PV Panels Maximum Power Point Tracking based on ANN in Three-Phase Packed E-Cell Inverter

摘要

This manuscript introduces a novel Maximum Power Point Tracking (MPPT) technique based on Artificial Neural Network (ANN) to inject harvested electrical power from PV panels to a three-phase stand-alone load using nine-level Packed E-Cell (PEC9) inverter. Instead of using three MPPT algorithms and three duty cycle controllers, the proposed ANN-MPPT technique proposes a single controller to extract the Maximum Power (MP) of three PV panels connected to the three-phase stand-alone PEC9 inverter. PEC9 is a promising multilevel inverters topology which uses least semiconductor switches, capacitors and a single DC source to generate a nine-level quasi-sinusoidal voltage waveform. The proposed three-phase PEC9 inverter control loop has been simulated by MATLAB software where the results show proper power quality, low Common Mode Voltage (CMV) and balanced capacitors voltage with minimum ripple.