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An Adaptive Cross-Tied Interconnection for Shaded PV Arrays: A Mathematical Analysis for Efficiency Enhancement
Corresponding Author(s) : Efendi S Wirateruna
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control,
Vol. 11, No. 2, May 2026 (Article in Progress)
Abstract
This study investigates the Adaptive Cross-Tied Interconnection (ACTI) configuration to improve the power output efficiency of photovoltaic (PV) arrays operating under partial shade conditions. The objective of this study is to develop a mathematical formulation that describes the behavior of ACTI compared to the conventional Series-Parallel (SP) configuration. Mathematical modeling is used to analyze the current distribution, voltage relationship, and the effect of shading patterns on the total output power. Simulations are performed using MATLAB/Simulink to verify the theoretical analysis results. This adaptive configuration dynamically adjusts the cross-tied based on the illumination intensity data, thus balancing the current between the shaded and normal modules. The results show that ACTI successfully reduces current mismatch losses and increases the output power without increasing circuit complexity. In a 3x3 PV array, the ACTI configuration yields a power increase of up to 48% compared to the SP configuration. In a 5x5 array, the efficiency increase ranges from 2% to 6%, depending on the shading pattern. The adaptive switching strategy maintains the current flow stability and produces a smoother power-voltage curve, allowing faster and more accurate tracking of the global maximum power point. These results demonstrate that ACTI provides an efficient, economical, and mathematically sound solution for improving the performance of PV systems under non-uniform irradiation conditions
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- M. Farghali et al., “Strategies to save energy in the context of the energy crisis: a review,” Environ Chem Lett, vol. 21, no. 4, pp. 2003–2039, 2023, doi: 10.1007/s10311-023-01591-5.
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- A. Alhejab, M. Abbasi, and S. Ahmed, “A Single Voltage Sensor Bypass Switch-Based Photovoltaic Fault Localization,” IEEE J Photovolt, pp. 1–11, 2025, doi: 10.1109/JPHOTOV.2025.3530001.
References
M. Farghali et al., “Strategies to save energy in the context of the energy crisis: a review,” Environ Chem Lett, vol. 21, no. 4, pp. 2003–2039, 2023, doi: 10.1007/s10311-023-01591-5.
N. A. Pambudi et al., “Renewable Energy in Indonesia: Current Status, Potential, and Future Development,” Sustainability, vol. 15, no. 3, 2023, doi: 10.3390/su15032342.
E. Kabir, P. Kumar, S. Kumar, A. A. Adelodun, and K.-H. Kim, “Solar energy: Potential and future prospects,” Renewable and Sustainable Energy Reviews, vol. 82, pp. 894–900, 2018, doi: https://doi.org/10.1016/j.rser.2017.09.094.
M. J. Afroni, E. S. Wirateruna, and O. Melfazen, “An Experimental Study of Partial Shading Effects on the P-V Characteristic Curve,” in 2022 11th Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), 2022, pp. 22–27. doi: 10.1109/EECCIS54468.2022.9902950.
S. M. Maharana, A. Mohapatra, C. Saiprakash, and A. Kundu, “Performance Analysis of Different PV Array Configurations under Partial Shading Condition,” in 2020 International Conference on Computational Intelligence for Smart Power System and Sustainable Energy (CISPSSE), 2020, pp. 1–5. doi: 10.1109/CISPSSE49931.2020.9212244.
E. S. Wirateruna, M. J. Afroni, and F. Badri, “Design of Maximum Power Point Tracking Photovoltaic System Based on Incremental Conductance Algorithm using Arduino Uno and Boost Converter ,” Applied Technology and Computing Science Journal, vol. 4, no. 2, pp. 101–112, 2022.
C. V Chandrakant and S. Mikkili, “A Typical Review on Static Reconfiguration Strategies in Photovoltaic Array Under Non-Uniform Shading Conditions,” CSEE Journal of Power and Energy Systems, vol. 9, no. 6, pp. 2018–2039, 2023, doi: 10.17775/CSEEJPES.2020.02520.
V. C. Chavan, S. Mikkili, and T. Senjyu, “Experimental Validation of Novel Shade Dispersion PV Reconfiguration Technique to Enhance Maximum Power Under PSCs,” CPSS Transactions on Power Electronics and Applications, vol. 8, no. 2, pp. 137–147, Jun. 2023, doi: 10.24295/CPSSTPEA.2023.00014.
A. A. Desai and S. Mikkili, “Modelling and analysis of PV configurations (alternate TCT-BL, total cross tied, series, series parallel, bridge linked and honey comb) to extract maximum power under partial shading conditions,” CSEE Journal of Power and Energy Systems, vol. PP, no. 99, 2019, doi: 10.17775/CSEEJPES.2020.00900.
H. Oufettoul, S. Motahhir, G. Aniba, M. Masud, and M. A. AlZain, “Improved TCT topology for shaded photovoltaic arrays,” Energy Reports, vol. 8, pp. 5943–5956, 2022, doi: https://doi.org/10.1016/j.egyr.2022.04.042.
C. W. Priananda, A. Rajagukguk, D. C. Riawan, Soedibyo, and M. Ashari, “New approach of maximum power point tracking for static miniature photovoltaic farm under partially shaded condition based on new cluster topology,” in 2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering, 2017, pp. 444–449. doi: 10.1109/QIR.2017.8168527.
A. Rajagukguk, C. W. Priananda, D. C. Riawan, Soedibyo, and M. Ashari, “Novel derivative cluster area methods (DCAM) for power optimization of PV farm under dinamically shading effect,” in 2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering, 2017, pp. 434–438. doi: 10.1109/QIR.2017.8168525.
M. J. Afroni and E. S. Wirateruna, “4 Section method for MPPT optimization in Solar Panel Experiments under PSC v221023,” in 2023 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS), 2023, pp. 172–177. doi: 10.1109/ICSGTEIS60500.2023.10424047.
E. S. Wirateruna and A. F. A. Millenia, “Design of MPPT PV using Particle Swarm Optimization Algorithm under Partial Shading Condition,” International Journal of Artificial Intelligence & Robotics (IJAIR), vol. 4, no. 1, pp. 24–30, May 2022, doi: 10.25139/ijair.v4i1.4327.
P. Murugesan, P. Winston David, P. Murugesan, and N. Kalyani Solaisamy, “One-step adaptive reconfiguration technique for partial shaded photovoltaic array,” Solar Energy, vol. 263, p. 111949, 2023, doi: https://doi.org/10.1016/j.solener.2023.111949.
E. S. Wirateruna, M. Ashari, and D. C. Riawan, “Estimation and Assessment of Partial Shading Patterns in Large PV Farms Using ANN Algorithm,” IEEE Access, vol. 13, pp. 139189–139202, 2025, doi: 10.1109/ACCESS.2025.3596268.
J. H. Teng, H. C. Wu, Z. H. Wu, and W. H. Huang, “Efficient Partial Shading Detection for Photovoltaic Generation Systems,” IEEE Trans Sustain Energy, vol. 14, no. 4, pp. 2249–2259, Oct. 2023, doi: 10.1109/TSTE.2023.3271298.
D. S. Pillai, J. P. Ram, A. M. Y. M. Ghias, M. A. Mahmud, and N. Rajasekar, “An Accurate, Shade Detection-Based Hybrid Maximum Power Point Tracking Approach for PV Systems,” IEEE Trans Power Electron, vol. 35, no. 6, pp. 6594–6608, Jun. 2020, doi: 10.1109/TPEL.2019.2953242.
T. S. Babu, D. Yousri, and K. Balasubramanian, “Photovoltaic Array Reconfiguration System for Maximizing the Harvested Power Using Population-Based Algorithms,” IEEE Access, vol. 8, pp. 109608–109624, 2020, doi: 10.1109/ACCESS.2020.3000988.
D. Yousri, S. B. Thanikanti, K. Balasubramanian, A. Osama, and A. Fathy, “Multi-Objective Grey Wolf Optimizer for Optimal Design of Switching Matrix for Shaded PV array Dynamic Reconfiguration,” IEEE Access, vol. 8, pp. 159931–159946, 2020, doi: 10.1109/ACCESS.2020.3018722.
T. S. Babu, J. P. Ram, T. Dragičević, M. Miyatake, F. Blaabjerg, and N. Rajasekar, “Particle Swarm Optimization Based Solar PV Array Reconfiguration of the Maximum Power Extraction Under Partial Shading Conditions,” IEEE Trans Sustain Energy, vol. 9, no. 1, pp. 74–85, 2018, doi: 10.1109/TSTE.2017.2714905.
B. Aljafari, P. R. Satpathy, and S. B. Thanikanti, “Partial shading mitigation in PV arrays through dragonfly algorithm based dynamic reconfiguration,” Energy, vol. 257, p. 124795, 2022, doi: https://doi.org/10.1016/j.energy.2022.124795.
X. Zhang, D. Meng, W. Li, T. Yu, Z. Fan, and Z. Hao, “Evolutionary based Pareto optimization algorithms for bi-objective PV array reconfiguration under partial shading conditions,” Energy Convers Manag, vol. 271, p. 116308, 2022, doi: https://doi.org/10.1016/j.enconman.2022.116308.
A. A. Teyabeen, N. B. Elhatmi, A. A. Essnid, and A. E. Jwaid, “Parameters Estimation of Solar PV Modules Based on Single-Diode Model,” in 2020 11th International Renewable Energy Congress (IREC), 2020, pp. 1–6. doi: 10.1109/IREC48820.2020.9310365.
A. Alhejab, M. Abbasi, and S. Ahmed, “A Single Voltage Sensor Bypass Switch-Based Photovoltaic Fault Localization,” IEEE J Photovolt, pp. 1–11, 2025, doi: 10.1109/JPHOTOV.2025.3530001.