Abstract:The number of electric vehicles in the Netherlands has sharply increased over the past decade. This has caused a need for the allocation of a substantial amount of new electric vehicle chargers around the country, which in turn has been acknowledged by a variety of legislative bodies. However, the approach of how these new charging infrastructures need to be spatially distributed has yet to be decided, including the distance that an electric vehicle charger could be allocated from the final destination of its … Show more
“…The five types of data were chosen as their combination and analysis bring opportunities to research on urban and regional mobility using GIS software, especially involving electric vehicles and electricity-based transport systems. The resulting dataset could be used for analyzing the potential location and distribution of electric vehicles charging infrastructure (similar to  ), or in combination with mobility survey data to determine the impact to the electricity grid supply and infrastructure of new mobility systems (similar to  and  ).…”
Section: Experimental Design Materials and Methodsmentioning
“…Planning electric vehicle charging infrastructure for the Italian highway network, Micari et al (2017) fixed the level of range anxiety at 75%. A study on the association between the walkability of urban areas and the cost of electric vehicles' fast chargers set the level of range anxiety at 70% (Mashhoodi et al, 2019). Alhazmi, Mostafa, and Salama (2017) have acknowledged the significance and uncertainty of the 'remaining electric range' of the EVs and adopted a stochastic function to accommodate it.…”
Section: Previous Studies and Knowledge Gapmentioning
Due to the sharp growth in the adaptation of electric vehicles (EV) in the Netherlands and the objectives of the Dutch Climate Accord is to encourage electric mobility, in the coming decades a substantial number of new EV charging facilities needs to be provided. Efficient planning of EV charging infrastructure is coupled with the notion of range anxiety, which is likely to be severely high in case of soon-to-be EV drivers. This study aims to estimate the cost of developing a new charging infrastructure under five scenarios of range anxiety in Amsterdam East. Employing a Linear Integer Programming optimization model, on the basis of geographic data on car registration, existing EV chargers, and electricity substations, it is obtained that if drivers use 90% of their battery before using a charging facility, the existing charging infrastructure needs to be expanded by only 31% to accommodate almost seven times larger number of EVs-the threshold set by the European Union (EU) legislation on the deployment of alternative fuel infrastructure. If drivers use only 30% of the batteries; however, an increase of 167% in infrastructure is inevitable (accounting for almost five million euro of cost). Second, at any point along the range anxiety spectrum, if the interval between charging session increases for 1 day, the overall cost decreases by more than 30%. These findings are discussed, and two policy approaches are proposed: (1) information technology approach; (2) demand-response approach, on the basis of EU legislation on energy efficiency and deployment of alternative fuel infrastructure.
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