• Energy Research
• AT close
• Transport Research close
• Energy Research close

Electric vehicles play a key role in strategic development plans of urban regions in Europe because they are seen as a promising technology to promote environmental quality, livability, and sustainability. Studies on electric mobility mostly concentrate on battery electric cars and disregard hybrid technologies which could address the weakness of range limitations. Therefore, this paper studies the impact of extended range electric vehicle (EREV) solutions on travel behavior, energy demand, environment, and overall sustainable development in the greater Stuttgart region in Germany. An integrated large-scale simulation approach merging different models is applied for future scenarios in 2025. The results show that with EREVs (1) most travel patterns can be fulfilled, (2) the impact on electricity generation is marginal, and (3) there is a high potential to reduce local emissions in areas with high traffic density. Overall, electric mobility is evaluated as one component toward sustainable development in the study area. This study demonstrates the complexity of the topic and highlights the importance of addressing this issue with a multidisciplinary approach

The aim of this work is to schedule the charging of electric vehicles (EVs) at a single charging station such that the temporal availability of each EV as well as the maximum available power at the station are considered. The total costs for charging the vehicles should be minimized w.r.t. time-dependent electricity costs. A particular challenge investigated in this work is that the maximum power at which a vehicle can be charged is dependent on the current state of charge (SOC) of the vehicle. Such a consideration is particularly relevant in the case of fast charging. Considering this aspect for a discretized time horizon is not trivial, as the maximum charging power of an EV may also change in between time steps. To deal with this issue, we instead consider the energy by which an EV can be charged within a time step. For this purpose, we show how to derive the maximum charging energy in an exact as well as an approximate way. Moreover, we propose two methods for solving the scheduling problem. The first is a cutting plane method utilizing a convex hull of the, in general, nonconcave SOC–power curves. The second method is based on a piecewise linearization of the SOC–energy curve and is effectively solved by branch-and-cut. The proposed approaches are evaluated on benchmark instances, which are partly based on real-world data. To deal with EVs arriving at different times as well as charging costs changing over time, a model-based predictive control strategy is usually applied in such cases. Hence, we also experimentally evaluate the performance of our approaches for such a strategy. The results show that optimally solving problems with general piecewise linear maximum power functions requires high computation times. However, problems with concave, piecewise linear maximum charging power functions can efficiently be dealt with by means of linear programming. Approximating an EV’s maximum charging power with a concave function may result in practically infeasible solutions, due to vehicles potentially not reaching their specified target SOC. However, our results show that this error is negligible in practice.

As an important trend in the automotive industry, electrification of propulsion systems has potential to significantly reduce greenhouse-gas emissions of the transportation sector. Whereas electric vehicles do not produce exhaust emissions during driving, the impact of electricity provision for charging batteries, as well as the impact of vehicle production play an essential role in a holistic consideration of the carbon footprint. The paper introduces a comprehensive evaluation of greenhouse gas-emission-related factors of cars driven by different propulsion technologies, considering the entire product life cycle. This comprises vehicle production, including battery system, electric powertrain and other relevant components, the car’s use phase under consideration of different electricity mixes and the end-of-life phase. The results of the study give insights of influencing factors on life-cycle-related carbon-dioxide-equivalent emissions of cars driven by combustion engines, hybrid powertrains and battery-electric propulsion systems. In addition, a comparison of actual mass-production cars is made and the total life-cycle carbon footprints are discussed under different boundary conditions of electric power supply. In this way, the article comprehensively introduces an automotive life-cycle assessment and provides fundamental information, contributing to an objective discussion of different propulsion technologies.

Abstract Carbon capture and storage (CCS) is a key technology to reduce carbon dioxide (CO2) emissions from industrial processes in a feasible, substantial, and timely manner. For geological CO2 storage to be safe, reliable, and accepted by society, robust strategies for CO2 leakage detection, quantification and management are crucial. The STEMM-CCS (Strategies for Environmental Monitoring of Marine Carbon Capture and Storage) project aimed to provide techniques and understanding to enable and inform cost-effective monitoring of CCS sites in the marine environment. A controlled CO2 release experiment was carried out in the central North Sea, designed to mimic an unintended emission of CO2 from a subsurface CO2 storage site to the seafloor. A total of 675 kg of CO2 were released into the shallow sediments (∼3 m below seafloor), at flow rates between 6 and 143 kg/d. A combination of novel techniques, adapted versions of existing techniques, and well-proven standard techniques were used to detect, characterise and quantify gaseous and dissolved CO2 in the sediments and the overlying seawater. This paper provides an overview of this ambitious field experiment. We describe the preparatory work prior to the release experiment, the experimental layout and procedures, the methods tested, and summarise the main results and the lessons learnt.

There has been a tremendous increase in the level of human activity on Earth since the start Industrial Revolution which has promoted great development within societies. However, recent scientific studies have shown that our actions have caused detrimental damage to our environment resulting in the observable phenomenon known as climate change. Some of the adverse effects of climate change include the destruction of habitats, changes in weather patterns and propagation of diseases ��� to name a few. This trend impacts all systems inhabiting our planet and has very grievous implications for the future if no action is taken. A major contributor to climate change is the transport sector which causes significant CO2 and green house gas pollution ��� due the heavy reliance on consuming fossil fuels. These harmful gases have been proven to facilitate global warming. The international community has recognised these undeniable facts and therefore is taking decisive steps to ensure that all sectors to become sustainable. There is a strong advocacy by the global community to promote "sustainable Transport" and ensure that the transport sector becomes emission free and less carbon intensive. An innovative solution to facilitate this transition to sustainable transport is the adoption of electric vehicles (EV���s) which are environmentally friendly and very efficient. EV���s are developing at a rapid pace and the EU is taking a lead in this revolution. Within the EU, the Netherlands has taken proactive steps to deploy as many EV within the country and has set ambitious goal to go all-electric by 2030. Given this bold target; this prompted the question that if the EV market share is forecasted to increase in the Netherlands, how much will it cost to install the appropriate infrastructure to accompany these vehicles? Hence the scope is to answer the following research question: ���To determine the financial viability of installing public electric vehicle charging infrastructure (Level 2 and 3) in the Netherlands���. It was concluded that public charging infrastructure is capital intensive and the associated costs cannot be borne by the government alone - effective financial co-operation between the public and private sectors is required. To get a holistic view to address this research question, global EV trends, the Dutch EV market and Dutch policies have been included.

Abstract Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.