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Modelling electric vehicle use and charging behaviour

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Title: Modelling electric vehicle use and charging behaviour
Authors: Daina, Nicolo
Item Type: Thesis or dissertation
Abstract: This thesis explores the role of consumers’ choices into the integration of mobility and power systems. It will contribute to the wider literature of electric vehicles-power systems integration by explicitly accounting for consumers’ preferences in shaping charging demand. This objective is achieved by developing a methodology to investigate electric vehicles (EV) charging choices in technological scenarios that enable smart charging operations. A modelling framework for the joint analysis of EV charging and activity-travel behaviour is introduced. This is based on an extension of traditional activity scheduling models that embeds the charging choice dimensions: namely the available energy after charging (that is related to the driving range) and the charging duration (defined here as the time elapsed from arrival at a charging facility until the desired battery level is achieved). This framework accommodates the interaction between charging behaviour and travel/activity behaviour, and allows us to capture the potential effects of charging service pricing and charging demand management policies on charging choices as well as along the timing dimension of travel/activity choices. A stated response survey instrument for estimating a tour-based operational version of the model is developed. Results from this empirical study provide insights into the value placed by individuals on the main attributes of the charging choice. The trade-offs between target battery levels and schedule delays potentially induced by long durations of the charging operation are also analysed. The model is then implemented into a micro-simulation framework to demonstrate the model applicability for modelling electric vehicle charging demand. The specific application shows the compatibility of charging choices under various electricity pricing scenarios with electric vehicle load flexibility – an essential requirement to enable smart charging operations.
Content Version: Open Access
Issue Date: May-2014
Date Awarded: Sep-2014
URI: http://hdl.handle.net/10044/1/25018
DOI: https://doi.org/10.25560/25018
Supervisor: Sivakumar, Aruna
Polak, John
Sponsor/Funder: Imperial College London
Department: Civil and Environmental Engineering
Publisher: Imperial College London
Qualification Level: Doctoral
Qualification Name: Doctor of Philosophy (PhD)
Appears in Collections:Civil and Environmental Engineering PhD theses

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