Travel activity based stochastic modelling of load and charging state of electric vehicles

Muhammad Naveed Iqbal*, Lauri Kütt, Matti Lehtonen, Robert John Millar, Verner Püvi, Anton Rassõlkin, Galina L. Demidova

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

22 Citations (Scopus)
52 Downloads (Pure)


The uptake of electric vehicles (EV) is increasing every year and will eventually replace the traditional transport system in the near future. This imminent increase is urging stakeholders to plan up-gradation in the electric power system infrastructure. However, for efficient planning to support an additional load, an accurate assessment of the electric vehicle load and power quality indices is required. Although several EV models to estimate the charging profile and additional electrical load are available, but they are not capable of providing a high-resolution evaluation of charging current, especially at a higher frequency. This paper presents a probabilistic approach capable of estimating the time-dependent charging and harmonic currents for the future EV load. The model is based on the detailed travel activities of the existing car owners reported in the travel survey. The probability distribution functions of departure time, distance, arrival time, and time span are calculated. The charging profiles are based on the measurements of several EVs.

Original languageEnglish
Article number1550
Number of pages14
JournalSustainability (Switzerland)
Issue number3
Publication statusPublished - 2 Feb 2021
MoE publication typeA1 Journal article-refereed


  • Activity based modelling
  • EV charging current
  • EV load model
  • Managed charging
  • SOC
  • Unmanaged charging


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