2015
DOI: 10.3390/en8054160
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Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks

Abstract: Electric Vehicles (EVs) have seen significant growth in sales recently and it is not clear how power systems will support the charging of a great number of vehicles. This paper proposes a methodology which allows the aggregated EV charging demand to be determined. The methodology applied to obtain the model is based on an agent-based approach to calculate the EV charging demand in a certain area. This model simulates each EV driver to consider its EV model characteristics, mobility needs, and charging processe… Show more

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Cited by 83 publications
(45 citation statements)
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References 58 publications
(100 reference statements)
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“…These total costs include stations-construction cost, waiting time cost, and refueling cost. Olivella-Rosell et al [56] propose an agent-based simulation approach that allows forecasting the EV charging demand in a certain urban area, and they successfully test the efficiency of their model in the city of Barcelona, Spain.…”
Section: Capacity Of Recharging Stationsmentioning
confidence: 99%
“…These total costs include stations-construction cost, waiting time cost, and refueling cost. Olivella-Rosell et al [56] propose an agent-based simulation approach that allows forecasting the EV charging demand in a certain urban area, and they successfully test the efficiency of their model in the city of Barcelona, Spain.…”
Section: Capacity Of Recharging Stationsmentioning
confidence: 99%
“…A concept of real-time scheduling techniques for EV charging that minimises the impact on the power grid and guarantees the satisfaction of consumer's charging requirements is suggested by Kang, Duncan, and Mavris (2013). Other studies related to the controlled EV charging problems can be found in Olivella-Rosell et al (2015) and Chen et al (2015).…”
Section: Related Workmentioning
confidence: 97%
“…The agent-based approach consists of an EV type, battery and charging process, charging infrastructure, mobility, and society. Monte Carlo techniques were used to define the charging demand and charging scenarios, which revealed voltage profiles reduction during peak demand charging and should be controlled for the condition of balanced and unbalanced loads [10][11][12]. Consequently, the PEVs can reduce the impact from charging mode at the same time or in the same power transmission line by using V2G technology and in combination with smart grid control [1,[13][14][15][16][17].…”
Section: Introductionmentioning
confidence: 99%