Open AccessOptimised operation of power sources of a PV/battery/hydrogen‐powered hybrid charging station for electric and fuel cell vehicles
Author(s) -
GarcíaTriviño Pablo,
Torreglosa Juan P.,
Jurado Francisco,
Fernández Ramírez Luis M.
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2019.0766
Subject(s) - automotive engineering , battery (electricity) , photovoltaic system , particle swarm optimization , energy storage , computer science , grid connection , energy management , power (physics) , cost reduction , electric power system , reliability engineering , engineering , electrical engineering , energy (signal processing) , algorithm , statistics , physics , mathematics , quantum mechanics , management , economics
This study presents a new energy management system (EMS) for the optimised operation of power sources of a hybrid charging station for electric vehicles and fuel cell vehicles. It is composed of a photovoltaic (PV) system, a battery and a hydrogen system as energy storage systems (ESSs), a grid connection, six fast charging units and a hydrogen supplier. The proposed EMS is designed to reduce the utilisation costs of the ESS and make them work, as much as possible, around their maximum efficiency points. The optimisation function depends on a cost prediction system that calculates the net present cost of the components from their previous performance and a fuzzy logic system designed for improving their efficiency. Finally, a particle swarm optimisation algorithm is used to solve the optimisation function and obtain the required power for each ESS. The proposed EMS is checked under Simulink environment for long‐term simulations (25 years). By comparing the EMS with a simpler one that optimises only the costs, it is proved that the proposed EMS achieves better efficiency of the charging station (+7.35%) and a notable reduction in the loss of power supply probability (−57.32%) without compromising excessively its average utilisation cost (+1.81%).