Inhomogeneous Markov Models for Describing Driving Patterns

Jan Emil Banning Iversen, Jan Kloppenborg Møller, Juan Miguel Morales González, Henrik Madsen

Research output: Book/ReportReportResearch

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Abstract

It has been predicted that electric vehicles will play a crucial role in incorporating a large renewable component in the energy sector. If electric vehicles are integrated in a naive way, they may exacerbate issues related to peak demand and transmission capacity limits while not reducing polluting emissions.
Optimizing the charging of electric vehicles is paramount for their successful integration. This paper presents a model to describe the driving patterns of electric vehicles, in order to provide primary input information to any mathematical programming model for optimal charging. Specically, an inhomogeneous Markov model that captures the diurnal variation in the use of a vehicle is presented. The model is dened by the time-varying probabilities of starting and ending a trip and is justied due to the uncertainty associated with the use of the vehicle. The model is tted to data collected from the actual utilization of a vehicle. Inhomogeneous Markov models imply a large number of parameters. The number of parameters in the proposed model is reduced using B-splines.
Original languageEnglish
Place of PublicationKongens Lyngby
PublisherTechnical University of Denmark
Number of pages18
Publication statusPublished - 2013
SeriesD T U Compute. Technical Report
Number2013-02
ISSN1601-2321

Keywords

  • Driving patterns
  • Inhomogeneous markov chain
  • B-splines
  • Electric vehicles

Cite this

Iversen, J. E. B., Møller, J. K., Morales González, J. M., & Madsen, H. (2013). Inhomogeneous Markov Models for Describing Driving Patterns. Kongens Lyngby: Technical University of Denmark. D T U Compute. Technical Report, No. 2013-02
Iversen, Jan Emil Banning ; Møller, Jan Kloppenborg ; Morales González, Juan Miguel ; Madsen, Henrik. / Inhomogeneous Markov Models for Describing Driving Patterns. Kongens Lyngby : Technical University of Denmark, 2013. 18 p. (D T U Compute. Technical Report; No. 2013-02).
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Iversen, JEB, Møller, JK, Morales González, JM & Madsen, H 2013, Inhomogeneous Markov Models for Describing Driving Patterns. D T U Compute. Technical Report, no. 2013-02, Technical University of Denmark, Kongens Lyngby.

Inhomogeneous Markov Models for Describing Driving Patterns. / Iversen, Jan Emil Banning; Møller, Jan Kloppenborg; Morales González, Juan Miguel; Madsen, Henrik.

Kongens Lyngby : Technical University of Denmark, 2013. 18 p. (D T U Compute. Technical Report; No. 2013-02).

Research output: Book/ReportReportResearch

TY - RPRT

T1 - Inhomogeneous Markov Models for Describing Driving Patterns

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AU - Morales González, Juan Miguel

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AB - It has been predicted that electric vehicles will play a crucial role in incorporating a large renewable component in the energy sector. If electric vehicles are integrated in a naive way, they may exacerbate issues related to peak demand and transmission capacity limits while not reducing polluting emissions.Optimizing the charging of electric vehicles is paramount for their successful integration. This paper presents a model to describe the driving patterns of electric vehicles, in order to provide primary input information to any mathematical programming model for optimal charging. Specically, an inhomogeneous Markov model that captures the diurnal variation in the use of a vehicle is presented. The model is dened by the time-varying probabilities of starting and ending a trip and is justied due to the uncertainty associated with the use of the vehicle. The model is tted to data collected from the actual utilization of a vehicle. Inhomogeneous Markov models imply a large number of parameters. The number of parameters in the proposed model is reduced using B-splines.

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Iversen JEB, Møller JK, Morales González JM, Madsen H. Inhomogeneous Markov Models for Describing Driving Patterns. Kongens Lyngby: Technical University of Denmark, 2013. 18 p. (D T U Compute. Technical Report; No. 2013-02).