• Energy Research
• Restricted close
• Open Source close
• 7. Clean energy close
• 11. Sustainability close
• 2. Zero hunger close
• Transport Research close

This paper nuances the claim that electric vehicles offer a similar form of automobility as petrol cars through an analysis of the (im)mobility and circulations that enable them. With circulation a...

Abstract In the current transition to a smarter and more efficient transportation system, battery electric vehicle mileage and the time required for charging are still two main constraints that need to be overcome to enable a larger penetration of electric vehicles. Moreover, the few charging stations available are a consequence of the “supply and demand” problem. Consequently, wireless dynamic recharging can be a complementary solution to address the problems of light-duty electric mobility and an added-value towards autonomous vehicles. Consequently, this paper presents an innovative approach based on real world mobility patterns collected for a sample in the city of Lisbon, Portugal, to assess users’ electric vehicle feasibility by assessing different recharging scenarios, comparing stationary and dynamic recharging scenarios. The results indicate that at least 15 % more drivers would be eligible to own an electric vehicle if wireless charging was available. Moreover, wireless charging reduces the range of battery used, with stationary charging requiring circa 3.2 times more battery range. The developed approach confirms that wireless dynamic recharging can significantly change the framework of current electric mobility limitations, reducing range anxiety issues, contributing to redesign electric vehicle battery capacity and overcome barriers in stationary charging deployment and availability.

<div class="section abstract"><div class="htmlview paragraph">The transport sector is experiencing a shift to zero-carbon powertrains driven by aggressive international policies aiming to fight climate change. Battery electric vehicles (BEVs) will play the main role in passenger car applications, while diversified solutions are under investigation for the heavy-duty sector. Within this framework, Light Commercial Vehicles (LCVs) impact is not negligible and accountable for about 2.5% of greenhouse gas (GHG) emissions in Europe. In this regard, few LCV comparative assessments on green powertrains are available in the scientific literature and justified by the fact that several factors and limitations should be considered and addressed to define optimal powertrain solutions for specific use cases. The proposed research study deals with a comparative numerical assessment of different zero-carbon powertrain solutions for LCV. BEVs are compared to hydrogen-based fuel cells (FC) and internal combustion engines (ICE) powered vehicles. The analysis is conducted through specifically developed vehicle models. Vehicle performance in terms of energy efficiency, well-to-wheel GHG, range, payload, and total cost of ownership (TCO) are compared. Optimal powertrain configurations based on predefined vehicle ranges have been identified, and the impact of various cost scenarios has been analyzed. The most influencing factors on TCO have been identified, and a sensitivity analysis has been carried out. The numerical tool developed, and the methodology adopted allows the definition of the domains in which one solution prevails over the others in terms of vehicle range, fuel, and electricity cost.</div></div>

This paper explores the implementation of the Building To Vehicle To Building (V2B2) scheme in European Countries, by evaluating the influence of weather conditions and local energy market prices on its energy and economic performance. The use of electric vehicles as energy vectors among buildings belonging to a virtual cluster is the key aspect of the V2B2 scheme: by exploiting mobile electric storage devices, renewable electricity produced by building integrated PV panels is shared among diverse users and consumed off-site. This novel energy management scheme has a twofold aim: i) promoting energy flexibility and efficiency in multiple buildings by improving the share of self-consumed renewable electricity at a cluster level and ii) reducing the interaction with the power grid. The proposed cluster includes two buildings, a house and an office space, and an electric vehicle, and it can be considered as the basic nucleus of human linked energy users. The energy and economic performance of the proposed V2B2 scheme highly depends on weather conditions and purchasing/selling electricity price. Therefore, to assess the impact of weather and energy prices on the system energy and economic performance, a comprehensive parametric analysis is conducted by varying the main design and operating parameters of the capacity of the key components of the investigated energy cluster, such as of buildings integrating PV panels and electric storage devices. The modelled and simulated scenarios refer to two different layouts simulated in several European cities, selected to consider different weather conditions and national electricity market prices. To identify the optimal V2B2 configurations, several energy and economic indicators of each simulated scenario are compared to a conventional reference one in which the novel energy management scheme is not implemented. Through the proposed V2B2 scheme, encouraging energy savings, from a minimum of 13.6% to a maximum of 71.2%, and economic outcomes are achieved.

