Impacts of partial shading and non-uniform irradiance in photovoltaic (PV) strings, and thus, arrays, can be mitigated by Array reconfiguration (ARC). On the other hand, the power clipping and the saturation of a PV inverter can lead to energy losses in grid-connected systems with limited maximum power point trackers (MPPTs) in their inverters. However, most ARC researchers focus on mismatched-oriented reconfiguration approaches that minimize the mismatch in each PV string to make them almost uniform. These conventional approaches aim to optimize the proxies, not the final alternating-current (AC) yield energy. Therefore, we proposed a string-level energy-first ARC method based on an Acceleration-Enhanced River Formation Dynamics (AE-RFD) algorithm. The proposed method directly maximized the delivered energy while maintaining current constraints and MPPT power limits. The proposed energy-first framework optimized the array configuration at the grid-tied inverter interface, maximizing delivered energy of multi-inputs and AC-side clipping constraints. A real grid-tied PV system of 15 kVA, 6 strings, and 3 MPPTs was utilized first to evaluate the proposed method with disturbed irradiance conditions for different MPPT architectures and a second benchmark PV system of 24 strings and 8 MPPTs. Our simulation results confirmed the effectiveness of the proposed method by demonstrating energy gains exceeding 5.5% with significant clipping reduction and enhancing the mismatch index. Comparisons with the ARC that is based on particle swarm optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) indicated that the proposed AE-RFD-based method exhibits improved robustness and stable convergence behavior.
Citation: Hatim G. Abood, Balasim M. Hussein, Waleed Khalid Shakir Al-Jubori. An energy-first reconfiguration of PV Array for Multi-MPPT systems considering inverter clipping under partial shading[J]. AIMS Energy, 2026, 14(4): 760-778. doi: 10.3934/energy.2026031
Impacts of partial shading and non-uniform irradiance in photovoltaic (PV) strings, and thus, arrays, can be mitigated by Array reconfiguration (ARC). On the other hand, the power clipping and the saturation of a PV inverter can lead to energy losses in grid-connected systems with limited maximum power point trackers (MPPTs) in their inverters. However, most ARC researchers focus on mismatched-oriented reconfiguration approaches that minimize the mismatch in each PV string to make them almost uniform. These conventional approaches aim to optimize the proxies, not the final alternating-current (AC) yield energy. Therefore, we proposed a string-level energy-first ARC method based on an Acceleration-Enhanced River Formation Dynamics (AE-RFD) algorithm. The proposed method directly maximized the delivered energy while maintaining current constraints and MPPT power limits. The proposed energy-first framework optimized the array configuration at the grid-tied inverter interface, maximizing delivered energy of multi-inputs and AC-side clipping constraints. A real grid-tied PV system of 15 kVA, 6 strings, and 3 MPPTs was utilized first to evaluate the proposed method with disturbed irradiance conditions for different MPPT architectures and a second benchmark PV system of 24 strings and 8 MPPTs. Our simulation results confirmed the effectiveness of the proposed method by demonstrating energy gains exceeding 5.5% with significant clipping reduction and enhancing the mismatch index. Comparisons with the ARC that is based on particle swarm optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) indicated that the proposed AE-RFD-based method exhibits improved robustness and stable convergence behavior.
| [1] |
Belhachat F, Larbes C (2021) PV array reconfiguration techniques for maximum power optimization under partial shading conditions: A review. Sol Energy 230: 558-582. https://doi.org/10.1016/j.solener.2021.09.089 doi: 10.1016/j.solener.2021.09.089
|
| [2] |
Sharma D, Jalil MF, Ansari MS, et al. (2023) A review of PV array reconfiguration techniques for maximum power extraction under partial shading conditions. Optik 275: 170559. https://doi.org/10.1016/j.ijleo.2023.170559 doi: 10.1016/j.ijleo.2023.170559
|
| [3] |
Al-Shahri OA, Ismail FB, Al-Muhsen NFO, et al. (2022) An improved model and performance analysis for grid-connected photovoltaic system in Oman. Heliyon 8: e12237. https://doi.org/10.1016/j.heliyon.2022.e12237 doi: 10.1016/j.heliyon.2022.e12237
|
| [4] | Naser RA, Altahir AAR, Ahmed AA, et al. (2025) Enhancing solar panel efficiency in harsh climates: An UAV-Integrated WSN cleaning approach. Lecture Notes in Networks and Systems BT—Proceedings of Data Analytics and Management (ICDAM 2025) 1597: 64-80. https://doi.org/10.1007/978-3-032-02831-0_6 |
| [5] |
