Scenario generation for electric vehicles' uncertain behavior in a smart city environment

João Soares, Nuno Borges, Mohammad Ali Fotouhi Ghazvini, Zita Vale and P.B. de Moura Oliveira

Energy, 2016, vol. 111, issue C, 664-675

Abstract: This paper presents a framework and methods to estimate electric vehicles' possible states, regarding their demand, location and grid connection periods. The proposed methods use the Monte Carlo simulation to estimate the probability of occurrence for each state and a fuzzy logic probabilistic approach to characterize the uncertainty of electric vehicles' demand. Day-ahead and hour-ahead methodologies are proposed to support the smart grids' operational decisions. A numerical example is presented using an electric vehicles fleet in a smart city environment to obtain each electric vehicle possible states regarding their grid location.

Keywords: Big data; Electric vehicles; Fuzzy logic; Monte carlo simulation; Smart city (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:111:y:2016:i:c:p:664-675

DOI: 10.1016/j.energy.2016.06.011

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