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• A methodology combining scenario planning, multi-actor multi-criteria analysis and visioning is proposed. • The methodology helps to develop desired future scenarios supported by a wide range of stakeholders. • The methodology is demonstrated on the development and evaluation of four scenarios for transport and mobility in Europe. Developing a vision for transport and mobility requires the consideration of several alternative scenarios and a selection of preferred futures based on a consensus of stakeholders. In this paper, we propose a methodology that combines scenario analysis (intuitive logics method), multi-actor multi-criteria analysis and visioning to develop normative scenarios, appraise stakeholders' preferences towards them and develop a common vision. The methodology includes participatory elements (workshops and surveys) to foster creativity, build consensus and contribute to social learning. The novelty is that the stakeholders' preferences towards the scenarios are explicitly evaluated based on their distinct set of objectives highlighting the synergies and conflicts towards future scenarios. The methodology is demonstrated by developing and evaluating four scenarios and creating a common vision for transport and mobility in Europe for 2030. The four scenarios were developed through a series of workshops and surveys. Then the preferences of 214 stakeholders in 14 stakeholder groups were appraised towards these scenarios to select the most desired ones. The selected scenarios (Digital nomads and Minimum carbon) were then integrated into a common vision. Our results show that such an approach can lead to a consensual and desired future pathway supported by a wide range of stakeholders. [ABSTRACT FROM AUTHOR]

Scheduling electric vehicle charging sessions allows to aggregate flexibility in order to minimize energy costs and reduce congestion in the electricity grid. Existing research shows that user input for energy and parking duration does not serve as a reliable prediction. The study presents an evaluation of the forecast error and computational performance of the different models. Two main methods are investigated: tree-based (gradient boosted trees LightGBM) and cluster-based (Gaussian mixture model). We also present a novel dynamic cluster-based method, the Similar Sessions method, which employs the similarity between charging sessions based on numerical variables. The results highlight the importance of selecting the forecast model influenced by the availability of training data. The effect of user registration on the accuracy of the forecast is investigated. The tests are run using ACN-Data dataset of Electric Vehicle charging sessions in California, United States. While underperforming on a small dataset with a short look-back period, tree-based methods show superiority while the charging data are accumulating. The Similar Sessions method shows superior accuracy under various data availability conditions. The proposed method requires no prior training, but has slower computational performance in deployment. • Evaluated tree and cluster methods for EV parking & energy based on arrival time. • Proposed "Similar Sessions" using cosine similarity; requires no prior training. • Models without user ID show lower accuracy but still surpass user estimates. • Tested data size sensitivity; the accuracy improves with longer look-back periods. • Gaussian Mix. models are constrained by data volume, revealing limited capacity [ABSTRACT FROM AUTHOR]

This study follows a multi-disciplinary approach to implementing an Energy Community (ECs) in Vega de Valcarce, a rural community in Spain. ECs are entities that encompass collective actions of citizens and other actors towards the open, democratic governance of renewable energy sources; ECs can take various technical and organisational forms. This study developed and evaluated socially accepted, technically optimal and feasible options for the implementation of the EC at Vega de Valcarce. We conducted a participatory multi-criteria analysis incorporating the results of mixed-integer linear programming for energy system optimisation and regulatory analysis of ECs under Spanish law. Our study showed that the main objectives of local stakeholders are the reduction of the energy bill and emissions. The limited liability company fulfilled legal and regulatory restrictions the best by implementing a bigger-sized EC. We summarise the key challenges of implementing an EC in a rural context, mainly legal and financial, and conclude with recommendations on how to overcome these. While contributing to understanding the roll-out of ECs in Spain and Europe, our research aims to provide a structured approach for the uptake of renewable energy in rural areas. [ABSTRACT FROM AUTHOR]

