Monte Carlo modelling for domestic car use patterns in United Kingdom

Huang, Sikai and Infield, David; (2015) Monte Carlo modelling for domestic car use patterns in United Kingdom. In: 2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings. IEEE, AUT, pp. 68-73. ISBN 9781479967292 (https://doi.org/10.1109/ICCVE.2014.7297635)

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Abstract

For the purposes of quantifying the potential impact of widespread electric vehicles charging on the UK's power distribution system, it is essential to obtain relevant statistical data on domestic vehicle usage. Since electric vehicle ownership is presently very limited, these data will inevitably be for conventional internal combustion engine vehicles, and in particular privately owned vehicles. This should not be an issue since the limited journey distances that will dealt with in this work could as easily be undertaken by an electric vehicle as a conventional vehicle. Particular attention is paid to the United Kingdom 2000 Time Use Survey as it contains detailed and valuable statistical information about household car use. This database has been analyzed to obtain detailed car use statistics, such as departure and arrival time, individual journey time, etc. This statistical information is then used to build up two Monte Carlo simulation models in order to reproduce weekday car driving patterns based on these probability distributions. The Monte Carlo methodology is a well-known technique for solving uncertainty problems. In this paper, key statistics of domestic car use are presented together with two different Monte Carlo simulation approaches the simulation results that have been analyzed to verify the results being consistent with the statistics extracted from the TUS data.

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  Item type:	Book Section
  ID code:	57637
  Dates:	Date Event 15 October 2015 Published 11 September 2014 Accepted
  Notes:	© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering
  Depositing user:	Pure Administrator
  Date deposited:	01 Sep 2016 10:58
  Last modified:	11 Nov 2024 15:04
  Related URLs:	Scopus publication Journal or Publication Event
  URI:	https://strathprints.strath.ac.uk/id/eprint/57637