Determination of distance between DC traction power centers in a 1500-V DC subway line with artificial intelligence methods
The electrification system in rail systems is designed
with regard to the operating data and design parameters. While the
electrification system is formed, the minimum voltage rating that the
traction force requires during the operation needs to be provided. The
highest value of the voltage drop occurring on the line is determined by the
distance between power centers. This value needs to be kept within certain
limits for the continuity of operation. In this study, the determination of
the distance between DC traction power centers for a 1500-V DC-fed rail
system is done by means of the adaptive neuro-fuzzy inference system
(ANFIS), support vector machines (SVMs), and artificial neural networks
(ANNs). The distance occurring on the line is calculated with regard to the
operating parameters by means of the ANFIS, SVMs, and ANNs. The ANFIS, SVMs,
and ANNs are explained and a comparison is made. The data created regarding
one-way and two-way supply conditions are examined for simulation. The main
contribution of this paper is the determination of the distance between
railway traction power centers with artificial intelligence methods.
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