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Scientific Reports , Article number: (2026)
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In photovoltaic systems, PSC occur when PV panels are exposed to nonuniform solar irradiance levels. Extracting the maximum power from PV systems operating under PSC represents a complex and challenging task for MPPT algorithms. Optimization-based MPPT techniques have therefore gained significant attention due to their ability to achieve fast convergence and high efficiency under such conditions. In this study, a novel M-DHO algorithm is proposed by integrating the DHO algorithm, which is inspired by the cooperative hunting behavior of the Asiatic wild dog, with a Levy flight strategy to enhance global search capability. Especially with Levy flight support, the M-DHO algorithm eliminates the problems of fast convergence and getting stuck in a local minimum. Furthermore, while the fast convergence problem is eliminated, the Levy Flight algorithm allows reaching the global maximum value faster with high accuracy in complex optimization problems. Nine distinct PSC scenarios are created across six different voltage regions, and the performance of the proposed M-DHO algorithm is comparatively assessed against GWO, WOA, FPA, and the conventional DHO algorithm. Simulation results demonstrate that the proposed M-DHO algorithm achieves faster convergence to the global maximum power point and higher tracking efficiency compared to the benchmark algorithms. When averaged over all scenarios, M-DHO achieved an average extracted power of 838.58W, tracking speed of 0.15s and an average tracking efficiency of 99.52%, outperforming other algorithms.
Cuckoo Search Algorithm
Dhole-Inspired Optimization
Flower Pollination Algorithm
Global Maximum Power Point
Grey Wolf Optimization
Incremental Conductance
Local Maximum Power Point
Modified Dhole-Inspired Optimization
Maximum Power Point Tracking
Partial Shading Condition
Particle Swarm Optimization
Photovoltaic
Whale Optimization Algorithm
Faculty of Technology, Department of Electrical and Electronics Engineering, Firat University, Elazig, 23200, Turkey
Resat Celikel & Omur Aydogmus
Bourns College of Engineering, Center for Environmental Research and Technology, University of California at Riverside, Riverside, CA, 92521, USA
Musa Yilmaz
Department of Electrical and Electronics Engineering, Batman University, Batman, 72100, Turkey
Musa Yilmaz
PubMed Google Scholar
PubMed Google Scholar
PubMed Google Scholar
Correspondence to Musa Yilmaz.
The authors declare no competing interests.
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See Fig. 6.
Module irradiance patterns for the nine partial shading scenarios.
See Fig. 7.
PV system voltages under partial shading scenarios.
See Fig. 8.
Power waveforms under partial shading scenarios PSC1–PSC9.
See Fig. 9.
Duty cycles under partial shading scenarios PSC1–PSC9.
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Celikel, R., Aydogmus, O. & Yilmaz, M. Modified Dhole-inspired optimization for maximum power extraction in photovoltaic systems under partial shading. Sci Rep (2026). https://doi.org/10.1038/s41598-026-47686-1
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DOI: https://doi.org/10.1038/s41598-026-47686-1
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