The Netherlands is a frontrunner in the field of public charging infrastructure, having a high number of public charging stations per electric vehicle (EV) in the world. During the early years of adoption (2012-2015) a large percentage of the EV fleet were Plugin Hybrid Electric Vehicles (PHEV)due to the subsidy scheme at that time. With an increasing number of Full Electric Vehicles (FEVs) on the market and a current subsidy scheme for FEV only, a transition of the EV fleet from PHEV to FEV is expected. This is hypothesized to have effect on charging behavior of the complete fleet, reason to understand better how PHEVs and FEVs differ in charging behavior and how this impacts charging infrastructure usage. In this paper, the effects of the transition of PHEV to FEV is simulated by extending an existing Agent Based Model. Results show important effects of this transitionon charging infrastructure performance.
298 woorden: In the upcoming years the whole concept of mobility will radically change. Decentralization of energy generation, urbanization, digitalization of processes, electrification of vehicles and shared mobility are only some trends which have a strong influence on future mobility. Furthermore, due to the shift towards renewable energy production, the public and the private sector are required to develop new infrastructures, new policies as well as new business models. There are countless opportunities for innovative business models emerging. Companies in this field – such as charging solution provider, project management or consulting companies that are part of this project, Heliox and Over Morgen respectively – are challenged with countless possibilities and increasing complexity. How to overcome this problem? Academic research proposes a promising approach, namely the use of business model patterns for business model innovation. In short, these business model patterns are descriptions of proven practical solutions to common business model challenges. An example for a general pattern would be the business model pattern “Consumables”. It describes how to lock in a customer into an ecosystem by using a subsidized basic product and complement it with overpriced consumables. This pattern works really well and has been used by many companies (e.g. Senseo, HP, or Gillette). To support the business model innovation process of Heliox and Over Morgen as well as companies in the electric mobility space in general, we propose to systematically consolidate and develop business model patterns for the electric mobility sector and to create a database. Electric mobility patterns could not only foster creativity in the business model innovation process but also enhance collaboration in teams. By having a classified list of business model pattern for electric mobility, practitioners are equipped which a heuristic tool to create, extend and revise business models for the future.
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.
Elektrisch rijden staat aan de vooravond van een schaalsprong. De ambitie van zowel de Nederlandse overheid als internationale overheden is om binnen nu en 12 jaar alleen nog maar elektrische auto’s nieuw op de markt toe te laten. De elektrisch vervoer (EV) keten staat voor de grote uitdaging om deze schaalsprong op tijd met voldoende laadinfrastructuur te faciliteren. Nederlandse ketenpartners willen, net als de afgelopen jaren, koploper blijven op het gebied van EV-laadinfrastructuur en daarom goed voorbereid zijn op deze schaalsprong. De centrale praktijkvraag van de EV-ketenpartners is “Hoe kan de toekomstige laadbehoefte voor elektrische voertuigen in een snel groeiende markt met nieuwe gebruikersgroepen goed worden ingevuld?” Het doel van Future Charging is om bij te dragen aan de doorbraak van elektrisch rijden door kennis over de laadbehoefte van nieuwe gebruikersgroepen te ontwikkelen en toekomstig laadgedrag in een agent-based model te simuleren. Simulaties geven EV-ketenpartners concrete inzichten in effecten van toekomstscenario’s op het gebruik van laadinfrastructuur, de impact op het elektriciteitsnet en openbare ruimte. Deze kennis ondersteunt EV-ketenpartners bij de uitrol van toekomstbestendige laadinfrastructuur. In totaal brengt dit project 17 consortiumpartners bij elkaar waarmee de volledige EV-keten voor laadinfrastructuur vertegenwoordigd is: gemeenten, netbeheerders, laadpaal-exploitanten, energiebedrijven en gebruikers. De partners bieden hiermee een rijke praktijkomgeving waar continu kan worden geleerd over de veranderende laadbehoefte van verschillende gebruikersgroepen en in verschillende ruimtelijke settings: van grootstedelijk tot “laden in de regio”. Sinds 2014 beheert en monitort de Hogeschool van Amsterdam de laaddata voor G4/MRA-E. Meer dan 8,5 miljoen laadsessies zijn opgeslagen in een professioneel datawarehouse en middels beveiligde accounts toegankelijk voor onderzoek. Future Charging slaat de brug tussen theorie over laadbehoefte, laadgedrag en agent-based simuleren en de praktijk van laadinfrastructuur. Het resultaat is een praktisch toepasbaar simulatiemodel waarmee ontwerpstudies en praktijkcases worden doorgerekend.
