Electric Power Systems Research · 2020

Classification of electric vehicle charging time series with selective clustering

Chenxi Sun, Tongxin Li, Steven H. Low, Victor O. K. Li

Electric Power Systems Research

Read paper BibTeX

What battery behavior can be learned from imperfect charging records?

An iterative procedure extracts and clusters the tail portions of charging curves despite missing observations, variable lengths, scheduling effects, and measurement noise. Experiments on ACN data illustrate how these patterns can support useful charging models.

Research themes

Connections

Recovering structure from limited measurements

Graph recovery estimates electrical network parameters. Charging curve clustering and energy disaggregation recover useful structure from observed behavior and aggregate meter readings.

Cite this paper

Chenxi Sun, Tongxin Li, Steven H. Low, Victor O. K. Li. Classification of electric vehicle charging time series with selective clustering. Electric Power Systems Research, 2020. https://doi.org/10.1016/j.epsr.2020.106695

BibTeX
@article{tongxin-charging-clusters,
  title = {{Classification of electric vehicle charging time series with selective clustering}},
  author = {Chenxi Sun and Tongxin Li and Steven H. Low and Victor O. K. Li},
  year = {2020},
  journal = {Electric Power Systems Research},
  url = {https://doi.org/10.1016/j.epsr.2020.106695},
  doi = {10.1016/j.epsr.2020.106695}
}