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Software . 2025
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ZENODO
Software . 2025
Data sources: Datacite
ZENODO
Software . 2025
Data sources: Datacite
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Consumer Habits based Approach to model Recharging and Grid INtegration (CHARGIN)

Authors: Bergfeld, Moritz; Rottoli, Marianna; Krajzewicz, Daniel;

Consumer Habits based Approach to model Recharging and Grid INtegration (CHARGIN)

Abstract

Modelling the charging demand of electric vehicles The CHARGIN model was developed at the Institute of Transport Research at the German Aerospace Center (DLR). It enables the simulation of the time- and location-specific charging demands of electric vehicles (EVs) on a microscopic level and provides detailed information about occupied charging stations, the energy demand and the connected charging power of a vehicle fleet over the course of a week in hourly resolution. The results can also be used to derive flexibility potential for controlled charging. The simulation can consider time-varying charging prices for a charging decision in order to take into account scarcity signals from the electricity system. Functionality CHARGIN simulates charging demand based on mobility data, which can be derived, from surveys, such as National Travel Household Surveys, or from transport demand models. Scenario framework conditions, such as fleet composition and charging prices, are also taken into account for the modelling.CHARGIN uses the input information to model the charging behaviour of each individual vehicle in the data set and uses this information to calculate the charging demand under the specified scenario conditions. Hourly-resolved profiles are calculated for the selected region over the course of a week, differentiated by charging location. The results include occupied charging stations, connected power, energy demand and flexibility potential. Four overarching assumptions apply to the CHARGIN calculations: EVs will develop into a mass market. EV users will not change their travel behaviour significantly. EV users will prefer to charge where they already park. The energy system can meet the demand for electricity and energy at all times. These assumptions are consistent with other studies and the expected user behaviour for a mass market of EVs. Contact Moritz BergfeldInstitute of Transport ResearchGerman Aerospace Center (DLR)Moritz.Bergfeld@DLR.de

Related Organizations
Keywords

smart charging, charging demand, charging infrastructure, electric mobility, sector coupling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average