Analysis of electric vehicle charge scheduling and effects on electricity demand costs

Jewell, Nicholas; Bai, Lihui; Naber, John; McIntyre, Michael L.

doi:10.1007/s12667-013-0114-0

Cited by 18 publications

(7 citation statements)

References 16 publications

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“…Simulated annealing (SA) is proposed in [109] to schedule the EVs charging and in [110] to schedule the charge and discharge process, including the AC power flow constraints. One of the main disadvantages of SA is its dependency of the initial solution.…”

Section: Heuristic and Meta-heuristic Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects

Hu¹,

Morais²,

Sousa

et al. 2016

Renewable and Sustainable Energy Reviews

370

197

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a b s t r a c tElectric vehicles can become integral parts of a smart grid, since they are capable of providing valuable services to power systems other than just consuming power. On the transmission system level, electric vehicles are regarded as an important means of balancing the intermittent renewable energy resources such as wind power. This is because electric vehicles can be used to absorb the energy during the period of high electricity penetration and feed the electricity back into the grid when the demand is high or in situations of insufficient electricity generation. However, on the distribution system level, the extra loads created by the increasing number of electric vehicles may have adverse impacts on grid. These factors bring new challenges to the power system operators. To coordinate the interests and solve the conflicts, electric vehicle fleet operators are proposed both by academics and industries. This paper presents a review and classification of methods for smart charging (including power to vehicle and vehicle-to-grid) of electric vehicles for fleet operators. The study firstly presents service relationships between fleet operators and other four actors in smart grids; then, modeling of battery dynamics and driving patterns of electric vehicles, charging and communications standards are introduced; after that, three control strategies and their commonly used algorithms are described; finally, conclusion and recommendations are made.

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Section: Heuristic and Meta-heuristic Algorithmsmentioning

confidence: 99%

“…Heuristic and meta-heuristic optimization used in: [86,[100][101][102][103][104][105][106][107][108][109][110][111][112].…”

Section: ) Start-up and Shut-down Costsmentioning

confidence: 99%

Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects

Hu¹,

Morais²,

Sousa

et al. 2016

Renewable and Sustainable Energy Reviews

370

197

View full text Add to dashboard Cite

show abstract

“…Workplaces may also offer slow charging with a paid-for membership card. Some EV owners desire to charge their EVs while at work in addition to domestic charging [20]. However, studies show that the vast majority of current users rely on domestic charging [9,33].…”

Section: Private and Public Charging Infrastructurementioning

confidence: 99%

Harvesting green miles from my roof

Bourgeois

Foell

Kortuem

et al. 2015

Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

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Electric vehicles are an increasingly attractive option for households to reduce carbon emissions, especially when they are powered by renewable energy. In this paper we report the results of an 18-month field trial investigating the desirability and feasibility of powering electric vehicles (EVs) with domestic solar electricity. Based on extensive collection of data from 7 households including over 75,000 miles of daily EV use, home electricity consumption and generation, and in-depth interviews with householders we develop a detailed understanding of what drives EV decisions in households, quantify to what extent our participating households currently power their EVs with solar electricity, and investigate how feasible the vision of "self-sustaining electric mobility" is. We use this understanding to draw implications for future research into supporting emerging practices of EV drivers.

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“…By scheduling charging jobs, the total time it takes to charge all vehicles can be minimized in the event that there are more vehicles to charge than there are charging stations available. This can be the case if there is limited EVSE charging infrastructure installed at the point of charging, or if chargers must be shut off or disabled during peak demand periods [65]. Scheduling charging activity also provides a fair charging experience for all PHEV owners in that cars with higher SOC can be disabled or delayed if there is another vehicle plugged in that has a lower SOC.…”

Section: A Overview Of Major System Componentsmentioning

confidence: 99%

“…A scheduling solution was presented in [65] that can be implemented to minimize the total processing time required. The following is a summary of the findings [65].…”

Section: Review Of Machine Schedulingmentioning

confidence: 99%

Development of a power monitoring and control system to provide demand side management of electric vehicle charging activity.

Jewell¹

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Analysis of electric vehicle charge scheduling and effects on electricity demand costs

Cited by 18 publications

References 16 publications

Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects

Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects

Harvesting green miles from my roof

Development of a power monitoring and control system to provide demand side management of electric vehicle charging activity.

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