Open AccessOpen switch fault detection technique of a back-to-back converter using NPC topology for turbine systems
Author(s) -
S. Mahaboob Basha,
Mounika Kannan
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.12.11351
Subject(s) - turbine , rectifier (neural networks) , topology (electrical circuits) , converters , fault detection and isolation , inverter , fault (geology) , wind power , computer science , electrical engineering , engineering , electronic engineering , control theory (sociology) , voltage , actuator , mechanical engineering , stochastic neural network , machine learning , seismology , recurrent neural network , artificial neural network , geology , control (management) , artificial intelligence
Efficiency is turning into more and more necessary in power electronics. New applications are developed to reduce the consumption of en-ergy. Inverters that supply continuous quality power have vast use in solar energy based applications. For a Wind Turbine Generation sys-tem with neutral-point-clamped (NPC) topology in a back to back converter , good efficiency is provided when operated at high power. In NPC topology totally twelve switches are present. Input current distortion, torsion vibration and output current distortion is caused by open switch fault within NPC inverter and rectifier of the consecutive converter. Wind Turbine Generation systems will be erroneous due to such faults. Open-switch fault detection methodology is necessary for consecutive converters for enhancing the output of Wind Turbine Genera-tion systems. Our proposed work checks NPC rectifier and inverter for outer and inner open switch faults. Additionally for all the possible open-switch faults , a novel open-switch fault detection methodology within the back to back converter has been presented in this paper.