Pachauri RK, Mahela OP, Sharma A, et al. (2020) Impact of partial shading on various PV array configurations and different modeling approaches: A comprehensive review. IEEE Access 8: 181375-181403. https://doi.org/10.1109/ACCESS.2020.3028473 doi: 10.1109/ACCESS.2020.3028473
|
| [6] |
Durango-Flórez M, González-Montoya D, Trejos-Grisales LA, et al. (2022) PV array reconfiguration based on genetic algorithm for maximum power extraction and energy impact analysis. Sustainability 14: 3764. https://doi.org/10.3390/su14073764 doi: 10.3390/su14073764
|
| [7] |
Babu TS, Ram JP, Dragicevic T, et al. (2018) Particle swarm optimization based solar PV array reconfiguration of the maximum power extraction under partial shading conditions. IEEE Trans Sustain Energy 9: 74-85. https://doi.org/10.1109/TSTE.2017.2714905 doi: 10.1109/TSTE.2017.2714905
|
| [8] |
Tazally MAIA, Tajuddin MFN, Azmi A, et al. (2018) Differential evolution based solar photovoltaic array reconfiguration algorithm for optimal energy extraction during partial shading condition. Int J Power Electron Drive Syst 9: 1397. https://doi.org/10.11591/ijpeds.v9.i3.pp1397-1405 doi: 10.11591/ijpeds.v9.i3.pp1397-1405
|
| [9] |
Pachauri RK, Kansal I, Babu TS, et al. (2021) Power losses reduction of solar PV systems under partial shading conditions using re-allocation of PV module-fixed electrical connections. IEEE Access 9: 94789-94812. https://doi.org/10.1109/ACCESS.2021.3093954 doi: 10.1109/ACCESS.2021.3093954
|
| [10] |
Muñoz-Rodríguez FJ, Sánchez-Jiménez JL, Robles C, et al. (2026) String level DC performance analysis in rooftop photovoltaic systems with multi-MPPT inverters. Sol Energy 308: 114359. https://doi.org/10.1016/j.solener.2026.114359 doi: 10.1016/j.solener.2026.114359
|
| [11] | Gbadega PA, Balogun OA, Akindeji KT (2025) Comparative assessment of MPPT techniques for solar PV systems under uniform insolation and partial shading conditions. 2025 33rd Southern African Universities Power Engineering Conference (SAUPEC), 1-6. https://doi.org/10.1109/SAUPEC65723.2025.10944400 |
| [12] |
Kadhim NA, Obed AA, Abid AJ, et al. (2024) A systematic review for reconfiguring photovoltaic arrays under conditions of partial shading. Electr Eng Tech J 1: 20-34. https://doi.org/10.51173/eetj.v1i1.6 doi: 10.51173/eetj.v1i1.6
|
| [13] |
Sai Krishna G, Moger T (2019) Improved SuDoKu reconfiguration technique for total‑cross‑tied PV array to enhance maximum power under partial shading conditions. Renew Sustain Energy Rev 109: 333-348. https://doi.org/10.1016/j.rser.2019.04.037 doi: 10.1016/j.rser.2019.04.037
|
| [14] |
dos Santos Vicente P, Vicente EM, Simoes MG, et al. (2020) Shading position effects on photovoltaic panel output power. Int Trans Electr Energy Syst 30: 1-19. https://doi.org/10.1002/2050-7038.12163 doi: 10.1002/2050-7038.12163
|
| [15] |
Said SZ, Islam SZ, Radzi NH, et al. (2024) Dust impact on solar PV performance: A critical review of optimal cleaning techniques for yield enhancement across varied environmental conditions. Energy Rep 12: 1121-1141. https://doi.org/10.1016/j.egyr.2024.06.024 doi: 10.1016/j.egyr.2024.06.024
|
| [16] |
Agor AD, Asante M, Hayfron-Acquah JB, et al. (2024) A power-aware river formation dynamics routing algorithm for enhanced longevity in MANETs. Int J Comput Networks Appl 11: 274-289. https://doi.org/10.22247/ijcna/2024/17 doi: 10.22247/ijcna/2024/17
|
| [17] | Abood HG, Sreeram V, Mishra Y (2016) Optimal placement of PMUs using river formation dynamics (RFD). 2016 IEEE International Conference on Power System Technology (POWERCON), 1-6. https://doi.org/10.1109/POWERCON.2016.7827879 |
| [18] |
Rabanal P, Rodríguez I, Rubio F (2013) Testing restorable systems: formal definition and heuristic solution based on river formation dynamics. Form Asp Comput 25: 743-768. https://doi.org/10.1007/s00165-011-0206-3 doi: 10.1007/s00165-011-0206-3
|
| [19] | Rabanal P, Rodríguez I, Rubio F (2008) Solving dynamic TSP by using river formation dynamics. 2008 Fourth International Conference on Natural Computation, 246-250. https://doi.org/10.1109/ICNC.2008.760 |
| [20] |
Kasim NK, Obaid NM, Abood HG, et al. (2021) Experimental study for the effect of dust cleaning on the performance of grid-tied photovoltaic solar systems. Int J Electr Comput Eng 11: 74-83. https://doi.org/10.11591/ijece.v11i1.pp74-83 doi: 10.11591/ijece.v11i1.pp74-83
|
| [21] | Obaid NM, Kasim NK, Hashim ET (2019) Performance assessment of first grid-tied PV solar system under Baghdad city climate condition. Iraqi J Sci Technol 10: 63-71. Available from: https://iasj.rdd.edu.iq/journals/journal/issue/11465. |
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Hatim G. Abood, Balasim M. Hussein, Waleed Khalid Shakir Al-Jubori. An energy-first reconfiguration of PV Array for Multi-MPPT systems considering inverter clipping under partial shading[J]. AIMS Energy, 2026, 14(4): 760-778. doi: 10.3934/energy.2026031
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