The increased use of Electric Vehicles (EVs) in industrial environments (e.g., battery-powered forklifts) requires proper design of the grid architecture. The shift towards the use of Renewable Energy Sources (RES) and the need for efficient energy use are leading to promising solutions with Photovoltaic (PV) sources, Energy Storage Systems (ESSs), and small power electronic converters. However, the sizing of the facility power system, including the source nominal power and the capacity of the ESS, requires careful consideration of various parameters. In this work, we present a novel approach to define the most suitable grid architecture based on behavioral PLECS modeling and validated through tests carried out on a reduced-scale system; the model considers the number of EVs, initial investment costs, Power Grid (PG) consumption costs, CO2 footprint, and EVs working time specifications. Through simulations, the optimum capacity of the PV and ESS installations can be determined by considering economic, technological, or environmental aspects.
Designing Power Systems to Charge Electrical Vehicle Fleets in the Industrial Environment / Nkembi, A. A.; Simonazzi, M.; Santoro, D.; Cova, P.; Menozzi, R.; Delmonte, N.. - ELETTRONICO. - 1005 LNEE:(2023), pp. 211-217. [10.1007/978-3-031-26066-7_33]
Designing Power Systems to Charge Electrical Vehicle Fleets in the Industrial Environment
Nkembi A. A.;Simonazzi M.;Santoro D.
;Cova P.;Menozzi R.;Delmonte N.
2023-01-01
Abstract
The increased use of Electric Vehicles (EVs) in industrial environments (e.g., battery-powered forklifts) requires proper design of the grid architecture. The shift towards the use of Renewable Energy Sources (RES) and the need for efficient energy use are leading to promising solutions with Photovoltaic (PV) sources, Energy Storage Systems (ESSs), and small power electronic converters. However, the sizing of the facility power system, including the source nominal power and the capacity of the ESS, requires careful consideration of various parameters. In this work, we present a novel approach to define the most suitable grid architecture based on behavioral PLECS modeling and validated through tests carried out on a reduced-scale system; the model considers the number of EVs, initial investment costs, Power Grid (PG) consumption costs, CO2 footprint, and EVs working time specifications. Through simulations, the optimum capacity of the PV and ESS installations can be determined by considering economic, technological, or environmental aspects.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
