In, an interactive charging management system for EV charging is investigated, guaranteeing EV users’ preferences. This work considers reducing the excessive waiting time for EV users however, even if this waiting time is minimal, it can negatively impact on the EV user experience, and this work only considers the case of a charging station. In, a charging methodology is presented that jointly optimizes pricing, scheduling, and admission control of an EV charging station, based on a multi-sub-process admission control scheme. Only a few works have considered the EV users’ preferences in their methodologies. In, a decentralized charging control is studied, where a load aggregator optimizes the charging of a plug-in EV fleet, considering price-based signals. These methodologies are useful to minimize charging costs, but users’ preferences are not significantly considered, which can create a barrier for users to adopt EVs.
For this purpose, the development of a suitable charging management system is required to address different stakeholders’ needs in the electro-mobility value chain, supporting the integration of RES (Renewable Energy Sources) and thus reshaping of the power demand curve.Ī charging problem as a Markov decision process has been modeled in to reduce the charging costs however, the approach does not consider the participation of an EV aggregator, which can interact with the transmission and distribution system operators considering their technical constraints. Smart interactions among the smart grid, aggregators, and EVs can bring various benefits to all parties involved, e.g., improved reliability and safety for the smart gird, increased profits for the aggregators, as well as enhanced self-benefit for EV customers. Leaving the charging process uncontrolled could hinder some of the present challenges in the power system, such as peak power demand at certain times. Electric Vehicles (EVs) will play a highly important role in the future Smart Cities, having different charging strategies that could adapt to the users’ needs, being a flexibility resource for market actors and system operators. Therefore, today’s focus is on the electrification of transportation, which is essential for the reduction of CO 2 emissions. Over the last 25 years, European rules have promoted the reduction of pollutants emissions through careful guidance of vehicles’ manufacturers. Nowadays, the European Union (EU) is combating climate change through interventions in the transportation sector, as it is by far the biggest harmful gas emitter accounting for more than 70% of all GHG emissions from transport in 2014. Finally, the deployment and testing results are presented. The architecture and the web applications of TwinEV module are analyzed. The methodology of the SCT tool, as well as the supportive optimization algorithm, are explained thoroughly. This module is based on a Smart Charging Tool (SCT), aiming to deliver a more user-central and cooperative approach to the EV charging processes. This paper focuses on the design of such a system, the TwinEV module, that offers high-value services to electric vehicles (EV) users. The development of a suitable charging management system is required to address different stakeholders’ needs in the electro-mobility value chain.
According to the literature, leaving the charging process uncontrolled could hinder some of the present challenges in the power system. The capabilities of EVs are many and vary since they can provide valuable system flexibility services, including management of congestion in transmission grids. E-mobility is a key element in the future energy systems.
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