Measurement and simulation of stray currents caused by AC railway traction

Kolář, Václav; Hrbáč, Roman; Mlčák, Tomáš

doi:10.1109/epe.2015.7161203

Cited by 10 publications

(6 citation statements)

References 1 publication

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“…Şekil 2 ile DC beslemeli bir demiryolunda DC gerilimin üretilmesine ait şematik verilmektedir. [12][13][14][15][16]. Çalışmaların büyük kısmının en önemli odak noktasını optimize sürüş teknikleri oluşturmaktadır [17].…”

Section: (7) (8)unclassified

Dinamik Model Algoritması ile 1500 V DC Beslemeli Bir Metro Hattında Katener Kısa Devre Durumunun Analizi

Akçay¹,

Kocaarslan

2019

Haliç Üniversitesi Fen Bilimleri Dergisi

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Ulaşım sistemleri içinde elektrik beslemeli demiryolları yatırım tercihi olarak yüksek bir orana sahiptir. Elektrikli demiryollarında ise elektrifikasyon sisteminin elektrik verme görevini kusursuz olarak yerine getirebilmesi işletme sürekliliği için esastır. Tasarım öncesinde elektrifikasyon sistemi benzetimi yapılarak sisteme ait kapasite, performans ve arıza durumları test edilmektedir. İşletme sürekliliği için arıza durumlarının analizi ve olası tedbirlerin alınması büyük önem taşımaktadır. Bu çalışmada dinamik bir model oluşturularak 1500 V DC beslemeli bir şehiriçi metro hattının benzetimi yapılmıştır. Dinamik yapı için geliştirilen algoritma anlatılarak benzetim sonuçları verilmiştir. Çalışma için katener sisteminde olası bir kısa devre durumunun analizi araştırılmıştır. 7 trafo merkezi bulunan bir raylı sistem hattına ait veriler kullanılarak kısa devre durumunun olası etkileri grafikler üzerinden değerlendirilmiştir. Elde edilen sonuçlar üzerinden alınması gereken tedbirler verilmiştir.

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Section: (7) (8)unclassified

Dinamik Model Algoritması ile 1500 V DC Beslemeli Bir Metro Hattında Katener Kısa Devre Durumunun Analizi

Akçay¹,

Kocaarslan

2019

Haliç Üniversitesi Fen Bilimleri Dergisi

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“…The Relative absolute Error is acquired by dividing the sum of real error of a measuring line by the sum of predicted error. In the RAE equation given by equation (13), xobs are the real values, xmodel are the predicted values, model is the mean value of xmodel, n is the measurement number [35][36].…”

Section: Relative Absolute Error (Rae)mentioning

confidence: 99%

“…Since the voltage drop occurring on the line and the currents drawn do not reach high values under normal operating conditions, the distances between the supply stations may be longer. As the number of traction supply stations and the efficiency of the traction force system increase, the voltage drop on the line and the losses decrease [12][13][14][15][16]. The traction system of the railway vehicle consists of a transformer, a three-phase PWM inverter and an asynchronous engine.…”

Section: Introductionmentioning

confidence: 99%

Comparison of ANN and ANFIS Methods for the Voltage-Drop Prediction on an Electric Railway Line

Kocaarslan¹,

Akçay²,

Akgündoğdu³

et al. 2018

IU-JEEE

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Railway electrification systems are designed with regard to the operating data and design parameters. The minimum voltage rating required by traction during the operation should be provided. The maximum voltage drop on a line determines the minimum traction voltage. This voltage should be maintened within certain limits for the continuity of operation. In this study, the maximum voltage drop generated via traction was determined using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for a 25-kV AC-supplied railway. The voltage drop on line was calculated with regard to the operating data using ANN and ANFIS. ANN and ANFIS were explained, and the results were compared. The Levenberg-Marquardt (LM) algorithm was used for the ANN model. The LM algorithm is preferred because of the speed and stability it provides for the training of ANNs. The data created for one-way supply status were examined for simulation.

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“…V 1 =V n1 −I vehicle ×R 1 −I vehicle ×R 3 (1) Since the voltage drop occurring on the line and the currents drawn do not reach high values under normal operating conditions, the distances between the supply stations may be longer. As the number of traction supply stations and the efficiency of the traction force system increase, the voltage drop on the line and the losses decrease [8][9][10][11][12]. The single-line scheme of a DC-fed line is presented in Figure 2.…”

Section: Introductionmentioning

confidence: 99%

Determination of distance between DC traction power centers in a 1500-V DC subway line with artificial intelligence methods

Akçay¹,

Kocaarslan²

2019

Turk J Elec Eng & Comp Sci

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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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Measurement and simulation of stray currents caused by AC railway traction

Cited by 10 publications

References 1 publication

Dinamik Model Algoritması ile 1500 V DC Beslemeli Bir Metro Hattında Katener Kısa Devre Durumunun Analizi

Dinamik Model Algoritması ile 1500 V DC Beslemeli Bir Metro Hattında Katener Kısa Devre Durumunun Analizi

Comparison of ANN and ANFIS Methods for the Voltage-Drop Prediction on an Electric Railway Line

Determination of distance between DC traction power centers in a 1500-V DC subway line with artificial intelligence methods

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