Classification Of Faults During Integration Of Hybrid System To Microgrid Using Neuro-Fuzzy Technique
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Abstract
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).
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