Abstract
The growing trend in electrical vehicle (EV) deployment has transformed independent power network and transportation network studies into highly congested interdependent network performance evaluations assessing their impact on power and transportation systems. Electrified transportation is highly capable of intensifying the interdependent correlations across charging service, transportation, and power networks. However, the evaluation of the complex coupled relationship across charging services, transportation, and power networks poses several challenges, including an impact on charging scheduling, traffic congestion, charging loads on the power grid, and high costs. Therefore, this article presents comparative survey analytics of large-scale EV integration’s impact on charging service network scheduling, transportation networks, and power networks. Moreover, price mechanism strategies to determine the charging fares, minimize investment profits, diminish traffic congestion, and reduce power distribution constraints under the influence of various factors were carried out. Additionally, the survey analysis stipulates the interdependent network performance index, ascertaining travel distance, route selection, long-term and short-term planning, and different infrastructure strategies. Finally, the limitations of the proposed study, potential research trends, and critical technologies are demonstrated for future inquiries.
Highlights
Electrical vehicles (EVs) are widely considered the most promising source of distributed energy in developed countries due to an increasing trend in climate change, with economic and political concerns.There were more than five million fleet electrical vehicle (EV) in 2018, which are expected to represent 57% of global car sales by 2040 [1]
Various electric electric vehicle vehicle vehicle charging studies consider only a few factors to determine a traffic flow prediction model, charging charging studies studies consider consider only only aa few few factors factors to to determine determine aa traffic traffic flow flow prediction prediction model, model, which which may may which may result in reduced flexibility and prediction accuracy
This study revealed that a hybrid pricing scheme is effective unless it compromises driver privacy
Summary
Electrical vehicles (EVs) are widely considered the most promising source of distributed energy in developed countries due to an increasing trend in climate change, with economic and political concerns.There were more than five million fleet EVs in 2018, which are expected to represent 57% of global car sales by 2040 [1]. Electrical vehicles (EVs) are widely considered the most promising source of distributed energy in developed countries due to an increasing trend in climate change, with economic and political concerns. Governments and private organizations around the world are intensively exploring to reduce greenhouse emissions from their operations with a robust initiative to expand the electric vehicle market and release market incentives to achieve their goals [2]. The prevalence of electric vehicles is due to their exceptional advantages over traditional vehicles: they are environmentally friendly, meet individual travel demands, and support vehicle-to-grid (V2G) programs as distributed load mobility in transportation networks. Despite numerous advantages, the integration of highly congested interdependent networks may introduce several new challenges to electrified transportation from charging scheduling, traffic flow, charging load on power network, and cost perspectives. The deployment on the large scale of Energies 2020, 13, 3371; doi:10.3390/en13133371 www.mdpi.com/journal/energies
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