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Use of Numerical Methods in the Analysis of Traction Energy Systems—An Overview of the Practical Examples

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Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 451))

Abstract

A characteristic feature of trolleybus transport is the random nature of traffic caused by congestion. It predestinates statistical and numerical methods for the analysis of trolleybus energy system. There are presented 3 methods of trolleybus traction system analysis: simulation of supply system based on Monte Carlo method, analysis of energy recovery potential based on statistical data analysis and benchmark of trolleybus supply system by one of Multiple Criteria Data Analysis—Data Envelopment Analysis (DEA) method.

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References

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Acknowledgments

This paper has been elaborated in the framework of the project ELIPTIC co-financed by the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 636012.

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Authors and Affiliations

  1. Faculty of Electrical and Control Engineering, Gdansk University of Technology, G. Narutowicza 11/12, 80-233, Gdansk, Poland

    Mikołaj Bartłomiejczyk

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  1. Mikołaj Bartłomiejczyk
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Correspondence to Mikołaj Bartłomiejczyk .

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Editors and Affiliations

  1. Sci N/w for Innova and Research Exc, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Rostov State Transport University, Rostov-on-Don, Russia

    Sergey Kovalev

  3. Bauman Moscow State Technical University, Moscow, Russia

    Valery Tarassov

  4. Institute of Mathematics, VŠB-Technical University of Ostrava, Ostrava, Czech Republic

    Václav Snášel

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Bartłomiejczyk, M. (2016). Use of Numerical Methods in the Analysis of Traction Energy Systems—An Overview of the Practical Examples. In: Abraham, A., Kovalev, S., Tarassov, V., Snášel, V. (eds) Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16). Advances in Intelligent Systems and Computing, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-319-33816-3_40

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  • DOI: https://doi.org/10.1007/978-3-319-33816-3_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33815-6

  • Online ISBN: 978-3-319-33816-3

  • eBook Packages: EngineeringEngineering (R0)

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