Forthcoming

Hybrid Adaptive MPPT Algorithm with Intelligent Exploration and Dither-Based Tracking for PV Systems

Authors

DOI:

https://doi.org/10.64470/elene.2025.1017

Keywords:

Adaptive Control, Global Maximum Power Point, Incremental Conductance, MPPT, Partial Shading, Photovoltaic, PV Systems, P&O

Abstract

This paper proposes an improved maximum power point tracking (MPPT) approach by developing a hybrid Perturb and Observe (P&O) and Incremental Conductance (INC) algorithm based on adaptive control, considering both existing influential perturbations, such as temperature and insolation changes, and integrating the kinks. The proposed method leverages P&O's fast decision-making capability for dynamic response and INC's slope estimation technique for higher precision around the maximum power point (MPP). Moreover, dither-gradient estimation and an adaptive exploration strategy are included to make the model more robust against noise and local maxima in partial shading. The controller works in two coordinated modes—Track and Explore—for achieving rapid convergence as well as steady-state stability. The oscillations are suppressed, and re-explorations can be made when the environment changes a lot, with a combination of dynamic reference power, exponential moving average (EMA) filtering, and irradiance-drop detection. The MATLAB/simulation results verified that the introduced hybrid P&O–Inc algorithm provides faster MPP tracking, better steady-state performance, and better tracking ability in PSC as well as under changing irradiances than other conventional detached MPPT methods.

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References

Ahmad, M. E., Numan, A. H., & Mahmood, D. Y. (2022). A comparative study of perturb and observe (P&O) and incremental conductance (INC) PV MPPT techniques at different radiation and temperature conditions. Eng. Technol. J, 40(2), 376-385. https://doi.org/http://doi.org/10.30684/etj.v40i2.2189

Alshareef, M. J. (2025). An enhanced fractional open circuit voltage MPPT method for rapid and precise MPP tracking in standalone photovoltaic systems. IEEE Access. https://doi.org/https://doi.org/10.1109/ACCESS.2025.3543327

Azad, M. L., Das, S., Sadhu, P. K., Satpati, B., Gupta, A., & Arvind, P. (2017). P&O algorithm based MPPT technique for solar PV system under different weather conditions. 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT),

Bakare, M. S., Abdulkarim, A., Shuaibu, A. N., & Muhamad, M. M. (2025). Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions. Scientific Reports, 15(1), 5890. https://doi.org/https://doi.org/10.1038/s41598-025-90417-1

Bouksaim, M., Mekhfioui, M., & Srifi, M. N. (2025). A Comprehensive Decade-Long Review of Advanced MPPT Algorithms for Enhanced Photovoltaic Efficiency. Solar,

Chowdhury, S. B. R., Mukherjee, A., & Gayen, P. K. (2021). Maximum power point tracking of photovoltaic system by Perturb & Observe and Incremental Conductance methods under normal and partial shading conditions. 2021 Innovations in Energy Management and Renewable Resources (52042),

Eze, V. H. U., Richard, K., Ukagwu, K. J., & Okafor, W. (2024). Factors Influencing the Efficiency of Solar Energy Systems. Journal of Engineering, Technology, and Applied Science (JETAS), 6(3), 119-131. https://doi.org/https://doi.org/10.36079/lamintang.jetas-0603.748

Hajar, A., Ahmed, G., Youness, H., & Benachir, E. H. (2024). Optimizing photovoltaic system efficiency through a Kalman filter driven approach for MPPT in partial shading conditions. 2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET),

Iovino, M., Förster, J., Falco, P., Chung, J. J., Siegwart, R., & Smith, C. (2025). Comparison between behavior trees and finite state machines. IEEE Transactions on Automation Science and Engineering. https://doi.org/https://doi.org/10.1109/TASE.2025.3610090

Lamine, O. M., Bessous, N., Abdelhalim, B., Banakhr, F. A., Mosaad, M. I., Oussama, M., & Mahmoud, M. M. (2024). A Combination of INC and Fuzzy Logic-Based Variable Step Size for Enhancing MPPT of PV Systems. International Journal of Robotics & Control Systems, 4(2). https://doi.org/http://dx.doi.org/10.31763/ijrcs.v4i2.1428

