RT journal article
T1 Model Predictive Control-Based Optimized Operation of a Hybrid Charging Station for Electric Vehicles
A1 González Rivera, Enrique
A1 García Triviño, Pablo
A1 Sarrias Mena, Raúl
A1 Torreglosa, Juan P.
A1 Jurado, Francisco
A1 Fernández Ramírez, Luis Miguel
A2 Ingeniería Eléctrica
A2 Ingeniería en AutomáticaElectrónica, Arquitectura y Redes de Computadores
K1 Charging station
K1 electric vehicles
K1 energy management system
K1 model predictive control
K1 Z-source converters
AB This paper presents an energy management system (EMS) based on a novel approach using model predictive control (MPC) for the optimized operation of power sources in a hybrid charging station for electric vehicles (EVs). The hybrid charging station is composed of a photovoltaic (PV) system, a battery, a complete hydrogen system based on a fuel cell (FC), electrolyzer (EZ), and tank as an energy storage system (ESS), grid connection, and six fast charging units, all of which are connected to a common MVDC bus through Z-source converters (ZSC). The MPC-based EMS is designed to control the power flow among the energy sources of the hybrid charging station and reduce the utilization costs of the ESS and the dependency on the grid. The viability of the EMS was proved under a long-term simulation of 25 years in Simulink, using real data for the sun irradiance and a European load profile for EVs. Furthermore, this EMS is compared with a simpler alternative that is used as a benchmark, which pursues the same objectives, although using a states-based strategy. The results prove the suitability of the EMS, achieving a lower utilization cost (-25.3%), a notable reduction in grid use (-60% approximately) and an improvement in efficiency.
PB IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
SN 2169-3536
YR 2021
FD 2021
LK http://hdl.handle.net/10498/25756
UL http://hdl.handle.net/10498/25756
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-may-2026