Open AccessPower enhancement in a grid connected solar PV System by using PLL-neural based converter
Author(s) -
Avinash Kumar,
Vivek Kumar Kostha,
Satyam Kumar Prasun
Publication year - 2019
Publication title -
smart moves journal ijoscience
Language(s) - English
Resource type - Journals
ISSN - 2582-4600
DOI - 10.24113/ijoscience.v5i11.235
Subject(s) - controller (irrigation) , control theory (sociology) , artificial neural network , photovoltaic system , ac power , computer science , matlab , grid , renewable energy , electric power system , maximum power principle , power (physics) , three phase , voltage , engineering , electrical engineering , control (management) , mathematics , artificial intelligence , physics , geometry , quantum mechanics , agronomy , biology , operating system
This work deals with neural network control algorithm-based grid connected to solar photo voltaic (PV) system consisting of DC-AC converter. The reference solar-grid current for three-leg VSC are estimated using neural network control algorithm. The neural network control algorithm based solar PV system is modeled in MATLAB R2018a along with SIMULINK.. This study presents an artificial neural network-based controller for regulating the level of active and reactive power output. First, the three phase currents from the VSI are measured and compared with the three reference currents. The neural network is trained to have minimum output error. It was concluded that the power output from the system was found to be190 KVA in case of system having no intelligent controller and 700 KVA in case of system with AAN based control. The voltage of output is maintained to be 20 kV in the grid system for analysis purpose. Thus the proposed control is expected to be implemented in the renewable energy resources for better output.