This paper examines the feasibility of using electric powered vehicles in urban freight transport from a carrier's perspective, including their attitudes towards electric freight vehicles (EFVs) and all relevant elements affecting this business case, such as: technological features, existing restricting and promoting policies, financial and non-financial incentives, type of operations, urban settings and logistics organization. We look at the business cases for different truck sizes, varying from small vans to large trucks, in relation to the logistics requirements. This contribution combines the relevant urban freight transport solution directions: technology (both for the vehicle and the supporting IT), logistics and policy. The attitudes of the different EFVs user groups are also taken into account. Only if all these elements support each other, a feasible case can be possible at this moment. We look at the current business case and make conclusions on where it is necessary to act in the near future in order to increase an uptake of electric freight vehicles. For this analysis we use the data collected from current demonstrations that are actually running in the European FP7 project FREVUE, which includes over 100 electric-powered vehicles in the cities of Amsterdam, Lisbon, London, Madrid, Milan, Oslo, Rotterdam, and Stockholm. This data includes operational, attitudinal and financial data for the before situation in which conventional vehicles were used and for the first year(s) where electric vehicles were operated. © 2016 The Authors.
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The transition towards electric mobility is expected to take off the coming years, as more EV car models access the market and charging infrastructure is being expanded. The expansion of charging infrastructure will have to accelerate to keep pace with the fast-growing need for charging. The coming years will be marked by uncertainty regarding technological developments (batteries, range), charging technologies (e.g. fast charging, inductive), growth of car sharing and autonomous driving and impact on user preferences and charging behaviour Data management is key to the EV market and public parties involved: to be able to adapt quickly to changes and to reduce risks and costs. This paper describes the five most important preconditions for effective data management that allows stakeholders to monitor the performance of their charging infrastructure and to take informed decisions on rollout strategies based on data science research results.
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The increased adoption of electric vehicles worldwide is largely caused by the uptake of private electric cars. In parallel other segments such as busses, city logistics and taxis, are increasingly becoming electrified. Amsterdam is an interesting case, as the municipality and the taxi sector have signed a voluntary agreement to realise a full electric taxi fleet by 2025. This paper investigates the results of a survey that was distributed amongst 3000 taxi drivers to examine perceptions and attitudes on the municipal charging incentives as well as taxi ride characteristics.
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As society has to adapt to changing energy sources and consumption, it is driving away from fossil energy. One particular area of interest is electrical driving and the increasing demand for (public) charging facilities. For municipalities, it is essential to adapt to this changing demand and provide more public charging facilities.In order to accommodate on roll-out strategies in metropolitan areas a data driven simulation model, SEVA1, has been developed The SEVA base model used in this paper is an Agent-Based model that incorporate past sessions to predict future charging behaviour. Most EV users are habitual users and tend to use a small subset of the available charge facilities, by that obtaining a pattern is within the range possibilities. Yet, for non-habitual users, for example, car sharing users, obtaining a pattern is much harder as the cars use a significantly higher amount of charge points.The focus of this research is to explore different model implementations to assess the potential of predicting free-floating cars from the non-habitual user population. Most important result is that we now can simulate effects of deployement of car sharing users in the system, and with that the effect on convenience for habitual users. Results show that the interaction between habitual and non habitual EV users affect the unsuccessful connection attempts based increased based on the size of the car-sharing fleet up to approximately 10 percent. From these results implications for policy makers could be drawn.
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Over the last years a large growth in Electric Vehicles (EV) and charging infrastructure (CI) development has been observed. Particularly in metropolitan areas this growth has led to a system in which multitudes of interactions between EV users take place. While many researchers have focused on EV user charging behavior and deployment strategies for CI, little attention has been paid to conceptualizing the problem domain. This research provides a brief overview of complex systems theory, and derives six characterizing elements of complex systems that may be applicable for CI. The paper investigates both theoretically but also empirically how these characterizing elements apply for CI and provides implications for the further roll-out of CI for both policy makers and researchers. We illustrate our findings with preliminary results form ongoing research. Recommendations include the further development of simulation tools that are capable of exploring effects of e.g. non-linear behavior, feedback loops and emergence of new patterns on CI performance. In the end this paper aims to provide directions to enable policy makers to be better prepared for the anticipated exponential growth of EVs and CI.
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This paper discusses the current developments, as well as the barriers and opportunities for using electric freight vehicles in daily city logistics operations based on the experiences from a number of running demonstrations. This paper discusses results from other studies and demonstrations that were published on electro mobility in city logistics in the last three years, as an update of an earlier state of the art review. Next, we present recent narratives based on the more than 100 electric freight vehicles (EFVs) deployed in the European project FREVUE and the experiences of TransMission in using four battery electric Cargohoppers to perform their urban deliveries in Amsterdam. Over the years the attention shifted from a focus on the limitations of EFVs in comparison to conventional vehicles, such as the limited range, towards the question how to better adapt the operations to deal with the EFV characteristics. Although, the business case for using EFVs, in comparison to conventional vehicles, is still suffering from high vehicle purchase price and uncertainty about its residual value, the use of EFVs in daily operations shows that in the majority of cases the current generation of EFVs have a good technical performance. Companies using EFVs are generally satisfied with these vehicles. Obviously still a number of barriers has to be levelled, but large scale EFV usage seems more feasible than before. © 2016 Published by Elsevier B.V.
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Overcoming Challenges in local green H2 economies Organizer: Dr Beata Kviatek, Jean Monnet Chair in Sustainable EU Economy, Centre of Expertise Energy / International Business School / Hanze University of Applied Sciences Groningen, the Netherlands One of the main pathways of the current energy transition includes development of regional green hydrogen economy, usually based in the so-called hydrogen valleys. The development of regional green hydrogen economies enables to green up regional industry and mobility, brings new business opportunities for local and regional businesses, redirects regional investments and financial streams, and proposes new avenues for regional education, knowledge, and research institutions. However, the complexity of regional transformation towards green hydrogen economy, poses challenges that require a close cooperation between different local and regional stakeholders at multiple levels, including national and European. What are these challenges in developing regional green hydrogen economies here, in the northern part of the Netherlands, and in other regions of Europe and what are the new pathways to overcome challenges in regional green hydrogen economies? – is the main question of the proposed panel discussion that will involve academics, policy makers, and practitioners from the northern part of the Netherlands as well as some European regions.
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The increasing share of renewable production like wind and PV poses new challenges to our energy system. The intermittent behavior and lack of controllability on these sources requires flexibility measures like storage and conversion. Production, consumption, transportation, storage and conversion systems become more intertwined. The increasing complexity of the system requires new control strategies to fulfill existing requirements.The SynergyS project addresses the main question how to operate increasingly complex energy systems in a controllable, robust, safe, affordable, and reliable way. Goal of the project is to develop and test a smart control system for a multi-commodity energy system (MCES), with electricity, hydrogen and heat. In scope are an industrial cluster (Chemistry Park Delfzijl) and a residential cluster (Leeuwarden) and their mutual interaction. Results are experimentally tested in two real-life demo-sites scale models: Centre of Expertise Energy (EnTranCe) and The Green Village (TU Delft) represent respectively the industrial and residential cluster.The result will be a market-driven control system to operate a multi-commodity energy system, integrating the industrial and residential cluster. The experimental setup is a combination of physical demo-site assets complemented with (digital) asset models. Experimental validation is based on a demo-scenario including real time data, simulated data and several stress tests.In this session we’ll elaborate more on the project and present (preliminary) results on the testing criteria, scenarios and experimental setup.
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