Abstract

Plug-in electric vehicles are the currently favoured option to decarbonize the passenger car sector. However, a decarbonisation is only possible with electricity from renewable energies and plug-in electric vehicles might cause peak loads if they started to charge at the same time. Both of these issues could be solved with coordinated load shifting (demand response). Previous studies analysed this research question by focusing on private vehicles with domestic and work charging infrastructure. This study additionally includes the important early adopter group of commercial fleet vehicles and reflects the impact of domestic, commercial, work, and public charging. For this purpose, two models are combined that capture the market diffusion of electric vehicles and their charging behaviour (ALADIN), as well as the load shifting potential of several new energy technologies (eLOAD). In a comparison of three different scenarios, we find that the charging of commercial vehicles does not inflict evening load peaks in the same magnitude as purely domestic charging of private cars does. Also, for private cars, charging at work occurs during the day and may reduce the necessity of load shifting while public charging plays a less important role in total charging demand as well as load shifting potential. Nonetheless, demand response reduces the system load by about 2.2 GW or 2.8% when domestic and work charging are considered when compared to a scenario with only domestic charging where a new peak might be created in the winter hours due to load shifting into the night.

Highlights

  • For a deeper insight into the model, in the following, we provide a formal description of the objective function and the relevant constraints for the least-cost scheduling of plug-in electric vehicles (PEVs) charging: The objective function of the linear optimization problem minimizes the costs of the load shifting activity: hmax

  • Let us turn to the simulation results for the PEV stock

  • We found that the market projections for plug-in electric vehicles are dominated by commercial fleet vehicles

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Summary

Motivation

To attain the climate targets, it is necessary to transform the energy system. Renewable energy sources (RES) can help to decrease greenhouse gas emissions in the electricity sector. The aim of this paper is to assess the extent to which additional charging facilities contribute to PEV market penetration in Germany and the shaving of peaks in the residual load (system load minus generation of fluctuating renewable energies). For this purpose, we combine two models that have been developed and described earlier: The model ALADIN (Alternative Automobiles Diffusion and Infrastructure) is used to determine the market diffusion of plug-in electric vehicles and their charging infrastructure.

Methods and and Model
Optimal Vehicle Charging
Results forj P representativeness for theprice
Data Used in the eLOAD Model
Scenario Set up
Assumptions for PEV Market Diffusion
Assumptions for Optimal Vehicle Charging
Development of the Electricity Sector
PEV Market Diffusion
Electricity
Average
Summary, Discussion, and Conclusions
Full Text
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