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Enhanced power extraction in shaded photovoltaic arrays using dynamic reconfiguration with multi-objective nutcracker optimization algorithm

Author

Listed:
  • Eswaramoorthy, K.
  • Viswanatha Rao, J.
  • Babu, Viswaprakash
  • Mukilan, P.

Abstract

Photovoltaic (PV) array performance is notably affected by Partial Shading Conditions (PSCs) by causing mismatch losses, reducing energy output, and compromising system reliability. The proposed study outlines a dynamic reconfiguration strategy for PV arrays under PSC using the Multi-Objective Nutcracker Optimization Algorithm (MONOA). MONOA is a recently developed bio-inspired metaheuristic designed for multi-objective optimization problems. It integrates fast opposition-based learning, crowding distance and non-dominated sorting to effectively search for optimal PV switching configurations that maximize output power and minimize current imbalance and switching activity. A Total Cross-Tied (TCT) based 9 × 9 PV array is used as test system, and a novel Objective Function (OF) is proposed for enhancing solution quality without requiring weight tuning. The performance of MONOA is compared against well-established algorithms such as Improved Prairie Dog Optimization (IPDO), Atom Search Optimization (ASO), and African Vultures Optimization Algorithm (AVOA) under two different shading patterns. Simulation results demonstrate that MONOA consistently achieves higher power output, better fill factor, lower mismatch loss, and the fastest execution time among all tested methods.

Suggested Citation

  • Eswaramoorthy, K. & Viswanatha Rao, J. & Babu, Viswaprakash & Mukilan, P., 2026. "Enhanced power extraction in shaded photovoltaic arrays using dynamic reconfiguration with multi-objective nutcracker optimization algorithm," Renewable Energy, Elsevier, vol. 257(C).
    • Handle: RePEc:eee:renene:v:257:y:2026:i:c:s0960148125024188
    DOI: 10.1016/j.renene.2025.124754
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    References listed on IDEAS

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    1. Mohammed Alkahtani & Zuyu Wu & Colin Sokol Kuka & Muflah S. Alahammad & Kai Ni, 2020. "A Novel PV Array Reconfiguration Algorithm Approach to Optimising Power Generation across Non-Uniformly Aged PV Arrays by Merely Repositioning," J, MDPI, vol. 3(1), pages 1-22, February.
    2. 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.
    3. 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.
    4. Solaisamy, Nithya Kalyani & David, Prince Winston & S, Devakirubakaran & Murugesan, Palpandian, 2025. "Performance improvement of partial shaded solar PV system using Unbalanced Adaptive Dynamic Reconfiguration technique," Renewable Energy, Elsevier, vol. 246(C).
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