Quasi-Z-Source Solar Inverter Fed BLDC Drive using ANFIS MPPT Control

Abstract: The major players in renewable energy generation are photovoltaics (PV), wind farms, fuel cell, and biomass. These distributed power generation sources are widely accepted for microgrid applications. However, the reliability of the microgrid relies upon the interfacing power converter. This paper proposes an artificial-intelligence-based solution to interface and deliver maximum power from a photovoltaic (PV) power generating system in standalone operation. BLDC motor is connected at the output side which acts as a load and efficiently utilizes the power obtained from solar using ANFIS. The qZSI acts as the interface in between the PV dc source and the BLDC motor. ANFIS promises the maximum power delivery to the load based on maximum power point tracking (MPPT). The proposed ANFIS-based MPPT offers high efficiency and accuracy. The closed loop control regulates the speed of the BLDC motor for different load conditions and also maintains regulated voltage and current. The effectiveness of this proposed method is verified using matlab/simulink software.

Keywords: quasi-Z-source inverter (qZSI), Adaptive neuro fuzzy inference system (ANFIS), Solar power generation.