Electric vehicles (EVs) are emerging as the future of transportation systems aimed at reducing greenhouse gas emissions and fossil fuel dependence in the transportation sector. The deepening penetration of Plug-in EVs (PEVs) forecasted for the incoming years could cause significant strain on distribution networks (DNs), as well as the need to address the growing energy demand. In order to limit the negative drawbacks associated with PEVs energy demand and to properly address related issues, in the paper we consider an energy-packet based (EPB) scheduling approach for PEVs charging, comparing its performance with a conventional charging approach. We formulate an optimization framework in order to reduce the overall peak power demand and to maximize fully charged PEVs during their declared parking time. We compare the performance among the scheduling approaches by running simulations on a real DN and using real vehicle parking data.
Performance comparison between scheduling strategies for PEVs charging in smart grids
GRABER, GIUSEPPE;MASSA, GIOVANNI;GALDI, Vincenzo;CALDERARO, Vito;PICCOLO, Antonio
2015-01-01
Abstract
Electric vehicles (EVs) are emerging as the future of transportation systems aimed at reducing greenhouse gas emissions and fossil fuel dependence in the transportation sector. The deepening penetration of Plug-in EVs (PEVs) forecasted for the incoming years could cause significant strain on distribution networks (DNs), as well as the need to address the growing energy demand. In order to limit the negative drawbacks associated with PEVs energy demand and to properly address related issues, in the paper we consider an energy-packet based (EPB) scheduling approach for PEVs charging, comparing its performance with a conventional charging approach. We formulate an optimization framework in order to reduce the overall peak power demand and to maximize fully charged PEVs during their declared parking time. We compare the performance among the scheduling approaches by running simulations on a real DN and using real vehicle parking data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.