Electric vehicle aggregation model: a probabilistic approach in representing flexibility

Research output: Contribution to conferencePaperpeer-review

26 Downloads (Pure)


With the increased roll-out of electric vehicles (EV), the need, but also opportunity, for leveraging their flexibility in the context of grid support, ancillary services and local market energy trading. However, the uncertainty and variability in driving patterns and resultant charging profiles pose substantial risk for aggregators. Given this context, the paper demonstrates a method for producing a stochastic, socio-economically-differentiated aggregation model that determines the flexibility space of a realistic and diverse EV fleet. A probabilistic Monte Carlo Markov Chain model is developed that allows for the overlay and comparison of different technical, spatial and social-economic behavioural factors through clustering and correlation analyses. In turn, the model enables a statistically significant analysis of the 'Energy Space' available that captures the inherit risk and uncertainty when leveraging EV flexibility.
Original languageEnglish
Number of pages8
Publication statusPublished - 1 Jul 2022
EventXXII Power Systems Computation Conference 2022 - INESC TEC, Porto, Portugal
Duration: 27 Jun 20221 Jul 2022


ConferenceXXII Power Systems Computation Conference 2022
Abbreviated titlePSCC 2022


  • aggregation
  • behavioural models
  • electric vehicle
  • Markov Chain Monte Carlo (MCMC)
  • probabilistic model


Dive into the research topics of 'Electric vehicle aggregation model: a probabilistic approach in representing flexibility'. Together they form a unique fingerprint.

Cite this