Europe's regulation of passenger car emissions has been proven to have failed when it comes to nitrogen oxide emissions (NO x ) by diesel engines. Due to historical decisions favouring diesel technology, Europe has become a diesel island with no equal worldwide. As a result, virtually every European citizen breathes in air which is deemed harmful to human health. Real driving emissions (RDE) testing by means of portable emissions measurement systems (PEMS) can potentially eliminate the discrepancy between lab and road tests, and will complement the dynamometer type-approval procedure from September 2017 onwards. Despite the significant potential of PEMS testing, the emission assessment has been watered down through politics to provide the automotive manufacturers with additional lead-time. In this way, the lab to road gap is not eliminated but only decreased. This means that diesel cars will continue to over-emit NO x until the 2020s at earliest. This has consequences for effectively bringing down local air quality issues, especially in low emission zones (LEZ). This paper presents a review of the European emission regulation history up to date and makes a comparison with the approach in the other important car markets globally. One can conclude that a substantial update of the European regulatory framework concerning automotive emissions is required, while ambitious post-2021 targets should be set if Europe does not want its automotive industry to lose its competitive position in the global market. In addition, an equilibrium should be sought for between sustainable personal transport in the form of zero-emission vehicles (ZEV), and a sustainable economic climate for the automotive industry. The former is needed if LEZs are to effectively bring down pollutant levels in cities. [ABSTRACT FROM AUTHOR]

Renewable energy communities (RECs) are prominent initiatives to provide end consumers an active role in the energy sector, raise awareness on the importance of renewable energy (RE) technologies and increase their share in the energy system thus reducing greenhouse gas (GHG) emissions. The economic viability of RECs though, depends on multiple interdependent factors that require careful examination for each individual context. This study aims at investigating the impact of electricity tariffs, ratio of electrification of heating and transportation sectors, prices of RE technologies and storage systems, and internal electricity exchange prices on the annual cost for electricity provision of a REC and its GHG emissions. A mixed-integer linear model is developed to minimize energy provision costs for a representative REC in Flanders, Belgium. The results indicate that RECs have the potential to reduce these costs by 10 to 26% and emissions by 5 to 13% compared to business-as-usual. The cost reduction depends on the type of electricity tariffs and the level of uptake of flexible assets such as heat pumps and electric vehicles. The shift towards a higher power component in the electricity tariff makes electricity storage systems more attractive, which leads to higher electricity self-consumption. The introduction of flexible assets adds the possibility to shift demand when tariffs are lower and makes higher installed capacities of photovoltaic systems economically viable due to the increase in the total electricity demand. However, RECs cost reduction compared to individual smart-homes amounts to only 4%–6% in the best cases. Uncertainties stemming from the costs of setting up a REC may reduce the estimated benefits. • First evaluation of economic viability or renewable energy communities in Flanders. • A multi-energy mixed-integer linear model is used to find the cost-optimal solution. • Electricity tariffs and uptake of flexible assets are the most influential factors. • Communities can achieve a cost-reduction up to 26% against business-as-usual cases. • Only 4%–6% cost-reduction when compared against individual prosumers. [ABSTRACT FROM AUTHOR]

In the booming research on the environmental footprint of, for example, electrical vehicles, heat pumps and other (smart) electricity consuming appliances, there is a clear need to know the hourly CO 2 content of one kW h of electricity. Since the CO 2 footprint of electricity can vary every hour; the footprint of for example an electric vehicle is influenced by the time when the vehicle is charged. With the availability of the hourly CO 2 content of one kW h, a decision support tool is provided to fully exploit the advantages of a future smart grid. In this paper, the GWP (Global Warming Potential) per kW h for each hour of the year is calculated for Belgium using a Life Cycle Assessment (LCA) approach. This enables evaluating the influence of the electricity demand on the greenhouse gas emissions. Because of the LCA approach, the CO 2 equivalent content does not only reflect activities related to the production of the electricity within a power plant, but includes carbon emissions related to the building of the infrastructure and the fuel supply chain. The considered feedstocks are nuclear combustible, oil, coal, natural gas, biowaste, blast furnace gas, and wood. Furthermore, renewable electricity production technologies like photovoltaic cells, hydro installations and wind turbines are covered by the research. The production of the wind turbines and solar panels is more carbon intensive (expressed per generated kW h of electricity) than the production of other conventional power plants, due to the lower electricity output. The overall average GWP per kW h is 0.184 kg CO 2 eq/kW h. Throughout the 2011 this value ranges from a minimum of 0.102 kg CO 2 eq/kW h to a maximum of 0.262 kg CO 2 eq/kW h depending on the timing. [ABSTRACT FROM AUTHOR]

Highlights: [•] Extended life cycle tests. [•] Investigation of the battery life cycle at different working conditions. [•] Investigation of the impact fast charging on the battery performances. [•] Extraction all required relationship for development of a cycle life model. [•] Development of a new life cycle model. [ABSTRACT FROM AUTHOR]