High-efficiency hybrid MPPT technique with integrated partial shading detection for photovoltaic systems under varying shading conditions


Koshkarbay N. Mohammed K.K. Mekhilef S. Kuttybay N. Saymbetov A. Nurgaliyev M. Kalassov N.
1 April 2026Elsevier Ltd

Renewable Energy
2026#261

This paper proposes a hybrid maximum power point tracking algorithm for photovoltaic systems, combining the dichotomy method with the Weighted Superposition Attraction algorithm. Weighted Superposition Attraction uses the superposition principle and an attraction-repulsion mechanism to perform global optimization under complex conditions. Under uniform shading conditions, where a single global maximum power point exists, the dichotomy algorithm efficiently converges to the optimum via a stepwise search. A delta-coefficient-based shading-detection method is introduced that requires no PV panel parameters. If the delta threshold exceeds 2, the system is classified as a uniform shading condition, and the dichotomy method is applied; otherwise, partial shading conditions are detected, and Weighted Superposition Attraction is used. Experiments with a boost converter show high dynamic performance and stability, achieving average tracking efficiencies of 99.63 % for dichotomy and 99.76 % for Weighted Superposition Attraction with convergence times of 0.51 s and 0.53 s, respectively. The hybrid algorithm reliably locates the global maximum power point under rapid irradiance changes and closely spaced local maximums.

Boost converter , Hybrid algorithm , Maximum power point tracking (MPPT) , Partial shading condition

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Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi, Almaty, 050040, Kazakhstan
Power Electronics and Renewable Energy Research Laboratory, Department of Electrical Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia
School of Engineering, Swinburne University of Technology, Hawthorn, VIC, 3122, Australia

Faculty of Physics and Technology
Power Electronics and Renewable Energy Research Laboratory
School of Engineering

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