NEURO-FUZZY CONTROL SYSTEM FOR GRID-CONNECTED PHOTOVOLTAIC SYSTEMS

摘要

The neuro-fuzzy control system for a grid-connected photovoltaic (PV) system includes an Adaptive Neuro-Fuzzy Inference System (ANFIS) implemented in real time. Independent active and reactive P-Q power control transfers the generated power to the grid using a voltage source inverter (VSI). The PV system includes a PV module, a buck converter, a VSI, a maximum power point tracking (MPPT) controller for the buck converter, and a VSI controller. The MPPT controller uses irradiation and temperature as inputs. A five-layer ANFIS processes these inputs and provides a control reference voltage as input to a PI controller connected to the buck converter to maintain the output voltage of the photovoltaic array with respect to the control reference voltage.

主权项

1. A neuro-fuzzy control system for a grid-connected photovoltaic (PV) system, comprising:
a solar power array outputting a panel voltage VPV; a DC-DC converter operably connected to the solar power array; a proportional-integral (PI) controller operably connected to the DC-DC converter, the PI controller controlling a duty cycle of the DC-DC converter; a processor in operable communication with the solar power array, the processor including means for receiving temperature and irradiance information from the solar power array and means for operating an adaptive neuro-fuzzy network, the adaptive neuro-fuzzy network outputting a reference voltage Vref; and means for applying a reference input to the PI controller, the reference input being characterized by the relation (Vref−VPV); wherein the maximum power point (MPPT) of the PV array is successfully allocated under varying temperature and irradiance values of the PV array.