Performance analysis of buck-boost DC-DC converter with incremental conductance MPPT for PV system

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.