Leyva, R., Alonso, C., Queinnec, I., Cid-Pastor, A., Lagrange, D., & Martinez-Salamero, L. (2006). MPPT of photovoltaic systems using extremum-seeking control. IEEE transactions on aerospace and electronic systems, 42(1), 249-258. https://doi.org/https://doi.org/10.1109/TAES.2006.1603420

Li, C., Chen, Y., Zhou, D., Liu, J., & Zeng, J. (2016). A high-performance adaptive incremental conductance MPPT algorithm for photovoltaic systems. Energies, 9(4), 288. https://doi.org/https://doi.org/10.3390/en9040288

Mohapatra, A., Nayak, B., & Saiprakash, C. (2019). Adaptive perturb & observe MPPT for PV system with experimental validation. 2019 IEEE International Conference on Sustainable Energy Technologies and Systems (ICSETS),

Naima, B., Belkacem, B., Ahmed, T., Benbouhenni, H., Riyadh, B., Samira, H., Sarra, Z., Elbarbary, Z., & Mohammed, S. A. (2025). Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems. Scientific Reports, 15(1), 24559. https://doi.org/https://doi.org/10.1038/s41598-025-10335-0

Renaudineau, H., Donatantonio, F., Fontchastagner, J., Petrone, G., Spagnuolo, G., Martin, J.-P., & Pierfederici, S. (2014). A PSO-based global MPPT technique for distributed PV power generation. IEEE transactions on industrial electronics, 62(2), 1047-1058. https://doi.org/https://doi.org/10.1109/TIE.2014.2336600

Saberi, A., Niroomand, M., & Dehkordi, B. M. (2023). An improved P&O based MPPT for PV systems with reduced steady‐state oscillation. International Journal of Energy Research, 2023(1), 4694583. https://doi.org/https://doi.org/10.1155/2023/4694583

Safari, A., & Mekhilef, S. (2011). Incremental conductance MPPT method for PV systems. 2011 24th Canadian Conference on Electrical and Computer Engineering (CCECE),

Saravanan, S., & Babu, N. R. (2016). Maximum power point tracking algorithms for photovoltaic system–A review. Renewable and Sustainable Energy Reviews, 57, 192-204. https://doi.org/https://doi.org/10.1016/j.rser.2015.12.105

Solís-Cervantes, C. U., Palomino-Resendiz, S. I., Flores-Hernández, D. A., Peñaloza-López, M. A., & Montelongo-Vazquez, C. M. (2024). Design and implementation of extremum-seeking control based on mppt for dual-axis solar tracker. Mathematics, 12(12), 1913. https://doi.org/https://doi.org/10.3390/math12121913

Sonia, P., Aravinda, K., Singla, A., Kumar, Y. J. N., Vishkarma, M. K., Ali, H. A., & Ramu, T. B. (2024). Incorporating Incremental Conductance MPPT Techniques into Solar Power Extraction. E3S Web of Conferences,

Tajiri, H., & Kumano, T. (2012). Input filtering of MPPT control by exponential moving average in photovoltaic system. 2012 IEEE International Conference on Power and Energy (PECon),

Tozlu, Ö. F., & Çalık, H. (2021). A review and classification of most used MPPT algorithms for photovoltaic systems. Hittite Journal of Science and Engineering, 8(3), 207-220. https://doi.org/https://doi.org/10.17350/HJSE19030000231

Wang, H., Li, L., Ye, H., & Zhao, W. (2024). Enhancing MPPT efficiency in PV systems under partial shading: A hybrid POA&PO approach for rapid and accurate energy harvesting. International Journal of Electrical Power & Energy Systems, 162, 110260. https://doi.org/https://doi.org/10.1016/j.ijepes.2024.110260

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Published

2025-12-24

Data Availability Statement

No datasets were generated or analyzed during the current study

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Section

Research Articles

How to Cite

Naji, H. (2025). Hybrid Adaptive MPPT Algorithm with Intelligent Exploration and Dither-Based Tracking for PV Systems. Electrical Engineering and Energy. https://doi.org/10.64470/elene.2025.1017