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AI-advanced MPPT for optimized hybrid solar-wind energy harvesting in off-grid rural electrification: Fabrication and performance modeling

Val Hyginus Udoka Eze · 2025 · KIU journal of science engineering and technology

Summary. Hybrid solar-wind systems can reliably power remote rural areas, but their intermittent nature reduces efficiency. This review examines AI-driven maximum power point tracking techniques—artificial neural networks, fuzzy logic control, and reinforcement learning—that optimize energy extraction in real time. Each approach has trade-offs in accuracy, computational demands, and training requirements. Practical implementation requires careful hardware selection and controller design. Simulation and testing confirm these AI methods significantly improve power extraction and system reliability for off-grid rural electrification.

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Eze, V. H. U.. (2025). AI-advanced MPPT for optimized hybrid solar-wind energy harvesting in off-grid rural electrification: Fabrication and performance modeling. KIU journal of science engineering and technology. https://doi.org/10.59568/kjset-2025-4-1-25

Details

DOI
10.59568/kjset-2025-4-1-25
Categories
energy, agtech
Added
2026-04-28