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Conceptual exploration of power peak shaving by smart train operation in rail freight transport
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics.ORCID iD: 0000-0001-7393-569X
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics.ORCID iD: 0000-0002-2571-4662
Trafikverket, Gothenburg, Sweden.
2022 (English)In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 236, no 7, p. 838-849Article in journal (Refereed) Published
Abstract [en]

Powerful electric locomotives with high traction performance are foreseen to be used to boost the overall performanceof freight transport. However, they would exert extra burden on the power supply system, so the power peak demandwould be a bottleneck for future freight transport. To avoid large-scale modifications to the existing systems but ensureoperational reliability, this study investigates the formation of power peaks and explores power peak shaving concepts tolet the existing systems be more reliable and accommodate more freight traffic. Different from many previous studieswhich focus on energy saving, this study aims at lowering the power peak demand by “smart train operation”, i.e.altering the train speed profile without compromising running time. This study is mainly performed by simulation basedon a standardized freight operation with full regenerative braking used. But this study also shows a real case study basedon measurement data of power history from an onboard energy meter. The study shows the formation of power peaksin different conditions and suggests some possible measures to shave the power peak demand. The study also showsthat there is a compromise between power peak shaving and energy saving, to which more attention is needed in futurestudies

Place, publisher, year, edition, pages
Sage Publications, 2022. Vol. 236, no 7, p. 838-849
National Category
Vehicle Engineering Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-301182DOI: 10.1177/09544097211045544ISI: 000694681600001Scopus ID: 2-s2.0-85114699833OAI: oai:DiVA.org:kth-301182DiVA, id: diva2:1591266
Note

QC 20220301

Available from: 2021-09-06 Created: 2021-09-06 Last updated: 2023-10-16Bibliographically approved

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Liu, ZhendongBerg, Mats

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CiteExportLink to record
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