MATLAB Code Implementation for Photovoltaic Inverter Simulation

Photovoltaic inverter simulation is a crucial method for studying grid-connected performance of PV power generation systems. Using MATLAB enables efficient modeling of inverter operation processes, analyzing output voltage/current waveforms and harmonic content. Below are the core concepts and key implementation steps for this simulation: System Modeling A typical PV inverter system includes photovoltaic array models, DC-DC boost converters, inverters (such as single-phase or three-phase full-bridge), LC filter circuits, and grid models. In MATLAB implementation, these components can be built using Simulink's Power Electronics toolbox blocks. Key parameter configuration involves setting appropriate switching frequencies (e.g., 10-20 kHz for IGBTs), filter component values (L/C calculated based on cutoff frequency), and PV array characteristics using the Solar Cell block with I-V curve parameters. Control Strategy Implementation The inverter's core lies in its control system, typically employing dual-loop control (outer voltage loop + inner current loop). Implementation involves designing PI controllers with anti-windup features or advanced algorithms like PR (Proportional Resonant) controllers for harmonic suppression. The control logic generates PWM signals through comparison with carrier waves (triangle/sawtooth waves). Phase-Locked Loop (PLL) algorithms, implemented using dq-transform or enhanced PLL blocks, synchronize with grid phase for seamless connection. Harmonic Analysis and Optimization FFT analysis tools (such as Powergui's FFT Analysis) perform spectral analysis on inverter output waveforms to monitor THD (Total Harmonic Distortion) against grid standards (typically <5%). For harmonic reduction, implementation may include optimized modulation strategies like SVPWM (Space Vector PWM) using MATLAB's SVM generator block, increasing filter orders, or adding harmonic compensation algorithms through repetitive controllers. Simulation Verification and Debugging Dynamic response testing involves varying irradiation levels (using controlled current sources) and load conditions to observe voltage/current tracking performance. Debugging focuses on key indicators like DC bus voltage stability (maintained through proper capacitor sizing) and grid current distortion rates. Implementation includes using Scopes and Data Logging for waveform capture and measurements. Extension Considerations: Integration with MPPT algorithms (Perturb and Observe or Incremental Conductance methods) enables efficient energy extraction from PV arrays. For microgrid applications, additional implementation of islanding detection mechanisms (using frequency/phase drift methods) and protection logic is required. Through MATLAB simulation, not only can theoretical designs be validated, but it also provides parameter optimization references for actual inverter hardware development, including component selection and controller tuning through systematic parameter sweeps.