Abstract:

This paper presents a boost type Vienna Rectifier with an Elman back propagation neural network algorithm for maximum power point tracking (MPPT) from the wind energy system. The preferred control algorithm deals with non-linear problems with improved conversance precision and reduced learning time. In this system, boost type Vienna Rectifier is employed as a machine side converter for single stage energy conversion of AC to DC with the enhanced output voltage and a grid side converter worked for DC to AC conversion. Vienna Rectifier facilitates power flow with high power density, continuous sinusoidal input current, improved power factor and offers low voltage stress across the switches. The proposed system configuration is designed to meet the load power demand of 1kW Active power with the combined contribution of the Wind energy conversion system and the main grid. The resulting analysis of the Vienna Rectifier with the aforementioned control algorithm is validated through Matlab-Simulink for variable wind speeds.<

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