Electric vehicles have penetrated the Dutch market, which increases the potential for decreased local emissions, the use and storage of sustainable energy, and the roll-out and use of electric car-sharing business models. This development also raises new potential issues such as increased electricity demand, a lack of social acceptance, and infrastructural challenges in the built environment. Relevant stakeholders, such as policymakers and service providers, need to align their values and prioritize these aspects. Our study investigates the prioritization of 11 Dutch decision-makers in the field of public electric vehicle charging. These decision-makers prioritized different indicators related to measurements (e.g., EV adoption rates or charge point profitability), organization (such as fast- or smart-charging), and developments (e.g., the development of mobility-service markets) using the best-worst method. The indicators within these categories were prioritized for three different scenario's in time. The results reveal that priorities will shift from EV adoption and roll-out of infrastructure to managing peak demand, using more sustainable charging techniques (such as V2G), and using sustainable energy towards 2030. Technological advancements and autonomous charging techniques will become more relevant in a later time period, around 2040. Environmental indicators (e.g., local emissions) were consistently valued low, whereas mobility indicators were valued differently across participants, indicating a lack of consensus. Smart charging was consistently valued higher than other charging techniques, independent of time period. The results also revealed that there are some distinct differences between the priorities of policymakers and service providers. Having a systematic overview of what aspects matter supports the policy discussion around EVs in the built environment.
In this study we developed models in order to predict the need for public charging points. These models give municipalities an insight into various environmental and consumer related factors that determine the need for public charging points for electric vehicles in the neighbourhood. These factors include, amongst others, the average gross monthly income of households in a certain neighbourhood and the overall number of cars in a certain neighbourhood. On the basis of the models it turns out, among other factors, that neighbourhoods with households with a relatively high average gross monthly income, and a relatively high number of cars, need a relatively large number of public charging points for electric vehicles.
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.
In the coming decades, a substantial number of electric vehicle (EV) chargers need to be installed. The Dutch Climate Accord, accordingly, urges for preparation of regional-scale spatial programs with focus on transport infrastructure for three major metropolitan regions among them Amsterdam Metropolitan Area (AMA). Spatial allocation of EV chargers could be approached at two different spatial scales. At the metropolitan scale, given the inter-regional flow of cars, the EV chargers of one neighbourhood could serve visitors from other neighbourhoods during days. At the neighbourhood scale, EV chargers need to be allocated as close as possible to electricity substations, and within a walkable distance from the final destination of EV drivers during days and nights, i.e. amenities, jobs, and dwellings. This study aims to bridge the gap in the previous studies, that is dealing with only of the two scales, by conducting a two-phase study on EV infrastructure. At the first phase of the study, the necessary number of new EV chargers in 353 4-digit postcodes of AMA will be calculated. On the basis of the findings of the Phase 1, as a case study, EV chargers will be allocated at the candidate street parking locations in the Amsterdam West borough. The methods of the study are Mixed-integer nonlinear programming, accessibility and street pattern analysis. The study will be conducted on the basis of data of regional scale travel behaviour survey and the location of dwellings, existing chargers, jobs, amenities, and electricity substations.
Stedelijke regio’s streven naar een duurzame mobiliteitstransitie. Deze ambitie staat echter op gespannen voet met het hoge autobezit- en autogebruik. De stormachtige introductie van lichte elektrische voertuigen, oftewel LEVs (denk aan e-scooters, e-steps, e-(cargo)bikes en micro-cars) leek een belangrijke ‘gamechanger’ te zijn. Deze LEVs zijn namelijk klein en efficiënt, zijn nagenoeg emissievrij, bieden mogelijkheden voor het verbeteren van het voor- en natransport van het openbaar vervoer (OV) en worden bovendien door hun gebruikers als prettig ervaren tijdens het reizen.Tot op heden maken LEVs deze beloften echter onvoldoende waar. Bij de introductie, thans met name in de vorm van deelsystemen, komen diverse uitdagingen aan het licht zoals: 1) verrommeling en overlast door verkeerd gepareerde LEVs, 2) ongewenste substitutie van loop-, fiets- en OV-verplaatsingen en beperkte impact op autogebruik en 3) en zorgen over de verkeersveiligheid en beleving, met name op de (al steeds drukker wordende) fietsinfrastructuur in Nederland. Deze problemen komen mede voort uit de snelle introductie waardoor gemeenten achter de feiten aanliepen en geen gericht beleid konden voeren. Langzaam komen we nu in een periode van stabilisatie en regulering maar een doorontwikkeling naar pro-actief LEV beleid is nodig om de potentie van LEVs voor de mobiliteitstransitie te ondersteunen. Het LEVERAGE-consortium, bestaande uit sterke partners uit de triple helix, gaat daarom aan de slag met deze vraagstukken. De centrale onderzoeksvraag is:Wat is de potentie van LEVs voor de mobiliteitstransitie naar bereikbare, duurzame, verkeersveilige, inclusieve en leefbare stedelijke regio’s en hoe kan deze optimaal worden benut door een betere integratie van LEVs in het mobiliteitssysteem en het mobiliteitsbeleid en door een effectieve governance van de samenwerking tussen publieke en private stakeholders?Om deze vraag te beantwoorden heeft het consortium een ambitieus en innovatieve onderzoeksopzet gedefinieerd waarbij veel nadruk wordt gelegd op de disseminatie en exploitatie van kennis in de beleidspraktijk.Collaborative partnersProvincie Noord-Brabant, Metropoolregio Arnhem-Nijmegen, Gemeente Eindhoven, Gemeente Breda, Gemeente Arnhem, Ministerie I&W, Rijkswaterstaat, Arriva, PON, Check, Citysteps, Cenex, TIER, We-all-Wheel, Fleet investment, Goudappel, Kennisinstellingen en netwerkorganisaties, HAN, TU/e, CROW, Connekt, POLIS, SWOV.
