A coordinated Framework for Optimized Charging of EV Fleet in Smart Grid

Usman, Muhammad; Knapen, Luk; Yasar, Ansar-Ul-Haque; Vanrompay, Yves; Bellemans, Tom; Janssens, Davy; Wets, Geert

doi:10.1016/j.procs.2016.08.049

Cited by 27 publications

(10 citation statements)

References 7 publications

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“…As the number of vehicles available at one location will be large, the impact on the electrical grid and associated charging cost for the fleet manager will also be significant. Several researchers have already published algorithms that can optimize the charging strategy of the fleet to include charging cost and the distribution grid impact [82][83][84]. These strategic algorithms also include the power balancing impact on the EV battery as well as state-of-charge management.…”

Section: Fleet Optimizationmentioning

confidence: 99%

Social and Technological Impact of Businesses Surrounding Electric Vehicles

Vidhi

Shrivastava

Parikh³

2021

Clean Technol.

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Electric vehicle (EV) penetration has been increasing globally and is expected to continue its exponential growth over the coming decades. Several countries have already announced plans to achieve total or partial electrification of their vehicle fleets. Such rapid transportation electrification will have a significant impact on society and businesses that support the transportation industry. Additionally, new business opportunities will be available to support this technological evolution. In this paper, the business opportunities emerging from EVs and their supporting infrastructure are reviewed. It has been observed that several businesses, such as sustainable mining and manufacturing, will need to be developed before EV growth as they provide the initial platform required for EV adoption. Other businesses such as fleet optimization, battery management, and recycling can be developed at a later stage. All of these businesses will also have social and technological impacts, which will drive policy decisions. Regional governments play a critical role in ensuring the smooth execution of a transition to transportation electrification through social programs, such as training and education for equitable growth, and legislative decisions, such as technology standardization.

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Section: Fleet Optimizationmentioning

confidence: 99%

Social and Technological Impact of Businesses Surrounding Electric Vehicles

Vidhi

Shrivastava

Parikh³

2021

Clean Technol.

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“…Then, the aggregator collects this information and calculates when each PHEV can start charging. Usman et al, proposed an automated coordinated control of EV fleets, which can plan the charging strategy at the cheaper moments and keep the vehicle charged enough to complete its scheduled trips [116]. Islam and Mithulananthan proposed a method that utilizes the measured PV output of a given sample and the supplied historical ramp to predict the PV output of the next immediate sample based on a non-iterative method [47].…”

Section: Coordinated Controlsmentioning

confidence: 99%

A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS)

et al. 2020

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The deployment of solar photovoltaics (PV) and electric vehicles (EVs) is continuously increasing during urban energy transition. With the increasing deployment of energy storage, the development of the energy sharing concept and the associated advanced controls, the conventional solar mobility model (i.e., solar-to-vehicles (S2V), using solar energy in a different location) and context are becoming less compatible and limited for future scenarios. For instance, energy sharing within a building cluster enables buildings to share surplus PV power generation with other buildings of insufficient PV power generation, thereby improving the overall PV power utilization and reducing the grid power dependence. However, such energy sharing techniques are not considered in the conventional solar mobility models, which limits the potential for performance improvements. Therefore, this study conducts a systematic review of solar mobility-related studies as well as the newly developed energy concepts and techniques. Based on the review, this study extends the conventional solar mobility scope from S2V to solar-to-buildings, vehicles and storage (S2BVS). A detailed modeling of each sub-system in the S2BVS model and related advanced controls are presented, and the research gaps that need future investigation for promoting solar mobility are identified. The aim is to provide an up-to-date review of the existing studies related to solar mobility to decision makers, so as to help enhance solar power utilization, reduce buildings’ and EVs’ dependence and impacts on the power grid, as well as carbon emissions.

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“…Electric cars are subdivided into the categories small, medium, large similar to what is done in [32]. In order to estimate the energy requirement, one needs to know the contribution of each one of those categories to the complete vehicle set similar to what is done in [33] [34] [35]. Belgian government statistics provide a classification of internal combustion engine (ICE) vehicles based on the motor cylinder volume: they provide a distribution of the registered cars using that classification.…”

Section: Electric Vehicle Categoriesmentioning

confidence: 99%

Optimal recharging framework and simulation for electric vehicle fleet

Usman

Knapen

Yasar

et al. 2020

Future Generation Computer Systems

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Electrical vehicles are considered sustainable transport alternatives as compared to conventional combustion engine vehicles due to their lower energy consumption and less pollutants production. The increased penetration of electric vehicles in the market depends upon technology to overcome the driving range barrier. That can be achieved by significantly planning the use of available charging stations. In this paper, a planning simulation model is presented which evaluates the feasibility of electric vehicles driving range when recharging is considered at home, at work or at quick charging stations in Flanders, Belgium. The proposed procedure plans a charging strategy for each electric vehicle so that entire scheduled tours of the individual can be executed successfully. The simulation starts by activating an agent for each electric vehicle that takes the daily schedule of the driver, registered charging requests at each charging station, and devises a charging strategy that may or may not require a detour to a charging station. Detouring to a charging station causes the time loss that result in the utility drop due to decreased participation in the planned activities. The charging station that leads to the minimum detour travel time, waiting time and recharging time is selected to minimize the time loss. The simulation uses a realistic travel demand predicted by an activity-based model. The results show the percentage of the population that can drive electric vehicle with charging only at home and/or work location; it also shows those who need a stop for recharging at a charging station. The results indicate the use of all charging stations over the day and also the waiting time as function of charging points at each charging station.

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A coordinated Framework for Optimized Charging of EV Fleet in Smart Grid

Cited by 27 publications

References 7 publications

Social and Technological Impact of Businesses Surrounding Electric Vehicles

Social and Technological Impact of Businesses Surrounding Electric Vehicles

A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS)

Optimal recharging framework and simulation for electric vehicle fleet

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