Modelo dinámico de gestión inteligente de carga de vehículos eléctricos en micro-redes mediante un modelo estocástico orientado a la calidad del producto eléctrico

Abstract

An intelligent electric vehicle (EV) charging management model is developed and applied to an islanded microgrid based on an-IEEE 15-bus benchmark system of 13.2 kV, aiming to preserve power quality, particularly the voltage profile and total harmonic distortion (THD), under increasing EV penetration. The proposed approach explicitly considers the stochastic nature of EV arrival and departure times, as well as the variability of distributed renewable generation. The microgrid integrates photovoltaic and wind generation, a battery energy storage system (BESS), diesel generation, and residential, commercial, and industrial loads. Different EV penetration levels (10%, 30%, 50%, and 70%) are evaluated by comparing scenarios with and without intelligent charging management. The strategy is formulated as a stochastic optimization problem with CVaR-based penalties, allowing probabilistic limitation of voltage and THD violations. Results show that, in unmanaged scenarios, simultaneous EV charging causes demand peaks, voltage drops below 0.95 p.u., and increased THD. In contrast, the proposed model redistributes EV demand toward off- peak periods, reduces power peaks, improves the nodal voltage profile, and maintains THD within acceptable limits, demonstrating its effectiveness for EV integration in islanded microgrids without requiring physical network reinforcements.