Since 2012 the dutch metropolitan area (the metropole region of amsterdam, the city of amsterdam, rotterdam, the hague, utrecht ) cooperate in finding the best way to stimulate electric mobility through the implementation of a public charging infrastructure. with more than 5600 charge points and 1.6 million charge sessions in the last two years this is one of the most extensively used public charging infrastructure available worldwide. in this paper a benchmark study is carried out to identify different charge patterns between these 5 leading areas with an extensive public charging infrastructure to establish whether and how charge behaviour (e.g. charged volume, capacity utilization, unique users) differs between cities. based on the results first explanations for possible differences in charge patterns between cities will be provided. the study aims to contribute to a better understanding of the utilization of public charging infrastructure in a metropolitan area existing of four city centres and the amsterdam metropolitan area and to provide input for policy makers to prepare a public charging infrastructure ready for the projected growth of electric mobility in the next five years.
While the Municipality of Amsterdam wants to expand the electric vehicle public charging infrastructure to reach carbon-neutral objectives, the Distribution System Operator cannot allow new charging stations where low-voltage transformers are reaching their maximum capacity. To solve this situation, a smart charging project called Flexpower is being tested in some districts. Charging power is limited during peak times to avoid grid congestion and, therefore, enable the expansion of charging infrastructure while deferring grid investments. This work simulates the implementation of the Flexpower strategy with high penetration of electric vehicles, considering dynamic and local power limits, to assess the impact on both the satisfaction of electric vehicle users and the business model of the Charging Point Operator. A stochastic approach, based on Gaussian Mixture Models, has been used to model different profiles of electric vehicle users using data from the Amsterdam public electric vehicle charging infrastructure. Several key performance indicators have been defined to assess the impact of such charging limitations on the different stakeholders. The results show that, while Amsterdam’s existing public charging infrastructure can host just twice the current electric vehicle demand, the application of Flexpower will enable the growth in charging stations without requiring grid upgrades. Even with 7 times more charging sessions, Flexpower could provide a power peak reduction of 57% while supplying 98% of the total energy required by electric vehicle users.
Fast charging is seen as a means to facilitate long-distance driving for electric vehicles (EVs). As a result, roll-out planning generally takes a corridor approach. However, with higher penetration of electric vehicles in urban areas, cities contemplate whether inner-city fast chargers can be an alternative for the growing amount of slow public chargers. For this purpose, more knowledge is required in motives and preferences of users and actual usage patterns of fast chargers. Similarly, with increasing charging speeds of fast chargers and different modes (taxi, car sharing) also switching to electric vehicles, the effect of charging speed should be evaluated as well as preferences amongst different user groups. This research investigates the different intentions and motivations of EV drivers at fast charging stations to see how charging behaviour at such stations differs using both data analysis from charging stations as a survey among EV drivers. Additionally, it estimates the willingness of EV drivers to use fast charging as a substitute for on-street home charging given higher charging speeds. The paper concludes that limited charging speeds imply that EV drivers prefer parking and charging over fast charging but this could change if battery developments allow higher charging speeds.
Economic and environmental sustainability are the two main drivers behind today’s logistics innovation. On the one hand, Industry 4.0 technologies are leading towards self-organizing logistics by enabling autonomous vehicles, which can significantly make logistics transport efficient. Detailed impact analysis of autonomous vehicles in repetitive, short-distance inter-hub transport in logistics hubs like XL Business park is presently being investigated in KIEM project STEERS. On the other hand, the zero-emission technology (such as battery electric) can complement the autonomous logistics transport in making such a logistics hub climate-neutral. In such a scenario, an automatic vehicle charging environment (i.e., charging infrastructure and energy supply) for autonomous electric vehicles will play a crucial role in maximizing the overall operational efficiency and sustainability by reducing the average idle time of both vehicles and charging infrastructure. The project INGENIOUS explores an innovative idea for presenting a sustainable and environment-friendly solution for meeting the energy demand and supply for autonomous electric vehicles in a logistics hub. It will develop and propose an intelligent charging environment for operating autonomous electric vehicles in XL Business park by considering its real-life settings and operational demand. The project combines the knowledge of education and research institutes (Hogeschool van Arnhem en Nijmegen and The University of Twente), industry partners (HyET Solar Netherlands BV, Distribute, Bolk Container Transport and Combi Terminal Twente), and public institutes (XL Business Park, Port of Twente, Regio Twente and Industriepark Kleefse Waard). The project results will form a sound basis for developing a real-life demonstrator in the XL Business park in the subsequent RAAK Pro SAVED project. A detailed case study for Industriepark Kleefse Waard will also be carried out to showcase the broader applicability of the INGENIOUS concept.
