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Partial shading mitigation in PV arrays through dragonfly algorithm based dynamic reconfiguration

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  • Aljafari, Belqasem
  • Satpathy, Priya Ranjan
  • Thanikanti, Sudhakar Babu

Abstract

The susceptibility of the PV array towards partial shading has raised a major reliability concern for efficient power generation. The partial shading forces the arrays to generate lower power along with forming non-convex curves causing complicated operation of power tracking algorithms. Hence, to reduce the losses, various conventional configurations and reconfiguration techniques exist with vulnerabilities in terms of reliable power enhancement and complexity. In this paper, a highly reliable, less complex, and fast array reconfiguration based on the Dragonfly algorithm (DA) optimization with a higher power enhancement capability, lower computational time, and hasty convergence is proposed for unwanted shading losses reduction in arrays. The effectiveness of the proposed reconfiguration is evaluated against conventional configurations and three pre-existing reconfiguration techniques under various artificial shading cases via power generation, losses, and efficiencies using simulation and experimental analysis for 3 × 3 and 9 × 9 arrays. From the conducted analysis, it has been established that the DA reconfiguration has 22%, 10.10%, 15.36%, 5.85%, 2.95%, 2.55%, and 1.07% higher power generation than the conventional configurations, electrical reconfiguration, SD-PAR, Sudoku, GA, PSO, and EAR respectively with reduced switches counts.

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  • 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).
    • Handle: RePEc:eee:energy:v:257:y:2022:i:c:s036054422201698x
    DOI: 10.1016/j.energy.2022.124795
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    References listed on IDEAS

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    1. Belqasem Aljafari & Priya Ranjan Satpathy & Siva Rama Krishna Madeti & Pradeep Vishnuram & Sudhakar Babu Thanikanti, 2022. "Reliability Enhancement of Photovoltaic Systems under Partial Shading through a Two-Step Module Placement Approach," Energies, MDPI, vol. 15(20), pages 1-27, October.
    2. Zhang, Xiaoshun & Meng, Die & Cai, Jiahui & Zhang, Guiyuan & Yu, Tao & Pan, Feng & Yang, Yuyao, 2023. "A swarm based double Q-learning for optimal PV array reconfiguration with a coordinated control of hydrogen energy storage system," Energy, Elsevier, vol. 266(C).
    3. Alharbi, Abdullah G. & Fathy, Ahmed & Rezk, Hegazy & Abdelkareem, Mohammad Ali & Olabi, A.G., 2023. "An efficient war strategy optimization reconfiguration method for improving the PV array generated power," Energy, Elsevier, vol. 283(C).
    4. Satpathy, Priya Ranjan & Aljafari, Belqasem & Thanikanti, Sudhakar Babu & Sharma, Renu, 2023. "An efficient power extraction technique for improved performance and reliability of solar PV arrays during partial shading," Energy, Elsevier, vol. 282(C).
    5. Belqasem Aljafari & Siva Rama Krishna Madeti & Priya Ranjan Satpathy & Sudhakar Babu Thanikanti & Bamidele Victor Ayodele, 2022. "Automatic Monitoring System for Online Module-Level Fault Detection in Grid-Tied Photovoltaic Plants," Energies, MDPI, vol. 15(20), pages 1-28, October.
    6. Mao, Mingxuan & Chen, Siyu & Zhao, Liuqing & Feng, Xinying & Ma, Fuping, 2023. "Pavement PV array reconfiguration strategy based on traveling salesman problem," Energy, Elsevier, vol. 284(C).
    7. Ahmed Al Mansur & Md. Ruhul Amin & Molla Shahadat Hossain Lipu & Md. Imamul Islam & Ratil H. Ashique & Zubaeer Bin Shams & Mohammad Asif ul Haq & Md. Hasan Maruf & ASM Shihavuddin, 2023. "The Effects of Non-Uniformly-Aged Photovoltaic Array on Mismatch Power Loss: A Practical Investigation towards Novel Hybrid Array Configurations," Sustainability, MDPI, vol. 15(17), pages 1-17, September.

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