2021
DOI: 10.3390/en14206697
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A Simplified Approach to Estimate EV Charging Demand in Urban Area: An Italian Case Study

Abstract: The development and the diffusion of the electromobility is crucial for reducing air pollution and increase sustainable transport. In particular, electrification of private mobility has a significantly role in the energy transition within urban areas, since the progressive substitution of conventional passenger cars by electric vehicles (EVs) leads to the decarbonisation of transport sector without direct emissions. However, increasing EV penetration in the market forces an expansion of the existing charging i… Show more

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Cited by 10 publications
(3 citation statements)
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“…This is a very important factor influencing the range of electric vehicles, which is one of the most discussed problems in EV research [30][31][32]. On the other hand, large-scale implementation of charging facilities influences the increase in energy consumption as noticed for instance by Lazzeroni et al [33]. This may lead to creation of new supply systems, preferably based on renewable energy, as proposed by Badea et al [34].…”
Section: Literature Reviewmentioning
confidence: 99%
“…This is a very important factor influencing the range of electric vehicles, which is one of the most discussed problems in EV research [30][31][32]. On the other hand, large-scale implementation of charging facilities influences the increase in energy consumption as noticed for instance by Lazzeroni et al [33]. This may lead to creation of new supply systems, preferably based on renewable energy, as proposed by Badea et al [34].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Classically, EV charging demand can be evaluated through driving patterns or traffic flows analysis (Feng et al, 2020). These approaches include the use of the Origin-Destination (OD) matrix to study how EV flows and the driving paths are distributed around a city (ElBanhawy et al, 2014), considering the charging behaviour of the users (Fu et al, 2020;Chen et al, 2020) and different range anxiety (Lazzeroni et al, 2021). The latter use Floating Car Data to identify mobility habits, particularly parking patterns, to estimate energy demand for EVs.…”
Section: Introductionmentioning
confidence: 99%
“…ELECTROMO BILITY (GUIDO et al, 2019), (AFONSO et al, 2020), (GRYPARIS et al, 2020), (KESTER et al, 2020), (WRÓBLEWSKI; LEWICKI, 2021), (IWAN et al, 2021), (LAZZERONI et al, 2021), (WOŁEK; JAGIEYYO; NSKI, 2021), (FERNANDEZ, 2021), (TURO; KUBIK; CHEN, 2021b), (FARIA et al, 2021), (WAHID et al, 2021), (BOOYSEN et al, 2022), (SIERRA et al, 2020).…”
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