Smart Charging: System Design and Implementation for Interaction Between Plug-in Electric Vehicles and the Power Grid

Abousleiman, Rami; Scholer, Richard A.

doi:10.1109/tte.2015.2426571

Cited by 62 publications

(25 citation statements)

References 24 publications

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“…To mitigate the influences, various types of intelligent control strategies have been proposed in the literature. In [4], a smart charging system is designed and implemented that allows the direct interaction between the EVs and power grid. The purpose of the smart charging system is to minimize the charging cost of EVs and prevent damage caused by the excessive loads.…”

Section: Introductionmentioning

confidence: 99%

“…In [6], different priority criteria such as battery state of charge, slack time, and their fairness index are integrated and compared to integrate EV smoothly and efficiently into the distribution network. It is noted that those studies [4]- [6] focus on EV intelligent control strategies design either on the distribution system level or at the household level. However, the FO who will play important role in the near future, is not considered in the studies.…”

Section: Introductionmentioning

confidence: 99%

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Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles’ Management System

Lind

et al. 2016

IEEE Trans. Transp. Electrific.

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Abstract-In this paper, a hierarchical management system is proposed to integrate electric vehicles (EVs) into a distribution grid. Three types of actors are included in the system: Distribution system operators (DSOs), Fleet operators (FOs) and EV owners. In contrast to a typical hierarchical control system where the upper level controller directly controls the lower level subordinated nodes, this study aims to integrate two common indirect control methods:market-based control and price-based control into the hierarchical electric vehicles management system. Specifically, on the lower level of the hierarchy, the FOs coordinate the charging behaviors of their EV users using a price-based control method. A parametric utility model is used on the lower level to characterize price elasticity of electric vehicles and thus used by the FO to coordinate the individual EV charging. On the upper level of the hierarchy, the distribution system operator uses the market-based control strategy to coordinate the limited power capacity of power transformer with fleet operators. To facilitate the application of the two indirect control methods into the system, a model describing decision tasks in control is used to specify the essential functions that are needed in the control system. The simulations illustrate the effectiveness of the proposed solutions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles’ Management System

Lind

et al. 2016

IEEE Trans. Transp. Electrific.

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“…SG supports a fundamental platform for the interactions between power systems and EV users [24]. The EV can be directly charged through power grids.…”

Section: Electric Vehiclementioning

confidence: 99%

Unit commitment in achieving low carbon smart grid environment with virtual power plant

Hua

Sun

et al. 2017

2017 International Smart Cities Conference (ISC2)

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Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract-This paper proposes a novel unit commitment (UC) model under smart grid (SG) environment, which intends to strike a balance pursuing minimum carbon emissions for policy maker, minimum costs for generators and minimum payment bills for consumers. This leads to a multiobjective optimization problem (MOP) which can be solved through the multiobjective immune algorithm (MOIA). Therefore, the energy market scheduling problem considering low carbon smart grid environment can be analysed. The case studies are conducted to demonstrate the proposed model and present the allocation of power generations as well as the daily energy market scheduling results. It has been proved that the penetration of SG contributes to the mitigation of carbon emissions during the peak demand time by around 500 ton/h. It is also suggested that if the policy maker can provide appropriate monetary compensation for the deployment of SG technologies, generators will be encouraged to participate in the SG deployment.Index Terms-Smart grid (SG), unit commitment (UC), multiobjective optimization (MOP), virtual power plant (VPP), electric vehicle (EV), demand response (DR).

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“…When most people are at home, the demand increases; it decreases throughout the day when most people are at work. Figure 12 shows a typical home load for winter and summer days in the USA [27]. This load is significantly affected by the behavior of the people.…”

Section: Home Loadmentioning

confidence: 99%

Modelling of a Residential Solar Energy Recuperation System Setup

Alghassab¹,

Zohdy²

2016

OJEE

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Increased pollution levels have caused damage to our planet. Many scientists are now warning on the long term effects. Green houses gases causes more of the sunlight to be trapped within the Earth's atmosphere and thus causing increased Earth temperature. Individuals, governments, and private entities are now acting on fixing this problem. One of the most promising solutions is installing an array of solar cells in residential areas. Doing so makes sense for areas with abundant sunlight as the dependency on the grid can be minimized and even completely illuminated while providing a feasible economic perspective at the same time. This paper presents the modelling of a residential setup as a complete system along with an electric vehicle. The modelled components include: Photovoltaic Cells, Home Load Usage, Electric Vehicle, High-Voltage battery as an energy storage, Boost, and Inverter. The presented analysis will help engineers and system designers do better cost analysis. The study can also be used as a basis for maximizing the solar energy usage and perform component optimization.

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Smart Charging: System Design and Implementation for Interaction Between Plug-in Electric Vehicles and the Power Grid

Cited by 62 publications

References 24 publications

Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles’ Management System

Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles’ Management System

Unit commitment in achieving low carbon smart grid environment with virtual power plant

Modelling of a Residential Solar Energy Recuperation System Setup

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