Estrategia para la ubicación de estaciones de carga de EVs utilizando un flujo de carga probabilístico basado en bootstrapping

This work proposes a technique for placing electric vehicle charging stations using a bootstrapping-based probabilistic power flow. The methodology employs maximum likelihood estimation to model uncertainties in EV charging demand and establish robust confidence intervals for key system metrics. This approach was implemented in the Matpower simulation software within the IEEE-14 bus system, modeling the probabilistic load profile of 4500 EVs while considering 4000 realizations to obtain a wide spectrum of operation scenarios. The main results identified bus 9 as the optimal location for EV charging infrastructure, obtaining minimal active power losses (26.5 +/- 0.5 MW) and a maximum efficiency of 92.87 +/- 0.08 %. The strategic placement of charging stations is closely linked to the lowest active power losses, offering optimal efficiency. However, beyond an optimal placement, this paper aims to increase the robustness of modern grids, overcoming drawbacks related to the integration of electromobility infrastructure. The selection of the most representative features, combined with uncertainty analysis, contributes to an improved decision-making, emphasizing the need for supporting sustainable mobility.