Modelling electric vehicles use : a survey on the methods
Daina, Nicolò and Sivakumar, Aruna and Polak, John W. (2017) Modelling electric vehicles use : a survey on the methods. Renewable and Sustainable Energy Reviews, 68 (Part 1). pp. 447-460. ISSN 1879-0690 (https://doi.org/10.1016/j.rser.2016.10.005)
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Abstract
In the literature electric vehicle use is modelled using of a variety of approaches in power systems, energy and environmental analyses as well as in travel demand analysis. This paper provides a systematic review of these diverse approaches using a twofold classification of electric vehicle use representation, based on the time scale and on substantive differences in the modelling techniques. For time of day analysis of demand we identify activity-based modelling (ABM) as the most attractive because it provides a framework amenable for integrated cross-sector analyses, required for the emerging integration of the transport and electricity network. However, we find that the current examples of implementation of AMB simulation tools for EV-grid interaction analyses have substantial limitations. Amongst the most critical there is the lack of realism how charging behaviour is represented.
ORCID iDs
Daina, Nicolò ORCID: https://orcid.org/0000-0002-5902-4651, Sivakumar, Aruna and Polak, John W.;-
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Item type: Article ID code: 77781 Dates: DateEvent1 February 2017Published18 October 2016Published Online4 October 2016AcceptedNotes: Funding Information: This work was partially supported by the Grantham institute for Climate Change at Imperial College , the UK Engineering and Physical Sciences Research Council under awards EP/L001039/1 and EP/I038837/1 . The authors would like to thank Dr. Dimitrios Papadaskalopoulos for its insightful comments on the manuscript. Publisher Copyright: © 2016 The Authors Subjects: Social Sciences
Technology > Motor vehicles. Aeronautics. AstronauticsDepartment: Faculty of Humanities and Social Sciences (HaSS) > Government and Public Policy > Politics Depositing user: Pure Administrator Date deposited: 16 Sep 2021 07:56 Last modified: 21 Nov 2024 01:20 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/77781