Monte Carlo modelling for domestic car use patterns in United Kingdom

Sikai Huang, David Infield

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

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.

LanguageEnglish
Title of host publication2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages68-73
Number of pages6
ISBN (Print)9781479967292
DOIs
Publication statusPublished - 15 Oct 2015
Event3rd International Conference on Connected Vehicles and Expo, ICCVE 2014 - Vienna, Austria
Duration: 3 Nov 20147 Nov 2014

Conference

Conference3rd International Conference on Connected Vehicles and Expo, ICCVE 2014
CountryAustria
CityVienna
Period3/11/147/11/14

Fingerprint

electric vehicle
Railroad cars
Electric vehicles
statistics
Statistics
simulation
distribution system
simulation model
Internal combustion engines
uncertainty
Probability distributions
methodology
time
Monte Carlo simulation

Keywords

  • electric vehicle
  • Monte Carlo modelling
  • vehicle data

Cite this

Huang, S., & Infield, D. (2015). Monte Carlo modelling for domestic car use patterns in United Kingdom. In 2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings (pp. 68-73). [7297635] Piscataway, NJ.: IEEE. https://doi.org/10.1109/ICCVE.2014.7297635
Huang, Sikai ; Infield, David. / Monte Carlo modelling for domestic car use patterns in United Kingdom. 2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings. Piscataway, NJ. : IEEE, 2015. pp. 68-73
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Huang, S & Infield, D 2015, Monte Carlo modelling for domestic car use patterns in United Kingdom. in 2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings., 7297635, IEEE, Piscataway, NJ., pp. 68-73, 3rd International Conference on Connected Vehicles and Expo, ICCVE 2014, Vienna, Austria, 3/11/14. https://doi.org/10.1109/ICCVE.2014.7297635

Monte Carlo modelling for domestic car use patterns in United Kingdom. / Huang, Sikai; Infield, David.

2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings. Piscataway, NJ. : IEEE, 2015. p. 68-73 7297635.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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PY - 2015/10/15

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N2 - 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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Huang S, Infield D. Monte Carlo modelling for domestic car use patterns in United Kingdom. In 2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings. Piscataway, NJ.: IEEE. 2015. p. 68-73. 7297635 https://doi.org/10.1109/ICCVE.2014.7297635