Department of Electrical Engineering, Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP023), Higher Technical School of Engineering of Algeciras (ETSIA), University of Cádiz, Algeciras, Cádiz, Spain
Department of Electrical Engineering, Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP023), Higher Technical School of Engineering of Algeciras (ETSIA), University of Cádiz, Algeciras, Cádiz, Spain
Department of Engineering in Automation, Electronics and Computer Architecture & Networks, Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP023), University of Cádiz, Higher Technical School of Engineering of Algeciras (ETSIA), Algeciras, Cádiz, Spain
Juan P. Torreglosa
Electrical Engineering Department, University of Huelva, Huelva, Spain
Department of Electrical Engineering, Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP023), Higher Technical School of Engineering of Algeciras (ETSIA), University of Cádiz, Algeciras, Cádiz, Spain
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.
