Modelagem e Análise de Estações de Recarga Rápida considerando uma estrutura de Microrredes e Padrões Estocásticos

  • Matheus S. da Cruz Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Santa Maria, RS
  • Caroline B. F. Darui Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Santa Maria, RS
  • Leonardo Nogueira F. da Silva Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Santa Maria, RS
  • Tiago G. Lucca Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Santa Maria, RS
  • Nelson Knak Neto Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Santa Maria, RS
  • Alzenira da Rosa Abaide Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Santa Maria, RS
Keywords: Fast-Charging Stations, Microgrids, Electric Vehicles, Photovoltaics, Wind Power, Energy Storage Systems

Abstract

One of the actions to reduce Greenhouse Emissions is the decarbonization of the transport sector. Among the alternatives for it, there are Electric Vehicles (EV). However, to increase the EV penetration, mainly in large countries, like Brazil or the US, it is necessary the development of Public Charging Infrastructure, such as Fast-Charging Stations (FCS) on Highways, to handle long-distance trips without long-charging times. The high powers that FCSs demands encourage the use of distributed resources, such as Photovoltaic and Wind Power, and Energy Storage Systems, characterizing microgrids. However, the random nature of the elements that make up the microgrids is a challenge for the characterization of load profiles that demonstrate the temporal behavior of FCS. In this context, this article presents a methodology for modeling FCS, considering stochastic models to characterize the load profiles of these microgrids, allowing for the expansion of the scenario numbers, which makes the analysis more comprehensive. From the models obtained, the need for models that consider stochastic patterns for expansion planning is evident.
Published
2022-11-30
Section
Articles