Probabilistic analysis to assess the impact of the charge of electric vehicles on distribution grids under normal operation

Abstract

The incorporation of high levels of small-scale non-dispatchable distributed generation is leading to the transition from the traditional 'vertical' power system structure to a 'horizontally-operated' power system, where the distribution networks contain both stochastic generation and load (such as electric vehicles recharging). This fact increases the number of stochastic inputs and dependence structures between them need to be considered. The deterministic analysis is not enough to cope with these issues and a new approach is needed. Probabilistic analysis provides a better approach. This PhD thesis describes the grid impact analysis of charging electric vehicles (EV) using charging curves with detailed battery modelling. A probabilistic method using Monte Carlo was applied to a typical Spanish distribution grid, also using mobility patterns of Barcelona. To carry out this analysis, firstly, an IEEE test system was adapted to a typical distribution grid configuration; secondly, the EV and its battery types were modeled taking into account the current vehicle market and the battery characteristics; and, finally, the recharge control strategies were taken in account. Once these main features were established, a statistical probabilistic model for the household electrical demand and for the EV charging parameters was determined. With these probabilistic models, the Monte Carlo analysis was performed within the established scenario in order to study the lines' and the transformers' loading levels. The results show that an accurate model for the battery gives a more precise estimation about the impact on the grid. Additionally, mobility patterns have been proved to be some of the most important key aspects for these type of studies.