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dc.contributor.authorMorales, Gaete-
dc.date.accessioned2023-12-07T13:02:04Z-
dc.date.available2023-12-07T13:02:04Z-
dc.date.issued2021-
dc.identifier.otherOER000002792vi
dc.identifier.urihttp://dlib.hust.edu.vn/handle/HUST/23656-
dc.description.abstractThere is substantial research interest in how future feets 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 profles for Germany. Depending on the hour of the day, a feet 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 efect of balanced charging strategies.vi
dc.description.urihttps://www.econstor.eu/handle/10419/235851/vi
dc.formatPDFvi
dc.language.isoenvi
dc.publisherEconStorvi
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Vietnam*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/vn/*
dc.subjectpin-điện từvi
dc.subjectemobpyvi
dc.subjectdữ liệuvi
dc.subjectthực nghiệmvi
dc.subjectcông cụ mởvi
dc.subjectchuỗi thời gianvi
dc.subject.lccTK2945vi
dc.titleAn open tool for creating battery-electric vehicle time series from empirical data, emobpyvi
dc.typeJournal articlevi
dc.description.noteCC BY 4.0vi
Appears in Collections:OER - Kỹ thuật điện; Điện tử - Viễn thông

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