Open AccessA Novel Study on Bipolar High Voltage Direct Current Transmission Lines Protection Schemes
Author(s) -
Suneeta Agarwal,
Chinmoy Kumar Panigrahi,
Abinash Sahoo,
Sanitha Mishra
Publication year - 2018
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v8i4.pp1977-1984
Subject(s) - span (engineering) , rectifier (neural networks) , fault (geology) , converters , electric power transmission , computer science , line (geometry) , transmission (telecommunications) , voltage , power (physics) , transmission system , transmission line , electrical engineering , electronic engineering , telecommunications , artificial neural network , engineering , physics , recurrent neural network , artificial intelligence , mathematics , biology , structural engineering , paleontology , stochastic neural network , geometry , quantum mechanics
In long dc transmission lines identification of fault is important for transferring a large amount of power. In bipolar Line commutated converter transmission lines are subjected to harsh weather condition so accurate and rapid clearance of fault is essential. A comparative study of the bipolar system with both converters healthy and one converter tripped is studied. Most of the research paper has focussed on transmission line faults in bipolar mode but none of them had focussed when HVDC system works in monopolar mode after the fault. In the proposed scheme the voltage signals are extracted from both poles of the rectifier ends and are processed to identify the faults in transmission lines.The Artificial neural network is utilised in detecting the fault in both bipolar and monopolar system. Since it can identify the relationship between input and output data to detect the fault pattern it can be utilised under all conditions. Moreover, benefits of the proposed method are its accuracy, no requirement of the communication system as it acquires data from one end and has a reach setting of 99%.