DocumentCode :
2046643
Title :
Detection of voltage sag by artificial neural network and mitigation using DSTATCOM
Author :
Singh, Monika ; Chacko, S.T. ; Zadgaonkar, A.S.
fYear :
2012
fDate :
17-19 Dec. 2012
Firstpage :
1
Lastpage :
5
Abstract :
An important task in power system operation is to decide whether the system, at a given point of time, operates safely, critically and optimally while the system operates safely. So uninterrupted supply of high quality power to customers in a secure and economic environment is the goal of power system engineers. In this paper the voltage sag is detected by artificial neural network then trained data and neural network output simulated in neural network block set, then it will be mitigated using DSTATCOM with neural network control block. Here different aspects or power line status were considered and simulated using artificial neural network to get the response under changed operating conditions.
Keywords :
learning (artificial intelligence); neurocontrollers; power cables; power distribution control; power supply quality; static VAr compensators; DSTATCOM; artificial neural network; economic environment; high quality power supply; neural network block set; neural network control block; neural network output; power line status; power system operation safety; voltage sag detection; Artificial neural networks; DSTATCOM; Voltage Sag;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power, Control and Embedded Systems (ICPCES), 2012 2nd International Conference on
Conference_Location :
Allahabad
Print_ISBN :
978-1-4673-1047-5
Type :
conf
DOI :
10.1109/ICPCES.2012.6508032
Filename :
6508032
Link To Document :
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