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.
The world of electric mobility and charging infrastructure has accelerated in recent years: from a start-up to a mature market. During the last decade, researchers at Amsterdam University of Applied Sciences have contributed to making the rollout and use of charging infrastructure smarter. By analysing data, simulating future scenarios, testing in practice and developing the necessary hardware, a step towards a mature market has been taken.In this book, we give you insight into this research, focusing on the last five years in which the Future Charging research project took place. We wish you a lot of reading pleasure and inspiration in order to jointly take the next step towards a zero-impact world through mobility.
Deployment and management of environmental infrastructures, such as charging infrastructure for Electric Vehicles (EV), is a challenging task. For policy makers, it is particularly difficult to estimate the capacity of current deployed public charging infrastructure for a given EV user population. While data analysis of charging data has shown added value for monitoring EV systems, it is not valid to linearly extrapolate charging infrastructure performance when increasing population size.We developed a data-driven agent-based model that can explore future scenarios to identify non-trivial dynamics that may be caused by EV user interaction, such as competition or collaboration, and that may affect performance metrics. We validated the model by comparing EV user activity patterns in time and space.We performed stress tests on the 4 largest cities the Netherlands to explore the capacity of the existing charging network. Our results demonstrate that (i) a non-linear relation exists between system utilization and inconvenience even at the base case; (ii) from 2.5x current population, the occupancy of non-habitual charging increases at the expense of habitual users, leading to an expected decline of occupancy for habitual users; and (iii) from a ratio of 0.6 non-habitual users to habitual users competition effects intensify. For the infrastructure to which the stress test is applied, a ratio of approximately 0.6 may indicate a maximum allowed ratio that balances performance with inconvenience. For policy makers, this implies that when they see diminishing marginal performance of KPIs in their monitoring reports, they should be aware of potential exponential increase of inconvenience for EV users.
Phosphorus is an essential element for life, whether in the agricultural sector or in the chemical industry to make products such as flame retardants and batteries. Almost all the phosphorus we use are mined from phosphate rocks. Since Europe scarcely has any mine, we therefore depend on imported phosphate, which poses a risk of supply. To that effect, Europe has listed phosphate as one of its main critical raw materials. This creates a need for the search for alternative sources of phosphate such as wastewater, since most of the phosphate we use end up in our wastewater. Additionally, the direct discharge of wastewater with high concentration of phosphorus (typically > 50 ppb phosphorus) creates a range of environmental problems such as eutrophication . In this context, the Dutch start-up company, SusPhos, created a process to produce biobased flame retardants using phosphorus recovered from municipal wastewater. Flame retardants are often used in textiles, furniture, electronics, construction materials, to mention a few. They are important for safety reasons since they can help prevent or spread fires. Currently, almost all the phosphate flame retardants in the market are obtained from phosphate rocks, but SusPhos is changing this paradigm by being the first company to produce phosphate flame retardants from waste. The process developed by SusPhos to upcycle phosphate-rich streams to high-quality flame retardant can be considered to be in the TRL 5. The company seeks to move further to a TRL 7 via building and operating a demo-scale plant in 2021/2022. BioFlame proposes a collaboration between a SME (SusPhos), a ZZP (Willem Schipper Consultancy) and HBO institute group (Water Technology, NHL Stenden) to expand the available expertise and generate the necessary infrastructure to tackle this transition challenge.
The developments of digitalization and automation in freight transport and logistics are expected to speed-up the realization of an adaptive, seamless, connected and sustainable logistics system. CATALYST determines the potential and impact of Connected Automated Transport (CAT) by testing and implementing solutions in a real-world environment. We experiment on smart yards and connected corridors, to answer research questions regarding supply chain integration, users, infrastructure, data and policy. Results are translated to overarching lessons on CAT implementations, and shared with potential users and related communities. This way, CATALYST helps logistic partners throughout the supply chain prepare for CAT and accelerates innovation.
The developments of digitalization and automation in freight transport and logistics are expected to speed-up the realization of an adaptive, seamless, connected and sustainable logistics system. CATALYST determines the potential and impact of Connected Automated Transport (CAT) by testing and implementing solutions in a real-world environment. We experiment on smart yards and connected corridors, to answer research questions regarding supply chain integration, users, infrastructure, data and policy. Results are translated to overarching lessons on CAT implementations, and shared with potential users and related communities. This way, CATALYST helps logistic partners throughout the supply chain prepare for CAT and accelerates innovation.
