MATLAB Code Implementation for Photovoltaic Inverter Simulation

Photovoltaic inverter simulation serves as a critical method for studying grid-connected performance of PV systems. Using MATLAB enables efficient implementation of closed-loop simulations covering voltage/current control and harmonic analysis. The core challenge involves establishing a comprehensive model integrating Maximum Power Point Tracking (MPPT), inverter modulation, and grid synchronization.

Core Simulation Module Breakdown Photovoltaic Array Modeling Requires simulation of I-V/P-V characteristic curves under varying irradiance conditions, typically implemented using single/double-diode equivalent circuit models through MATLAB's Simscape Electrical or custom script-based modeling.

MPPT Control Layer Implements perturbation and observation or incremental conductance algorithms for dynamic maximum power point tracking, requiring oscillation handling during sudden irradiance changes through conditional logic and filtering in the code.

Inverter Modulation Strategy Dual-loop voltage-current control: Inner current loop ensures fast response using PI controllers, outer voltage loop maintains DC bus stability through proportional-integral regulation SPWM/SVPWM modulation techniques affect harmonic distribution, requiring coordination with filter design via Fourier analysis functions and filter parameter optimization

Grid Synchronization and Harmonic Suppression Achieves grid phase synchronization through Phase-Locked Loop (PLL) algorithms, employs Proportional-Resonant (PR) controllers or repetitive control to suppress specific harmonics (e.g., 3rd/5th/7th) using frequency-domain compensation techniques

Key Simulation Validation Metrics THD (Total Harmonic Distortion) must meet grid standards (typically <5%) calculated using FFT analysis functions Dynamic response testing requires simulation of grid voltage sag/frequency fluctuation scenarios through event-based scripting Efficiency analysis must account for switching losses and filter losses using loss calculation subroutines

Extended Application Directions Can integrate with Simulink for real-time simulation using Rapid Prototyping tools, or embed fault diagnosis algorithms (e.g., islanding detection) through state machine implementation. Parameter sensitivity analysis (e.g., filter inductance values) can further optimize system robustness via parameter sweeping functions.