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Nilesh Sanjay Wagh,
Rahul. R. Bibave,
- Student, Department of Electrical Engineering, Sanjivani College of Engineering Kopargaon, Maharashtra, India
- Assistant Professor, Department of Electrical Engineering, Sanjivani College of Engineering Kopargaon, Maharashtra, India
Abstract
Photovoltaic (PV) systems are becoming a major source of clean, renewable, electrical energy; however, the power generation from PV systems is continuously changing as the solar irradiance and temperature change. Thus, to harness the utmost output from PV systems operating under changing conditions a suitable Maximum Power Point Tracking (MPPT) technique must be used. The classical methods (Perturb and Observe (P&O), fixed-step Incremental Conductance (INC)) are known to give good MPPT operation, but often with a compromise between tracking speed and steady-state power oscillation. An Adaptive Step-Size Incremental Conductance (AS-INC) MPPT technique is recommended in this study for the purpose of enhancing convergence speed, tracking accuracy and steady state performance. The proposed method is a dynamic perturbation step changing according to the operating condition of the PV system, such that larger perturbation step size is applied at large deviation from the maximum power point (MPP) and smaller perturbation step size is applied at small deviation from the MPP. The proposed AS- INC controller is integrated with a PV system, which is developed and tested in MATLAB/Simulink under different operating conditions. The performance is evaluated and compared to the conventional fixed-step INC approach with respect to convergence time, power oscillation and overall MPPT tracking efficiency. Based on the results of the simulation, the proposed AS-INC method can achieve the MPP in about 0.12 s, whereas the fixed-step INC method requires 0.45 s. The steady-state power oscillation decreased from around ±4.8 W to ±0.8 W and the reported tracking efficiency increased from 94.7% to 98.9%. The results showed the superiority of adaptive step-size control in terms of faster and more stable MPPT operation of PV systems under dynamic environmental conditions.
Keywords: Electric Vehicles (EVs), Internet of Things (IoT), Solar Power, Smart Parking, Energy Prediction, Green Mobility.
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Journal of Alternate Energy Sources & Technologies
| Volume | 17 | |
| 03 | ||
| Received | 30/07/2026 | |
| Accepted | 11/10/2026 | |
| Published | 30/10/2026 | |
| Publication Time | 92 Days |