• Energy Research

Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step approach to estimating public charging demand of electric vehicles. Previous methods are limited in their ability to provide differentiated results and adapt to future developments. Therefore, we account for user groups (private, carsharing, commercial), technical developments (vehicles, infrastructure), infrastructure availability, and carsharing development (operational area, business models, autonomous vehicles). Our approach also considers the interactions between these factors and allows for scenario analysis yielding the quantity and spatial distribution of public charging demand. We demonstrate our approach for Berlin, Germany. We find that the majority of public charging demand results from carsharing. This demand is concentrated in the city center, even when carsharing is available citywide. Public charging demand for commercial users is relatively low and located outside the city center. For private users, public charging demand shifts to the city center with an increasing market penetration of electric vehicles and technological advancements (increased range, charging speed). Public demand from private users increases dramatically when private infrastructure is absent. Finally, public charging demand shifts to the city center when private users do not have private infrastructure.

Greenhouse gas emissions, in particular CO2 emissions, are a major environmental problem caused mainly by the transportation and the energy sectors. Electric vehicles have been proposed as a solution for mitigating greenhouse gas emissions in road transport. At the same time their potential emission reduction depends on the emissions from the generation of electricity used to charge the vehicles. This study analyzes indirect emissions of electric vehicles to examine optimization potential using real-world data. The results of the study suggest that charging during the daytime is associated with the usage of more electricity from renewable energy sources than charging in typical non-work hours. However, due to the highly violate character of renewable energy sources the differences are rather small. Also, CO2 emissions per kilometer driven depend on driving patterns influencing the energy demand of the vehicles. Accordingly, optimization potential using renewable energy-oriented time course of charging is found to be rather small with an average greenhouse gas emission reduction of 4%. Thus to achieve the potential of electric vehicles to solve environmental issues requires the optimization of driving and charging patterns as well as measures for reducing the carbon intensity in the electricity grid.

Battery electric vehicles (BEV) provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging and connection decisions significantly decreases the load shifting potential of controlled charging. The analysis of marginal values of equations and variables of the optimization problem yields valuable insights on the importance of specific constraints and optimization variables. Assumptions on fleet battery availability and a detailed representation of fast charging are found to have a strong impact on wind curtailment, renewable energy feed-in, and required gas power plant flexibility. A representation of fleet connection to the grid in high temporal detail is less important. Peak load can be reduced by 5% and 3% in both scenarios, respectively. Shifted load is robust across sensitivity analyses while other model results such as curtailment are more sensitive to factors such as underlying data years. Analyzing the importance of increased BEV fleet battery availability for power systems with different weather and electricity demand characteristics should be further scrutinized.

Electric vehicles offer a means to reduce greenhouse gas emissions in passenger transport. The availability of reliable charging infrastructure is crucial for the successful uptake of electric vehicles in dense urban areas. In a pilot project in the city of Hamburg, Germany, public charging infrastructure is equipped with a reservation option providing exclusive access for local residents and businesses. The present paper combines quantitative and qualitative methods to investigate the effects of the newly introduced neighborhood charging concept. We use a methodology combining a quantitative questionnaire survey and qualitative focus group discussions as well as the analyses of charging infrastructure utilization data. Results show that inner-city charging and parking options are of key importance for (potential) users of electric vehicles. Hence, the neighborhood concept is rated very positively. Providing guaranteed charging and parking facilities are therefore likely to increase the stock of EVs. On the other hand, these could to a large extent be additional cars with consequential disadvantages. The study shows that openly accessible infrastructure is presently utilized much more intense than the exclusive option. Consequentially, the concept evaluated should be part of an integrated approach managing parking and supporting efficient concepts like car sharing.

Abstract The city of Berlin has significantly expanded public charging infrastructure for electric vehicles. As a result of this investment, real-world charging data for the city of Berlin are available for the first time. In addition to other metrics, this dataset contains specific information about carsharing vehicles. This research letter offers numerous insights into public charging demand and infrastructure. The results are only now available due to a sufficient fleet size of electric vehicles. The analysis shows that the distribution of charging stations is very unequal in Berlin. The data also show that the infrastructure network is much denser in the city center. While there is an unequal distribution of infrastructure, we see that the utilization of infrastructure is relatively equal. This reflects unequal charging demand, as can be expected based on the location of the infrastructure. We also determine that the majority of public charging events come from free-floating carsharing vehicles. The analysis of infrastructure use shows that the edge of the city center has the highest rates of stations occupied by vehicles after completing charging. Carsharing users occupy infrastructure after charging significantly more than individual private and commercial users. However, if the pricing scheme allows, individual users also occupy infrastructure after completing charging. The research letter provides several policy recommendations for the build-up and operation of charging infrastructure. These focus on charging demand from individual users, infrastructure efficiency, and carsharing operators and their business models. The results are timely as decisions on public charging infrastructure must be made now to meet electric vehicle demand.