ArticleScientific reports2025
A reduced sensor-based efficient and robust MPPT nonlinear controller for grid-integrated photovoltaic energy systems operating under rapidly changing climatic conditions.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Current sensorless MPPT method with battery management for PV based single phase standalone system.Scientific reports · 2026Article
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Abstract
This paper proposes a reduced sensor-based nonlinear maximum power point tracking (MPPT) controller for grid-integrated photovoltaic (PV) systems operating under rapidly changing climatic conditions. Unlike conventional approaches that require costly irradiance sensors, the proposed method employs a mathematical irradiance estimation model and a radial basis function neural network to generate optimal reference voltages, which are then enforced by a backstepping nonlinear controller. This two-stage design enables fast and robust MPPT while maintaining DC-link stability and grid power quality. The controller was validated on a 100 kW MATLAB/Simulink-based grid-tied PV system with a DC-DC boost converter and inverter. Under step changes in irradiance, the system tracked the new MPP in as little as 7 ms, while restoring DC-link stability (500 V) within 42 ms. Under continuously varying conditions, it maintained synchronization with the grid and achieved a total harmonic distortion (THD) below 0.1%. Comparative results against Perturb & Observe (P&O), Improved Differential Evolution (IDE), and Particle Swarm Optimization (PSO) demonstrated that the proposed method achieved the highest PV-side power yield (80.41 kW vs. 79.71 kW for P&O, 73.44 kW for IDE, and 59.34 kW for PSO), the highest grid-side active power delivery (78.69 kW vs. 77.98 kW, 72.14 kW, and 58.29 kW respectively), and the lowest integral absolute error of DC-link voltage (IAE = 10.6156). These results confirm that the controller provides faster convergence, improved voltage regulation, and superior grid stability compared to state-of-the-art MPPT methods, making it a promising solution for real-world deployment in large-scale PV systems.
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