High Gain SEPIC-Zeta Converter for Energy Management of Wind-PMSG Based Water Pumping System

Recent studies have shown that researchers are very fascinated with variable speed Permanent Magnet Synchronous Generator (PMSG) based Wind Energy Conversion Systems (WECS). This study addresses a number of PMSG related topics, including topologies using adaptive network based fuzzy inference system maximum power point tracking (ANFIS MPPT) controlled methods. According to the simulation findings, both an artificial neural network (ANN) and ANFIS approaches work well for determining wind rapidity and for monitoring the supreme power point and related rotor speed. The suggested single ended primary inductance converter (SEPIC) zeta converter with ANN controller enhances an energy from battery to be applied to the motor at times of power shortage from WECS. The simulation and experimental findings demonstrate the steady state performance under a range of wind speeds and prove an efficiency of the developed controllers utilizing the parameters that were measured.