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Ever since 2002, when the first Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES) was held in Dubrovnik, the SDEWES conferences series has been providing a forum for world-wide scientists and those interested in learning about the sustainability of development, to present research progress and to discuss the state of the art, the future directions and priorities in the various areas of sustainable development. One of the main issues of the coming decades is to improve efficiencies by integrating various energy systems, using excess from one, as resource in another in the correct moment. Integrating electricity, heating, cooling, transport, water, buildings, waste, wastewater, industry, forestry and agriculture systems will be pivotal towards sustainable development. SDEWES has maintained high publishing standard as 2408 SDEWES papers were published in special issues of leading scientific journals including “Energy - The International Journal”. In 2022, the 17th SDEWES Conference was held during November 6–10 in Paphos, Cyprus, the 5th SEE Conference took place in May 22–26, 2022 in Vlorë, Albania, the 3rd Latin American Conference was held through a virtual platform during July 24–28, 2022. The Energy journal has continued its cooperation with SDEWES launching a special issue dedicated to the 2022 Conferences. The special issue includes papers which traditionally cover a range of energy issues - higher renewables penetration and various technologies and fuels assessments at energy supply side, as well as, energy efficiency in various sectors, buildings, district heating, electric vehicles and demand modelling at energy demand side.

Abstract Most of small islands around the world today, are dependent on imported fossil fuels for the majority of their energy needs especially for transport activities and electricity production. The use of locally renewable energy resources and the implementation of energy efficiency measures could make a significant contribution to their economic development by reducing fossil fuel imports. An electrification of vehicles has been suggested as a way to both reduce pollutant emissions and increase security of supply of the transportation sector by reducing the dependence on oil products imports and facilitate the accommodation of renewable electricity generation, such as wind and, in the case of volcanic islands like Sao Miguel (Azores) of the geothermal energy whose penetration has been limited by the valley electricity consumption level. In this research, three scenarios of EV penetration were studied and it was verified that, for a 15% LD fleet replacement by EVs with 90% of all energy needs occurring during the night, the accommodation of 10 MW of new geothermal capacity becomes viable. Under this scenario, reductions of 8% in electricity costs, 14% in energy, 23% in fossil fuels use and CO2 emissions for the transportation and electricity production sectors could be expected.

Abstract This paper presents seasonal variations of the wind characteristics and wind turbine characteristics in the regions around Elazig, namely Maden, Agin and Keban. Mean wind speed data in measured hourly time series format is statistically analyzed for the six year period 1998–2003. The probability density distributions are derived from the time series data and their distributional parameters are identified. Two probability density functions are fitted to the measured probability distributions on a seasonal basis. The wind energy characteristics of all the regions is studied based on the Weibull and Rayleigh distributions. Energy calculations and capacity factors for the wind turbine characteristics were determined for wind machines of different sizes between 300 and 2300 kW. It was found that Maden is the best region, among the regions analyzed, for wind characteristics and wind turbine characteristics.

Abstract This article evaluates the methods to characterise the behaviour of lithium ion cells of several chemistries and a nickel metal hydride cell for automotive applications like (plug-in) hybrid vehicles and battery electric vehicles. Although existing characterisation test methods are used, it was also indicated to combine test methods in order to speed up the test time and to create an improved comparability of the test results. Also, the existing capacity tests ignore that cells can be charged at several current rates. However, this is of interest for, e.g. fast charging and regenerative braking. Tests for high power and high energy application have been integrated in the enhanced method. The article explains the rationale to ameliorate the test methods. The test plan should make it possible to make an initial division in a group of cells purchased from several suppliers.