On-line simulation of voltage regulation in autotransformer-fed AC electric railroad traction networks

Abstract-Transports on rail are increasing and major railway infrastructure investments are expected. An important part of this infrastructure is the railway power supply system. The future railway power demands are not known. The more distant the uncertain future, the greater the number of scenarios that have to be considered. Large numbers of scenarios make time demanding (some minutes, each) full simulations of electric railway power systems less attractive and simplifications more so.The aim, and main contribution, of this paper is to propose a fast approximator, that uses aggregated traction system information as inputs and outputs. This approximator can be used as an investment planning constraint in the optimization. It considers that there is a limit on the intensity of the train traffic, depending on the strength of the power system. This approximator approach is not encountered before in the literature.In the numerical example of this paper, the approximator inputs are the power system configuration; the distance between a connection from contact line to the public grid, to another connection, or to the end of the contact line; the average values and the standard deviations of the inclinations of the railway; the average number of trains; and the average velocity of them, for that distance. The output is the maximal attainable average velocity of an added train for the by the inputs described railway power system section.The approximator facilitates studies of many future railway power system loading scenarios, combined with different power system configurations, for investment planning analysis. The approximator is based on neural networks.An additional value of the approximator is that it provides an understanding of the relations between power system configuration and train traffic performance.

show abstract

“…All contact line voltages in [23] has to lie within a certain range. Other 50 Hz simulators are presented in [38], [39].…”

Section: ) Commercialmentioning

confidence: 99%

Fast Estimation of Relations Between Aggregated Train Power System Data and Traffic Performance

Abrahamsson

Söder

2011

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…A number of power flow algorithms have been proposed for TPSSs in the past decades, as listed in Table 1. Though the algorithms of [3,[14][15][16][17][18][19][20][21][22] are applicable, the Multiple conductor Nodal Fixed-point Algorithm (MNFA), involving the multiple conductor model, a nodal analysis, and fixed-point iteration [23][24][25][26][27][28][29][30], has acquired the widest use because of its accuracy and convenience for programming. However, the MNFA cannot offer convincing evidence of the power limit for PSC assessment.…”

Section: Introductionmentioning

confidence: 99%

A Novel Power Flow Algorithm for Traction Power Supply Systems Based on the Thévenin Equivalent

2018

View full text Add to dashboard Cite

Abstract:With the rapid development of high-speed and heavy-haul railways throughout China, modern large power locomotives and electric multiple units (EMUs) have been applied in main railway lines. The high power requirements have brought about the problem of insufficient power supply capacity (PSC) of traction power supply systems (TPSSs). Thus, a convenient method of PSC assessment is meaningful and urgently needed. In this paper, a novel algorithm is proposed based on the Thévenin equivalent in order to calculate the PSC. In this algorithm, node voltage equations are converted into port characteristic equations, and the Newton-Raphson method is exploited to solve them. Based on this algorithm, the PSC of a typical high-speed railway is calculated through the repeated power flow (RPF). Subsequently, the effects of an optimized organization of train operations are analyzed. Compared to conventional algorithms, the proposed one has the advantages of fast convergence and an easy approach to multiple solutions and PV curves, which show vivid and visual information to TPSS designers and operators. A numerical analysis and case studies validate the effectiveness and feasibility of the proposed method, which can help to optimize the organization of train operations and design lines and enhance the reliability and safety of TPSSs.

show abstract

“…Many models are developed to simulate train movement. Some models have been produced to analyse power quality, however these models tend to focus on single aspects of power quality, such as harmonic analysis [3] and voltage regulation [4]. It would be desirable and more effective to simulate these aspects of power quality together.…”

Section: Modelling Railway Power Qualitymentioning

confidence: 99%

Railway modelling for power quality analysis

Chymera¹,

Renfrew²,

Barnes³

2006

WIT Transactions on the Built Environment, Vol 88

View full text Add to dashboard Cite

Power quality is increasingly important in the consideration of railway systems. Poor power quality affects the performance of trains and introduces problems for local distribution networks.This paper looks at improving modelling techniques to assess the power quality of a railway system. Modelling techniques used to simulate electrified railways are adapted to simulate power quality aspects with improved computational efficiency. The model developed is used to assess the voltage regulation and harmonic distortion of a rail system, and harmonic distortion on the local distribution network.

show abstract

On-line simulation of voltage regulation in autotransformer-fed AC electric railroad traction networks

Cited by 31 publications

References 3 publications

Fast Estimation of Relations Between Aggregated Train Power System Data and Traffic Performance

Fast Estimation of Relations Between Aggregated Train Power System Data and Traffic Performance

A Novel Power Flow Algorithm for Traction Power Supply Systems Based on the Thévenin Equivalent

Railway modelling for power quality analysis

Contact Info

Product

Resources

About