Open AccessOptimal placement of rectifier substations on DC traction systems
Author(s) -
Pereira Fabio Henrique,
Pires Cassiano Lobo,
Nabeta Silvio Ikuyo
Publication year - 2014
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
eISSN - 2042-9746
pISSN - 2042-9738
DOI - 10.1049/iet-est.2010.0063
Subject(s) - traction (geology) , rectifier (neural networks) , automotive engineering , traction substation , engineering , electrical engineering , materials science , control theory (sociology) , computer science , mechanical engineering , voltage , transformer , artificial intelligence , control (management) , stochastic neural network , recurrent neural network , artificial neural network
Rectifier substation placement on DC traction systems has been the purpose of several works which have tried to establish mathematical models to optimise that placement. Those mathematical models were always performed to optimise one variable like distance between substations, consumed energy or peak demand. This study presents the rectifier substation placement through optimisation techniques, specifically genetic algorithm. This proposed technique differs from the early presented ones because the genetic algorithm is applied on substation placement for DC traction systems, considering the variations of train position and train power consumption during their operations, in order to keep all traction substations evenly loaded. In this study, the chosen parameters for optimal rectifier placement are peak demand and consumed energy, which is illustrated with the application of the proposed method.