期刊名称：Eastern-European Journal of Enterprise Technologies
印刷版ISSN：1729-3774
电子版ISSN：1729-4061
出版年度：2018
卷号：5
期号：2
页码：47-56
DOI：10.15587/1729-4061.2018.142936
语种：English
出版社：PC Technology Center
摘要：The result of applying the quantitative approach to the calculation of static stability of the traction power system helped us establish that when a train runs along an actual section there emerge zones with lack of stability in terms of voltage. Exact solution to the task of evaluating the stability is extremely difficult because of the need to compute the nonlinear dependences determining the modes of operation of the traction power system and electric rolling stock.In this work, we constructed a system of four autonomous nonlinear differential equations based on experimental data that simulate the behavior of current and voltage in the contact network. We also calculated stability regions for voltage regulators in the traction network, which stabilize voltage at pantographs of electric rolling stock.The obtained stability regions of voltage regulators made it possible to estimate resource of stability and to find the most robust regulators out of those constructed. The study revealed that the non-linear regulator has better robust properties than the linear one. In this case, stability of the linear regulator is very narrow ‒ Δk=0.000004, which is an order of magnitude lower than for the non-linear regulator. When applying the non-linear regulator, voltage in the contact network stabilizes 3 times faster regardless of the place of its location.Application of the devised approach would make it possible to calculate the stability regions for various schematics of the traction network in the implementation of high-speed motion and to narrow the range of voltage fluctuations. The developed dynamic model of power consumption processes, as well as the voltage regulator, could be used when constructing an intelligent, adaptive traction power system for high-speed motion.
关键词：traction power system;voltage regulator;stability region;nonlinear recurrent analysis
