Developments in xEVs charging infrastructure and energy management system for smart microgrids including xEVs

Ahmad, Furkan; Alam, Mohammad Saad; Asaad, Mohammad

doi:10.1016/j.scs.2017.09.008

Cited by 104 publications

(40 citation statements)

References 90 publications

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“…After reaching the voltage level, called the float voltage, the current gradually begins to decrease. The charging current decreases in time because of the increasing battery internal resistance that stems from the increase in the charge [43]. This allows the charge to be completed with the leakage current, and in this way, the possibility of overcharging the battery is reduced.…”

Section: Charging Systems Of the Batteries Of Electrical Vehiclesmentioning

confidence: 99%

A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies

et al. 2019

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Electric vehicles are the latest form of technology developed to create an environmentally friendly transportation sector and act as an additional energy source to minimize the demand on the grid. This comprehensive research review presents the vehicle-to-grid (V2G) and the vehicle-to-home (V2H) technologies, along with their structures, components, power electronic topologies, communication standards, socket structure, and charging methods. In addition, the charging topologies in V2G and V2H are given in detail. This study is planned as a useful guide for future studies that can be achieved in that it compares the results obtained and analyzes the studies in the literature, finding the advantages and disadvantages of charging topologies in V2G and V2H.

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Section: Charging Systems Of the Batteries Of Electrical Vehiclesmentioning

confidence: 99%

A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies

et al. 2019

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“…Electric vehicle (EV) is a transport mean that emits zero direct greenhouse gas and produces minimal noise. Thus, the EV, whose powertrain depends on electric motors and battery storage [1], is considered to be one of the most effective ways to reduce oil dependence and greenhouse gas emissions [2,3]. EV deployment has been growing rapidly over the past ten years, with the global stock of electric passenger cars passing five million in 2018, an increase of 63% from the previous year [4].…”

Section: Introductionmentioning

confidence: 99%

Modelling, Simulation, and Management Strategy of an Electric Vehicle Charging Station Based on a DC Microgrid

2020

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The rapid development of electric vehicles (EVs) increases the power demand, which causes an extra burden on the public grid, increasing the load fluctuations and, therefore, hindering the high penetration of EVs. In this paper, a real-time rule-based algorithm for electric vehicle (EV) charging stations empowered by a direct current (DC) microgrid is proposed. Such a DC microgrid model consists of EVs, an electrochemical storage system, a public grid connection, and photovoltaic sources. The EV charging station model is based on data-driven modelling while its management model takes into account discrete events. This paper focuses on power management strategy of an EV charging station under power limitation and considers most of the drivers' choices. The EV charging system topology is presented and common problems during an EV charging process are discussed, e.g., disconnection operation, standby mode, shedding, and restoration operation. Furthermore, the proposed power management deals with the uncertainties of EV drivers' behavior considering arbitrary and random choices through the human-computer interface. The simulation results obtained under MATLAB/Simulink verify the feasibility of the proposed management strategy that presents a good performance in terms of precise control.Appl. Sci. 2020, 10, 2053 2 of 21 load profile. In Li, Q et al. [13], a max-weight EV dispatch algorithm is proposed to control the EV charging rates, which can optimally utilize the distribution system capacity, respecting to power system's physical limits. The author of [5] discussed three main charging patterns of EV drivers from observations on measured data and proposed a novel schedule strategy based on "valley filling" concept to manage EV charging behaviors in order to relieve its impact on the public grid. However, the proposed methods do not make EVs to downscale the total charging power absorbed from the public grid.Xu, Z et al. [14] proposed a three-level (provincial level, municipal level, and charging station level) EV charging strategy that jointly optimizes system load profile and charging costs while satisfying customer charging requirements, which reduces system peak demand charging costs. A robust energy management strategy for EV charging stations is proposed in [15]. It is based on randomized algorithms and determines a day-ahead upper bound profile on the power consumption of EV charging stations and strictly respected in real-time, guarantying the grid stability in a more efficient and less costly manner. However, no additional storage unit could be used to compensate for EV uncertainties.Although various charging strategies have been employed to design different EV charging protocols in existing work, the current research outcomes are still limited to the interactions and power transfer between EVs and the public grid. The distributed energy generation system has attracted wide attention because of its on-site power consumption, which improves the peak performance of the public grid without increasing the grid c...

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“…With an increase in the amount of EVs integrated into electric energy distribution systems, EV charging will give a negative impact on the original characteristics of electric energy consumption of load point . Due to the randomness of EV users’ travel and charging behaviors, EV charging shows stochastic nature both spatially and temporally, which will aggravate the degree of imbalance of electric energy consumption on three phases and increase the peak–valley difference of load curve in the electric energy distribution system.…”

Section: Introductionmentioning

confidence: 99%

A Real‐Time Multilevel Energy Management Strategy for Electric Vehicle Charging in a Smart Electric Energy Distribution System

He³

et al. 2019

Energy Tech

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The randomness of electric vehicle (EV) charging has negative impacts on three‐phase imbalance and peak–valley difference in electric energy distribution systems. Traditional EV charging strategies have shortcomings: the performance of three‐phase imbalance mitigation may be limited if the grid‐connected EVs are extremely imbalanced on three phases; in addition, the comprehensive regulation of peak–valley difference and three‐phase imbalance is not developed, and the three‐phase imbalance of reactive power is ignored. Therefore, a real‐time multilevel energy management strategy (RMEMS) for EV charging is proposed. A tri‐level optimization model (TOM) is designed as the central system. In upper‐level optimization, the three‐phase selection (TPS) of EVs is optimized to balance active or reactive power consumption on three phases. Based on the results from upper‐level optimization, the charging active power is regulated in middle‐level optimization to reduce the peak–valley difference on each phase. In lower‐level optimization, the reactive power compensated by EV chargers is optimized based on the results from upper‐level and middle‐level optimization to balance the reactive power on three phases. Case studies show that the proposed RMEMS performs well for balancing active and reactive power consumption on three phases, and the peak–valley differences of active power consumption on each phase are all mitigated.

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Developments in xEVs charging infrastructure and energy management system for smart microgrids including xEVs

Cited by 104 publications

References 90 publications

A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies

A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies

Modelling, Simulation, and Management Strategy of an Electric Vehicle Charging Station Based on a DC Microgrid

A Real‐Time Multilevel Energy Management Strategy for Electric Vehicle Charging in a Smart Electric Energy Distribution System

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