Fast Co-Simulation Methodology to Assess Electric Vehicle Penetration in Distribution Networks

Abstract

The study of the impact generated by a massive connection of electric vehicles in distribution networks requires modeling their connection behavior in different scenarios and considering their stochastic characteristics in annual periods and with short simulation steps. This implies a combinatorial explosion of case studies with a high computational cost. This article presents a methodology aimed at reducing the simulation time required to determine the hosting capacity (HC) of electric vehicles through the co-simulation of hardware and software. Monte Carlo methods and quasi-static time series (QSTS) simulation concepts are used to model the connection features of electric vehicles. The simulation and implementation are done using Matlab and OpenDSS software using parallel computing. The methodology is tested in the IEEE 123 node system observing the dependency of the HC indicator on the location and type of EV connection charger and the reduction of execution times.