Cargando…

An open tool for creating battery-electric vehicle time series from empirical data, emobpy

There is substantial research interest in how future fleets of battery-electric vehicles will interact with the power sector. Various types of energy models are used for respective analyses. They depend on meaningful input parameters, in particular time series of vehicle mobility, driving electricit...

Descripción completa

Detalles Bibliográficos
Autores principales: Gaete-Morales, Carlos, Kramer, Hendrik, Schill, Wolf-Peter, Zerrahn, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196066/
https://www.ncbi.nlm.nih.gov/pubmed/34117257
http://dx.doi.org/10.1038/s41597-021-00932-9
_version_ 1783706615853088768
author Gaete-Morales, Carlos
Kramer, Hendrik
Schill, Wolf-Peter
Zerrahn, Alexander
author_facet Gaete-Morales, Carlos
Kramer, Hendrik
Schill, Wolf-Peter
Zerrahn, Alexander
author_sort Gaete-Morales, Carlos
collection PubMed
description There is substantial research interest in how future fleets of battery-electric vehicles will interact with the power sector. Various types of energy models are used for respective analyses. They depend on meaningful input parameters, in particular time series of vehicle mobility, driving electricity consumption, grid availability, or grid electricity demand. As the availability of such data is highly limited, we introduce the open-source tool emobpy. Based on mobility statistics, physical properties of battery-electric vehicles, and other customizable assumptions, it derives time series data that can readily be used in a wide range of model applications. For an illustration, we create and characterize 200 vehicle profiles for Germany. Depending on the hour of the day, a fleet of one million vehicles has a median grid availability between 5 and 7 gigawatts, as vehicles are parking most of the time. Four exemplary grid electricity demand time series illustrate the smoothing effect of balanced charging strategies.
format Online
Article
Text
id pubmed-8196066
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-81960662021-06-17 An open tool for creating battery-electric vehicle time series from empirical data, emobpy Gaete-Morales, Carlos Kramer, Hendrik Schill, Wolf-Peter Zerrahn, Alexander Sci Data Article There is substantial research interest in how future fleets of battery-electric vehicles will interact with the power sector. Various types of energy models are used for respective analyses. They depend on meaningful input parameters, in particular time series of vehicle mobility, driving electricity consumption, grid availability, or grid electricity demand. As the availability of such data is highly limited, we introduce the open-source tool emobpy. Based on mobility statistics, physical properties of battery-electric vehicles, and other customizable assumptions, it derives time series data that can readily be used in a wide range of model applications. For an illustration, we create and characterize 200 vehicle profiles for Germany. Depending on the hour of the day, a fleet of one million vehicles has a median grid availability between 5 and 7 gigawatts, as vehicles are parking most of the time. Four exemplary grid electricity demand time series illustrate the smoothing effect of balanced charging strategies. Nature Publishing Group UK 2021-06-11 /pmc/articles/PMC8196066/ /pubmed/34117257 http://dx.doi.org/10.1038/s41597-021-00932-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Gaete-Morales, Carlos
Kramer, Hendrik
Schill, Wolf-Peter
Zerrahn, Alexander
An open tool for creating battery-electric vehicle time series from empirical data, emobpy
title An open tool for creating battery-electric vehicle time series from empirical data, emobpy
title_full An open tool for creating battery-electric vehicle time series from empirical data, emobpy
title_fullStr An open tool for creating battery-electric vehicle time series from empirical data, emobpy
title_full_unstemmed An open tool for creating battery-electric vehicle time series from empirical data, emobpy
title_short An open tool for creating battery-electric vehicle time series from empirical data, emobpy
title_sort open tool for creating battery-electric vehicle time series from empirical data, emobpy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196066/
https://www.ncbi.nlm.nih.gov/pubmed/34117257
http://dx.doi.org/10.1038/s41597-021-00932-9
work_keys_str_mv AT gaetemoralescarlos anopentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy
AT kramerhendrik anopentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy
AT schillwolfpeter anopentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy
AT zerrahnalexander anopentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy
AT gaetemoralescarlos opentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy
AT kramerhendrik opentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy
AT schillwolfpeter opentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy
AT zerrahnalexander opentoolforcreatingbatteryelectricvehicletimeseriesfromempiricaldataemobpy