Open AccessClassification Of Faults During Integration Of Hybrid System To Microgrid Using Neuro-Fuzzy Technique
Author(s) -
Ritu Singh
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i5.1776
Subject(s) - microgrid , computer science , diesel generator , matlab , fault (geology) , fuzzy logic , artificial neural network , generator (circuit theory) , neuro fuzzy , steam turbine , turbine , control engineering , artificial intelligence , data mining , fuzzy control system , automotive engineering , diesel fuel , engineering , control (management) , power (physics) , physics , quantum mechanics , geology , operating system , mechanical engineering , seismology
To improve microgrid efficiency, detecting the fault as soon as possible is imperative. Taking into account the above problem a peculiar technique has been implemented in the analysis of this paper with a micro grid consisting of wind turbine (WT) and diesel generator for the classification of different types of faults. All Neuro-fuzzy (NF) fault disturbances are introduced by taking the input function data for accurate classification of different faults. One technically applicable 3-bus framework integrated with various forms of delivery generations that are considered for the purpose of security analysis and the simulation is done for the environment using MATLAB / SIMULINK. The fault classification is achieved by using Neuro Fuzzy. The results of the comparison are presented, showing the improved performance of Neuro Fuzzy (NF).