Verification of a train traction power simulator for DC feeding system by a commercial operation measurement

Ogawa, Tomoko; Takeuchi, Yoko; Morimoto, Hiroaki; Yoshii, Tsurugi; Imamura, Yoichi; Kageyama, Masahisa

doi:10.1109/esars-itec.2016.7841373

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…Railway simulators that calculate the energy consumption of trains and substations have been developed and written about in various documents (2)- (7) . However, there are few reports in which accuracy was verified (3)- (5) . We developed our simulator because we need a highly accurate railway simulator as indicated above.…”

Section: Overview Of Railway Total Simulatormentioning

confidence: 99%

Evaluating the Accuracy of Railway Total Simulator Compared with Actual Measurement Data

et al. 2018

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We developed a railway total simulator that can simulate not only each sub system such as a train, signalling system, and power supply system but also train operation and energy usage based on the collaboration of subsystems for all railroads. The purpose of this simulator is to determine the influence of the energy consumption of trains and substations depending on the change in train characteristics, timetables, power supply systems and so on. The targets of calculation for this simulator are the energy consumption of substations and trains restricted by the condition of signalling systems and traffic control systems. We evaluate the simulation accuracy of the proposed simulator for a DC feeding system by using measurements obtained from the Okinawa Urban Monorail. It is confirmed that the simulation results can help predict power behaviour with a sufficient accuracy on railway lines and the average simulation differences were within 6%, namely a 3.6% difference in rolling stock power consumption, 3.9% difference in rolling stock regenerative power, and 3.0% difference in substation power supply. On comparing the calculation results of the proposed simulator with actual measurement data from a general DC power railway system, it is concluded that the simulator and actual results have a sufficiently low difference.

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Section: Overview Of Railway Total Simulatormentioning

confidence: 99%

Evaluating the Accuracy of Railway Total Simulator Compared with Actual Measurement Data

et al. 2018

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“…A more precise simulation model is applied in this section. Specifically, a traction power simulator is used, which enables setting of ground facilities, train characteristics, and operation, and the decentralized control law is utilized in a more practical manner (13) .…”

Section: Calculation Conditionmentioning

confidence: 99%

Train Power Demand Control Using Decentralized and Parallel Control Scheme

2017

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It is important for railway companies to reduce the power consumption of substations in order to reduce the contract power cost and facilities. This study proposes a decentralized control system for controlling the train power demand. Each train calculates its own power allocation independently and in parallel using the information broadcasted by the substations in this control scheme. This control system is very advantageous from the view point of communication load, plug & play' and capital investment because it does not need a server. This work investigates the effect of train power control using the decentralized control scheme via simple and precise numerical simulations' which demonstrate that several trains run on the railroad and are powered by a substation.

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Improvement of DC Railway Simulation Using Iteration History-of-Convergence Calculation

et al. 2020

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Verification of a train traction power simulator for DC feeding system by a commercial operation measurement

Cited by 3 publications

References 5 publications

Evaluating the Accuracy of Railway Total Simulator Compared with Actual Measurement Data

Evaluating the Accuracy of Railway Total Simulator Compared with Actual Measurement Data

Train Power Demand Control Using Decentralized and Parallel Control Scheme

Improvement of DC Railway Simulation Using Iteration History-of-Convergence Calculation

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