Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation. / Bocharnikov, Yury; Tobias, Andrew; Roberts, Christian.

IET Conference on Railway Traction Systems, RTS 2010. Vol. 2010 13342. ed. 2010. 32.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Bocharnikov, Y, Tobias, A & Roberts, C 2010, Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation. in IET Conference on Railway Traction Systems, RTS 2010. 13342 edn, vol. 2010, 32, IET Conference on Railway Traction Systems, RTS 2010, Birmingham, United Kingdom, 13/04/10. https://doi.org/10.1049/ic.2010.0038

APA

Bocharnikov, Y., Tobias, A., & Roberts, C. (2010). Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation. In IET Conference on Railway Traction Systems, RTS 2010 (13342 ed., Vol. 2010). [32] https://doi.org/10.1049/ic.2010.0038

Vancouver

Bocharnikov Y, Tobias A, Roberts C. Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation. In IET Conference on Railway Traction Systems, RTS 2010. 13342 ed. Vol. 2010. 2010. 32 https://doi.org/10.1049/ic.2010.0038

Author

Bocharnikov, Yury ; Tobias, Andrew ; Roberts, Christian. / Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation. IET Conference on Railway Traction Systems, RTS 2010. Vol. 2010 13342. ed. 2010.

Bibtex

@inproceedings{6c41045d17be4ee5a0770d9f344f64c1,
title = "Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation",
abstract = "It is known that for a single DC powered train, energy savings can be obtained by a combination of motoring, braking and coasting during a journey. However, this does not necessarily yield all of the net energy savings that are possible if other trains are running within the same electrical section. Further savings may be available during motoring by using energy regenerated by other trains while they are braking. This paper first presents a single train trajectory optimisation to obtain minimum energy consumption with maximum regenerated energy, and then considers net energy reduction between two adjacent DC substations when the optimised trajectories are used. Each trajectory is optimised individually using a genetic algorithm to search for the best possible compromise between energy consumption and journey time requirements. A weighted combination of these two is used as the objective function and the rates of train acceleration, braking and coasting form a set of variables that define a driving strategy. In order to estimate the benefits and effects of optimised trajectories on net energy consumption, multi-train simulation was then performed for both fastest and optimised journeys. Both qualitatively and quantitatively, the results suggest that further considerable reductions of net energy consumption may be achieved by the adjustment of schedules for both the up and down direction so as to increase the receptivity of those trains within each subsection, or by the recalculation of single train trajectories with different optimisation criteria. Finally, consideration is given to the possible application of the technique on a real railway traction system. Although demonstrated here on a DC system, the method could equally be applied to AC electrified railways.",
keywords = "Energy reduction, Genetic algorithm, Optimisation, Railway, Train control",
author = "Yury Bocharnikov and Andrew Tobias and Christian Roberts",
year = "2010",
month = aug,
day = "19",
doi = "10.1049/ic.2010.0038",
language = "English",
isbn = "9781849192118",
volume = "2010",
booktitle = "IET Conference on Railway Traction Systems, RTS 2010",
edition = "13342",
note = "IET Conference on Railway Traction Systems, RTS 2010 ; Conference date: 13-04-2010 Through 15-04-2010",

}

RIS

TY - GEN

T1 - Reduction of train and net energy consumption using genetic algorithms for trajectory optimisation

AU - Bocharnikov, Yury

AU - Tobias, Andrew

AU - Roberts, Christian

PY - 2010/8/19

Y1 - 2010/8/19

N2 - It is known that for a single DC powered train, energy savings can be obtained by a combination of motoring, braking and coasting during a journey. However, this does not necessarily yield all of the net energy savings that are possible if other trains are running within the same electrical section. Further savings may be available during motoring by using energy regenerated by other trains while they are braking. This paper first presents a single train trajectory optimisation to obtain minimum energy consumption with maximum regenerated energy, and then considers net energy reduction between two adjacent DC substations when the optimised trajectories are used. Each trajectory is optimised individually using a genetic algorithm to search for the best possible compromise between energy consumption and journey time requirements. A weighted combination of these two is used as the objective function and the rates of train acceleration, braking and coasting form a set of variables that define a driving strategy. In order to estimate the benefits and effects of optimised trajectories on net energy consumption, multi-train simulation was then performed for both fastest and optimised journeys. Both qualitatively and quantitatively, the results suggest that further considerable reductions of net energy consumption may be achieved by the adjustment of schedules for both the up and down direction so as to increase the receptivity of those trains within each subsection, or by the recalculation of single train trajectories with different optimisation criteria. Finally, consideration is given to the possible application of the technique on a real railway traction system. Although demonstrated here on a DC system, the method could equally be applied to AC electrified railways.

AB - It is known that for a single DC powered train, energy savings can be obtained by a combination of motoring, braking and coasting during a journey. However, this does not necessarily yield all of the net energy savings that are possible if other trains are running within the same electrical section. Further savings may be available during motoring by using energy regenerated by other trains while they are braking. This paper first presents a single train trajectory optimisation to obtain minimum energy consumption with maximum regenerated energy, and then considers net energy reduction between two adjacent DC substations when the optimised trajectories are used. Each trajectory is optimised individually using a genetic algorithm to search for the best possible compromise between energy consumption and journey time requirements. A weighted combination of these two is used as the objective function and the rates of train acceleration, braking and coasting form a set of variables that define a driving strategy. In order to estimate the benefits and effects of optimised trajectories on net energy consumption, multi-train simulation was then performed for both fastest and optimised journeys. Both qualitatively and quantitatively, the results suggest that further considerable reductions of net energy consumption may be achieved by the adjustment of schedules for both the up and down direction so as to increase the receptivity of those trains within each subsection, or by the recalculation of single train trajectories with different optimisation criteria. Finally, consideration is given to the possible application of the technique on a real railway traction system. Although demonstrated here on a DC system, the method could equally be applied to AC electrified railways.

KW - Energy reduction

KW - Genetic algorithm

KW - Optimisation

KW - Railway

KW - Train control

UR - http://www.scopus.com/inward/record.url?scp=77956278369&partnerID=8YFLogxK

U2 - 10.1049/ic.2010.0038

DO - 10.1049/ic.2010.0038

M3 - Conference contribution

SN - 9781849192118

VL - 2010

BT - IET Conference on Railway Traction Systems, RTS 2010

T2 - IET Conference on Railway Traction Systems, RTS 2010

Y2 - 13 April 2010 through 15 April 2010

ER -