Timetable Optimization on the Railway Line Electrified in a DC Power System in Terms of Energy Consumption Using the Particle Swarm Optimization
The paper presents the results of the investigation of timetable influence on energy consumption and peak power demand on a DC electrified railway. The aim of the investigation is to optimize a timetable in terms of energy consumption and coasts. The original railway timetable was modified to insure the highest receptivity of the overhead catenary system (OCS) for the trains braking with recuperation. For this purpose the Particle Swarm Optimization has been used in connection with the program carrying out the parallel train performance calculations with the power flow calculation in the DC rail supply system with the recuperative braking. The optimization has been done taking into account the restrictions resulting from passenger waiting time.
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Availability:
- Find a library where document is available. Order URL: http://master.grad.hr/cetra/ocs/index.php/cetra4/cetra2016/schedConf/presentations
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Supplemental Notes:
- Abstract reprinted with permission of University of Zagreb Faculty of Civil Engineering, Department of Transportation.
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Corporate Authors:
University of Zagreb
Faculty of Civil Engineering, Department of Transportation
Kačićeva 26
Zagreb, Croatia 1000 -
Authors:
- Jefimowski, Włodzimierz
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Conference:
- 4th International Conference on Road and Rail Infrastructure – CETRA 2016
- Location: Šibenik , Croatia
- Date: 2016-5-23 to 2016-5-25
- Publication Date: 2016-5
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References;
- Pagination: pp 977-985
- Monograph Title: Proceedings of the 4th International Conference on Road and Rail Infrastructure – CETRA 2016: Road and Rail Infrastructure IV
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Serial:
- Proceedings of the International Conference on Road and Rail Infrastructure CETRA
- Publisher: University of Zagreb
- ISSN: 1848-9850
Subject/Index Terms
- TRT Terms: Electric railroads; Energy consumption; Optimization; Railroads; Timetables
- Uncontrolled Terms: Particle swarm optimization
- Subject Areas: Energy; Planning and Forecasting; Railroads;
Filing Info
- Accession Number: 01637065
- Record Type: Publication
- Files: TRIS
- Created Date: May 31 2017 4:08PM