Book/Dissertation / PhD Thesis

FZJ-2019-02706

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Modellierung zeitlich aufgelöster Ladeenergienachfragen von batterie-elektrischen Fahrzeugen und deren Abbildung in einem Energiesystemmodell

Linssen, J. (Corresponding author)FZJ*

2019
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich
ISBN: 978-3-95806-395-2

Please use a persistent id in citations: http://hdl.handle.net/2128/22069  urn:nbn:de:0001-2019042919

Abstract: The need for climate protection and resource conservation, in combination with current trends in transportation, requires urgent action and the implementation of viable strategies. Today the contribution of electric transportation towards a climate‐neutral and efficient transport system is not clear, given that the reduction potentials are determined to asignificant degree by the charging behavior of vehicle users. Thus far, sound empirical experiences of charging behavior has been lacking. The resulting energy demand from charging is not only characterized by technical and economic conditions, but also by user behavior. The mobility behavior is determined by lifestyles and socio‐demographic aspects and their development over long periods. Therefore, the goal of this study is to develop a model approach that takes into account the lifestyles and socio demographic factors under pinning the charging behavior. This will provide a fact‐based quantification of the effects achieved by electric vehicles in the total energy system. The starting point of this research is an analysis of the status quo of electric vehicle concepts, market conditions, user requirements, charging infrastructure and mobility behavior. On the basis of that, a modeling approach for the charging demand of electric vehicles is developed. To allow for the socio‐demographic mapping of mobility patterns, a data‐mining method is developed to build homogeneous clusters of electric vehicle users. Compared to current models for charging profiles, this method has the advantage that demographic effects and the formation of specific groups of buyers can be taken into account. In summary, the diurnal demand profiles for charging electric vehicles are used to analyzethe impact and attainable effects of electric vehicles within the total energy system. On this, an existing bottom‐up energy system model is adapted for the analysis across all sectors. The combination of charging load and power flow models is not sufficient, because varying charging profiles influence the emissions of the power sector and the cost ranking of techniques and measures in other sectors. The analyses show the high potential of electric vehicles to meet climate protection and energy saving targets. The significant impact of different target regimes in the scenarios on the application of electric vehicles could then be quantified. To illuminate the impact of charging demand profiles on cost‐optimized system designs, further research is needed using adapting models with higher spatial and temporal resolution. Furthermore, the impact of new mobility concepts such as, e.g., autonomous driving and sharing concepts, should be analyzed. The developed data‐mining concept for clustering homogeneous user groups and the resulting charging profiles should also beapplied to the possible change in mobility patterns.

Note: Dissertation, Technische Universität Berlin, 2018

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Contributing Institute(s):

1. Technoökonomische Systemanalyse (IEK-3)

Research Program(s):

1. 134 - Electrolysis and Hydrogen (POF3-134) (POF3-134)

Appears in the scientific report 2019

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