A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Particle swarm optimization (PSO) is envisioned as potential solution to overcome maximum power point tracking (MPPT) problems. Nevertheless, conventional PSO suffers from large transient oscillation, slow convergence and tedious parameter tuning when tracking global MPP (GMPP) under partial shading...
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my.uniten.dspace-342112024-10-14T11:18:27Z A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition Koh J.S. Tan R.H.G. Lim W.H. Tan N.M.L. 58127236400 35325391900 57224979685 24537965000 Maximum power point tracking partial shading particle swarm optimization perturb and observe Local search (optimization) Particle swarm optimization (PSO) Convergence Local search Maximum Power Point Tracking Partial shading Particle swarm Particle swarm optimization Partitioning algorithms Perturb and observe Search method Swarm optimization Maximum power point trackers Particle swarm optimization (PSO) is envisioned as potential solution to overcome maximum power point tracking (MPPT) problems. Nevertheless, conventional PSO suffers from large transient oscillation, slow convergence and tedious parameter tuning when tracking global MPP (GMPP) under partial shading conditions (PSC), leading to poor efficiency and significant power loss. Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. A modified initialization scheme that leverages grid partitioning and oppositional-based learning is incorporated to produce an evenly distributed initial population across P-V curve. Additionally, a rank-based selection scheme is adopted to choose best half of population for subsequent global and local search modes. A modified global search method with fewer parameters is devised to rapidly identify approximated location of GMPP. Finally, a modified local search method using Perturb and Observe with adaptive step size method (P&O-ASM) is proposed to refine the near-optimal duty cycle and track GMPP with negligible oscillations. MPSO-HALS is implemented into low-cost microcontroller for real-time application. Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE. Final 2024-10-14T03:18:27Z 2024-10-14T03:18:27Z 2023 Article 10.1109/TSTE.2023.3250710 2-s2.0-85149377022 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149377022&doi=10.1109%2fTSTE.2023.3250710&partnerID=40&md5=6847bfa2326de184310973d980695f65 https://irepository.uniten.edu.my/handle/123456789/34211 14 3 1822 1834 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Maximum power point tracking partial shading particle swarm optimization perturb and observe Local search (optimization) Particle swarm optimization (PSO) Convergence Local search Maximum Power Point Tracking Partial shading Particle swarm Particle swarm optimization Partitioning algorithms Perturb and observe Search method Swarm optimization Maximum power point trackers |
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Maximum power point tracking partial shading particle swarm optimization perturb and observe Local search (optimization) Particle swarm optimization (PSO) Convergence Local search Maximum Power Point Tracking Partial shading Particle swarm Particle swarm optimization Partitioning algorithms Perturb and observe Search method Swarm optimization Maximum power point trackers Koh J.S. Tan R.H.G. Lim W.H. Tan N.M.L. A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition |
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Particle swarm optimization (PSO) is envisioned as potential solution to overcome maximum power point tracking (MPPT) problems. Nevertheless, conventional PSO suffers from large transient oscillation, slow convergence and tedious parameter tuning when tracking global MPP (GMPP) under partial shading conditions (PSC), leading to poor efficiency and significant power loss. Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. A modified initialization scheme that leverages grid partitioning and oppositional-based learning is incorporated to produce an evenly distributed initial population across P-V curve. Additionally, a rank-based selection scheme is adopted to choose best half of population for subsequent global and local search modes. A modified global search method with fewer parameters is devised to rapidly identify approximated location of GMPP. Finally, a modified local search method using Perturb and Observe with adaptive step size method (P&O-ASM) is proposed to refine the near-optimal duty cycle and track GMPP with negligible oscillations. MPSO-HALS is implemented into low-cost microcontroller for real-time application. Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE. |
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58127236400 |
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58127236400 Koh J.S. Tan R.H.G. Lim W.H. Tan N.M.L. |
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Koh J.S. Tan R.H.G. Lim W.H. Tan N.M.L. |
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Koh J.S. |
title |
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition |
title_short |
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition |
title_full |
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition |
title_fullStr |
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition |
title_full_unstemmed |
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition |
title_sort |
modified particle swarm optimization for efficient maximum power point tracking under partial shading condition |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2024 |
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1814061171640107008 |
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13.209306 |