Impact analysis of traction loads on power grid based on probabilistic three‐phases load flow

Che, Yulong; Wang, Xiaoru; Lv, Xiaoqin; Hu, Yi; Li, Long-yuan; Chen, Haoyue

doi:10.1049/joe.2018.8532

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…Thus, several aspects of the power flow analysis regarding both the railway substations and the catenary are better characterized from a probabilistic analysis [41][42][43]. Analyses of feeder current profile, [44,45], harmonic propagation in DC [46] or AC railways [47], and the voltage profile in the catenary [39,48], have been performed using probabilistic methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Traction power substation balance and losses estimation in AC railways using a power transfer device through Monte Carlo analysis

Morais

Martins

2022

Rail. Eng. Science

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The high dynamic power requirements present in modern railway transportation systems raise research challenges for an optimal operation of railway electrification. This paper presents a Monte Carlo analysis on the application of a power transfer device installed in the neutral zone and exchanging active power between two sections. The main analyzed parameters are the active power balance in the two neighbor traction power substations and the system power losses. A simulation framework is presented to comprise the desired analysis and a universe of randomly distributed scenarios are tested to evaluate the effectiveness of the power transfer device system. The results show that the density of trains and the relative branch length of a traction power substation should be considered in the evaluation phase of the best place to install a power transfer device, towards the reduction of the operational power losses, while maintaining the two substations balanced in terms of active power.

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Section: Literature Reviewmentioning

confidence: 99%

Traction power substation balance and losses estimation in AC railways using a power transfer device through Monte Carlo analysis

Morais

Martins

2022

Rail. Eng. Science

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“…In comparison to other users, the 50 Hz single-phase alternating current electrified rail charges the energy system asymmetrically. Electric locomotives with installed power greater than 2000 kW are fitted with rectifiers, which introduce the effects of load asymmetry and higher harmonics of current caused by the deforming consumer [9,19]. For an analysis of these problems, in this paper a method was designed to measure electrical quantities that can influence the quality of electrical power.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Prediction of Reactive Power at Railway Stations Using Adaptive Neuro Fuzzy Inference Systems

2022

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Electricity has become an important concern in today’s society. This is due to the fact that the electric grid now has a greater number of non-linear components. The AC-powered locomotive is one of these non-linear components. The aim of this paper was to model and predict the reactive power produced by an AC locomotive. This paper presents a study on the modelling and prediction of reactive power produced by AC-powered electric locomotives. Reactive power flow has a significant impact on network voltage levels and power efficiency. The research was conducted by using intelligent techniques—more precisely, by using the adaptive neuro fuzzy inference system (ANFIS). Several approaches to the ANFIS structure were used in the research. Of these, we mention the ANFIS-grid partition, ANFIS subtractive clustering and ANFIS fuzzy c-means (FCM) clustering. Thus; for modelling and predicting reactive power, ANFIS was trained, then tested. For the training of ANFIS, experimental data obtained from measurements performed in a train supply sub-station were used. The measurements were taken over a period of time when the locomotives were far away from the station, close to the station, and at the station, respectively. The currents and voltages from the supply substation, respectively the active, reactive, and distorted powers, were measured on the data acquisition board. With the measured data of the reactive power, the modelling with ANFIS was performed, and a prediction of the variation in the reactive power was made. The paper analysed the results of the modelling by comparing between several types of ANFIS architectures. The values of RMSE, RMS and the training time of ANFIS were compared for several structures of ANFIS.

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Correlation analysis of traction load sequences based on optimal delay method

Che

Wang

et al. 2022

International Journal of Electrical Power & Energy Systems

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Impact analysis of traction loads on power grid based on probabilistic three‐phases load flow

Cited by 4 publications

References 9 publications

Traction power substation balance and losses estimation in AC railways using a power transfer device through Monte Carlo analysis

Traction power substation balance and losses estimation in AC railways using a power transfer device through Monte Carlo analysis

Modelling and Prediction of Reactive Power at Railway Stations Using Adaptive Neuro Fuzzy Inference Systems

Correlation analysis of traction load sequences based on optimal delay method

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