Electric energy is essential in modern life, with solar power emerging as a leading renewable energy source. Photovoltaic (PV) systems convert sunlight into electricity, but their output is highly sensitive to environmental changes such as solar irradiance. A reliable Maximum Power Point Tracking (MPPT) method is needed to maximize efficiency, This study investigates the performance of a Buck-Boost DC-DC converter integrated with the Incremental Conductance (InCo) algorithm for MPPT in PV systems. A comparative analysis is conducted between systems with and without MPPT under variable irradiance conditions, replicating real-world scenarios like partially cloudy weather. Simulations were performed in MATLAB Simulink using a PV module model based on actual datasheet parameters. A digital lux meter was used to simulate light intensity fluctuations. Results show that the MPPT-enabled system effectively tracks the Maximum Power Point (MPP) even during rapid irradiance changes. On average, the system achieved improvements of 65.53% in output voltage, 65.48% in current, and 86.47% in power compared to the non-MPPT configuration. These findings demonstrate that combining the InCo algorithm with a Buck-Boost converter offers an efficient and adaptive solution for improving energy conversion in PV systems in environments with unstable solar exposure.
No takes yet. Share an insight, caveat, or question.
Rimbawati et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: