Approximation of overloads for a selected tram traction substation using artificial neural networks
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RIS BIB ENDNOTEApproximation of overloads for a selected tram traction substation using artificial neural networks
Publication date: 29.12.2016
Technical Transactions, 2016, Electronical Engineering Issue 3-E 2016, pp. 39 - 50
https://doi.org/10.4467/2353737XCT.16.264.6063Authors
Approximation of overloads for a selected tram traction substation using artificial neural networks
The article presents some of the results of measurements of loads for a selected tram traction substation for a continuous period of time covering sixteen weeks (112 days). Particular attention was paid to overloads occurring in consequent days. The second part of the article presents the analysis of overloads relating to the time interval of 60 minutes in successive days. This analysis was implemented in Matlab using a two-layer feedforward artificial neural network (ANN). The results of the approximation of the analyzed overloads are promising. A continuation of research may lead to the formulation of mathematical equations that might be useful for designers in terms of sufficiently precise calculations of overloads of rectifier units of DC traction substations.
Information: Technical Transactions, 2016, Electronical Engineering Issue 3-E 2016, pp. 39 - 50
Article type: Original article
Titles:
Approximation of overloads for a selected tram traction substation using artificial neural networks
Approximation of overloads for a selected tram traction substation using artificial neural networks
Faculty of Electrical and Computer Engineering, Cracow University of Technology
ELECTREN S.A.
Department of Traction and Traffic Control, Faculty of Electrical and Computer Engineering, Cracow University of Technology
Published at: 29.12.2016
Article status: Open
Licence: None
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