A Universal Engineering Model for Photovoltaic Cells with Maximum Power Point Tracking Implementation

This paper aims to develop a universal engineering model for photovoltaic cells to enhance understanding of their operational principles. We propose and validate through simulation an algorithm that achieves maximum power point tracking (MPPT) for photovoltaic cells by controlling the duty cycle of a Boost converter circuit. Prior to algorithm implementation, we established a comprehensive PV model within the MATLAB/Simulink simulation environment, designed to emulate the performance characteristics of various photovoltaic cell types and specifications under different operating conditions. The model incorporates key parameters including short-circuit current (Isc), open-circuit voltage (Voc), and temperature coefficients to ensure accurate representation of real-world PV behavior.

Subsequently, we implemented maximum power point tracking control (MPPT) using the perturb and observe (P&O) method. This control algorithm continuously monitors the photovoltaic system's output power and adjusts the Boost converter's duty cycle through incremental changes, systematically seeking the operating point that yields maximum power output. The implementation involves real-time power calculation (P = V × I) and comparison with previous values to determine the optimal direction for duty cycle adjustment. This approach ensures the photovoltaic system operates at peak efficiency across varying environmental conditions, including changing irradiance levels and temperature fluctuations, thereby significantly improving overall system performance and energy harvest efficiency.

The simulation results demonstrate the model's effectiveness in tracking the maximum power point with minimal oscillation around the optimal operating point, showcasing rapid convergence and stable performance under dynamic conditions. The MATLAB/Simulink implementation includes customizable blocks for PV array configuration, Boost converter design, and MPPT controller parameters, allowing engineers to adapt the model for specific application requirements.