Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-11917
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Main Title: Methodology for Estimating the Spatial and Temporal Power Demand of Private Electric Vehicles for an Entire Urban Region Using Open Data
Author(s): Straub, Florian
Streppel, Simon
Göhlich, Dietmar
Type: Article
URI: https://depositonce.tu-berlin.de/handle/11303/13123
http://dx.doi.org/10.14279/depositonce-11917
License: https://creativecommons.org/licenses/by/4.0/
Abstract: With continuous proliferation of private battery electric vehicles (BEVs) in urban regions, the demand for electrical energy and power is constantly increasing. Electrical grid infrastructure operators are facing the question of where and to what extent they need to expand their infrastructure in order to meet the additional demand. Therefore, the aim of this paper is to develop an activity-based mobility model that supports electrical grid operators in detecting and evaluating possible overloads within the electrical grid, deriving from the aforementioned electrification. We apply our model, which fully relies on open data, to the urban area of Berlin. In addition to a household travel survey, statistics on the population density, the degree of motorisation, and the household income in fine spatial resolution are key data sources for generation of the model. The results show that the spatial distribution of the BEV charging energy demand is highly heterogeneous. The demand per capita is higher in peripheral areas of the city, while the demand per m2 area is higher in the inner city. For reference areas, we analysed the temporal distribution of the BEV charging power demand, by assuming that the vehicles are solely charged at their residential district. We show that the households’ power demand peak in the evening coincide with the BEV power demand peak while the total power demand can increase up to 77.9%.
Subject(s): electric vehicle
activity-based simulation
transportation electrification
charging power demand
spatial temporal distribution
open data
Issue Date: 8-Apr-2021
Date Available: 19-May-2021
Language Code: en
DDC Class: 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Sponsor/Funder: DFG, 410830482, Multi-Domain Modellierung und Optimierung eines integrierten Energieversorgungs- und Fahrzeugsystems für urbane Ballungsräume
DFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berlin
Journal Title: Energies
Publisher: MDPI
Volume: 14
Issue: 8
Article Number: 2081
Publisher DOI: 10.3390/en14082081
EISSN: 1996-1073
TU Affiliation(s): Fak. 5 Verkehrs- und Maschinensysteme » Inst. Maschinenkonstruktion und Systemtechnik » FG Methoden der Produktentwicklung und Mechatronik
Appears in Collections:Technische Universität Berlin » Publications

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