Implementation Of Neural Network Control Mechanism For Grid Connected Wind-Solar PV Charging Station

Uncategorized

Authors: Manish Kumar, Ishan Sethi2

Abstract: Distributed Generators (DG) embody a multi-source microgrid amalgamated within a unified framework. These DGs are meticulously designed to calibrate voltage, current, and frequency in accordance with the load terminal’s observed power demand. Constructing an optimal control paradigm for these systems amplifies their functional efficacy. This study simulates a DG control architecture within MATLAB/Simulink, integrating photovoltaic (PV) arrays, a proton-exchange membrane fuel cell (PEMFC), and an ultra-capacitor to ensure a steady and dependable output for the grid. The PV component within this configuration utilizes a Maximum Power Point Tracking (MPPT) mechanism, which optimizes power transmission to the grid. To address PV’s inherent variability, an ultra-capacitor and PEMFC are employed, ensuring stable output. Here, the ultra-capacitor counterbalances the PEMFC’s thermodynamic fluctuations, enhancing reliability. A power-electronics-based interfacing circuit, paired with advanced control configurations, upholds power quality by regulating the grid's voltage and frequency within permissible thresholds.

DOI: http://doi.org/10.5281/zenodo.17248263

× How can I help you?