evsim
Overview
evsim is part of a suite of packages to analyse, model and simulate
the charging behavior of electric vehicle users:
- evprof:
Electric Vehicle PROFiling
- evsim:
Electric Vehicle SIMulation
evsim package provides the functions for:
- Simulating new EV sessions based on Gaussian Mixture Models created
with package {evprof}
- Calculating the power demand from a data set of EV sessions in a
specific time resolution
- Calculating the occupancy (number of vehicles connected) in a
specific time resolution
Usage
If you have your own data set of EV charging sessions or you have
already built your EV model with evprof, the best
place to start is the Get
started chapter in the package website.
Installation
You can install the package from CRAN or the latest development
version from GitHub:
# CRAN stable release
install.packages("evsim")
# install.packages("pak")
pak::pak("resourcefully-dev/evsim")
Getting help
If you encounter a clear bug, please open an issue with a minimal
reproducible example on GitHub.
For further technical details, you can read the following academic
articles about the methodology used in this paper:
- Increasing hosting capacity of low-voltage distribution
network using smart charging based on local and dynamic capacity
limits. Sustainable Energy, Grids and Networks, vol. 41.
Elsevier BV, p. 101626, March 2025. DOI link.
- Assessment of electric vehicle charging hub based on
stochastic models of user profiles. Expert Systems with
Applications (Vol. 227, p. 120318). Elsevier BV. May 2023. DOI link.
- Potential benefits of scheduling electric vehicle sessions
over limiting charging power. CIRED Porto Workshop 2022:
E-mobility and power distribution systems. Institution of Engineering
and Technology, 2022. DOI
link.
- Flexibility management of electric vehicles based on user
profiles: The Arnhem case study. International Journal of
Electrical Power and Energy Systems, vol. 133. Elsevier BV, p. 107195,
Dec. 2021. DOI
link.
- Electric vehicle user profiles for aggregated flexibility
planning. IEEE PES Innovative Smart Grid Technologies Europe
(ISGT Europe). IEEE, Oct. 18, 2021. DOI
link.
Acknowledgements
This work started under a PhD program in the the University of Girona
in collaboration with Resourcefully, the energy
transition consulting company that currently supports the development
and maintenance.