Sajid, Injila
  • Sarwar, Adil
  • Tariq, Mohd
  • Bakhsh, Farhad Ilahi
  • Ahmad, Shafiq
  • Shah Noor Mohamed, Adamali

Abstract

During partial shading conditions (PSCs), the efficiency of power transfer in a Photovoltaic (PV) system decreases significantly, which can result in the formation of hotspots in the PV array. Although the insertion of bypass diodes can alleviate this issue, it can result in multiple power peaks on the power-voltage (P–V) characteristics and complicate the process of maximum power tracking. To tackle this problem, using metaheuristic algorithms for Maximum Power Point Tracking (MPPT) can yield favourable results by avoiding convergence to local power peaks and reducing computation stress on the microcontroller. However, continuous research is required in this area due to variations in the performance of metaheuristic algorithms. Therefore, this work introduces a novel MPPT approach based on the Archimedes Optimization Algorithm (AOA) for the successful capture of the Maximum Power Point (MPP) under various PS scenarios. The performance of AOA is evaluated against the other state-of-the-art algorithms such as particle swarm optimization (PSO), Jaya, and the newly proposed variant of Jaya called the adaptive Jaya (A-Jaya). The proposed MPPT method is analysed in MATLAB/Simulink software and validated using real-time results obtained from Typhoon Hardware-in-the-loop (HIL)-402 emulator. The proposed algorithm outperforms the previous algorithms, as evidenced by a comparison of the results in terms of power tracking efficiency, tracking time, and the quantity of power fluctuations.

Suggested Citation

  • Sajid, Injila & Sarwar, Adil & Tariq, Mohd & Bakhsh, Farhad Ilahi & Ahmad, Shafiq & Shah Noor Mohamed, Adamali, 2023. "Archimedes optimization algorithm (AOA)-Based global maximum power point tracking for a photovoltaic system under partial and complex shading conditions," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s036054422302563x
    DOI: 10.1016/j.energy.2023.129169
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    References listed on IDEAS

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    1. 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.
    2. Yadav, Anurag Singh & Mukherjee, V., 2021. "Conventional and advanced PV array configurations to extract maximum power under partial shading conditions: A review," Renewable Energy, Elsevier, vol. 178(C), pages 977-1005.
    3. Danandeh, M.A. & Mousavi G., S.M., 2018. "Comparative and comprehensive review of maximum power point tracking methods for PV cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2743-2767.
    4. Eltamaly, Ali M. & Al-Saud, M.S. & Abokhalil, Ahmed G. & Farh, Hassan M.H., 2020. "Simulation and experimental validation of fast adaptive particle swarm optimization strategy for photovoltaic global peak tracker under dynamic partial shading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
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    1. Xiang, Qilin & Xu, Lijie & Yuan, Chengqing, 2026. "A reinforcement learning-based Synergistic Hybrid Evolutionary Algorithm for multi-angle shipboard photovoltaic system MPPT under dynamic navigational shading," Renewable Energy, Elsevier, vol. 260(C).
    2. Yang, Jun & Peng, Qiao & Liu, Tianqi & Liu, Youbo & Gu, Tingyun & Meng, Jinhao, 2025. "Fast global flexible power point tracking of photovoltaic systems under partial shading condition with tracking-affiliated environmental parameter estimation," Energy, Elsevier, vol. 318(C).
    3. Liu, Wenzhuo & Lu, Mengying & Bai, Haoliang & Liu, Zhe & Lv, Song, 2026. "All-day autonomous MPPT energy storage PV-TEG hybrid system based on dual axis solar tracker," Renewable Energy, Elsevier, vol. 256(PE).
    4. Hegazy Rezk & Usama Hamed Issa & Anas Bouaouda & Fatma A. Hashim, 2025. "A Novel Improved Gradient‐Based Optimizer for Single‐Sensor Global MPPT of PV System," Journal of Mathematics, John Wiley & Sons, vol. 2025(1).

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