The diffusion of electric vehicles is undoubtedly the problem of power distribution networks. It becomes therefore essential to have the tools that allow to measure the impact of EV penetration on distribution networks. This work deals with studying the impact of charging electric vehicles, imagining a distribution not only temporal, but also spatial. In fact, the proposed approach tries to take into account the movement of vehicles during a time interval. Depending on the distance traveled, the EV battery reaches a certain level of charge and therefore the EV may need to recharge at the next stop. The impact on the electrical demand of the substations is then estimated by combining the time-varying electrical load with the EV fleet charging behavior based on these geographically spread charging stations. Because of the stochastic nature of the problem, the analysis is based on Monte Carlo simulation to calculate reliability indexes for the power substations.

A model to estimate the impact of electrical vehicles displacement on medium voltage network

Gruosso, Giambattista
2019-01-01

Abstract

The diffusion of electric vehicles is undoubtedly the problem of power distribution networks. It becomes therefore essential to have the tools that allow to measure the impact of EV penetration on distribution networks. This work deals with studying the impact of charging electric vehicles, imagining a distribution not only temporal, but also spatial. In fact, the proposed approach tries to take into account the movement of vehicles during a time interval. Depending on the distance traveled, the EV battery reaches a certain level of charge and therefore the EV may need to recharge at the next stop. The impact on the electrical demand of the substations is then estimated by combining the time-varying electrical load with the EV fleet charging behavior based on these geographically spread charging stations. Because of the stochastic nature of the problem, the analysis is based on Monte Carlo simulation to calculate reliability indexes for the power substations.
2019
Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
9781509066841
Electric Vehicle; Load profile; Monte Carlo simulation; Reliability; Energy Engineering and Power Technology; Electrical and Electronic Engineering; Industrial and Manufacturing Engineering; Control and Optimization
File in questo prodotto:
File Dimensione Formato  
08591563.pdf

Accesso riservato

: Publisher’s version
Dimensione 352.53 kB
Formato Adobe PDF
352.53 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1088388
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 3
social impact