The ever-increasing electrification of society has been a cause of utility grid issues in many regions around the world. With the increased adoption of electric vehicles (EVs) in the Netherlands, many new charge points (CPs) are required. A common installation practice of CPs is to group multiple CPs together on a single grid connection, the so-called charging hub. To further ensure EVs are adequately charged, various control strategies can be employed, or a stationary battery can be connected to this network. A pilot project in Amsterdam was used as a case study to validate the Python model developed in this study using the measured data. This paper presents an optimisation of the battery energy storage capacity and the grid connection capacity for such a P&R-based charging hub with various load profiles and various battery system costs. A variety of battery control strategies were simulated using both the optimal system sizing and the case study sizing. A recommendation for a control strategy is proposed.
Insight is given in the data sharing environment that AUAS has provided for charging infrastructure; and effect of privacy legislation are evaluated.
On the eve of the large-scale introduction of electric vehicles, policy makers have to decide on how to organise a significant growth in charging infrastructure to meet demand. There is uncertainty about which charging deployment tactic to follow. The main issue is how many of charging stations, of which type, should be installed and where. Early roll-out has been successful in many places, but knowledge on how to plan a large-scale charging network in urban areas is missing. Little is known about return to scale effects, reciprocal effects of charger availability on sales, and the impact of fast charging or more clustered charging hubs on charging preferences of EV owners. This paper explores the effects of various roll-out strategies for charging infrastructure that facilitate the large-scale introduction of EVs, using agent-based simulation. In contrast to previously proposed models, our model is rooted in empirically observed charging patterns from EVs instead of travel patterns of fossil fuelled cars. In addition, the simulation incorporates different user types (inhabitants, visitors, taxis and shared vehicles) to model the diversity of charging behaviours in an urban environment. Different scenarios are explored along the lines of the type of charging infrastructure (level 2, clustered level 2, fast charging) and the intensity of rollout (EV to charging point ratio). The simulation predicts both the success rate of charging attempts and the additional discomfort when searching for a charging station. Results suggest that return to scale and reciprocal effects in charging infrastructure are considerable, resulting in a lower EV to charging station ratio on the longer term.
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.
