Robust and Predictive Charging of Large Electric Vehicle Fleets in Grid Constrained Parking Lots

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Abstract

Grid congestion forms an obstacle for the adoption of electric vehicles (EVs) by companies for their sustainability goals. This paper presents a robust approach to smart charging of large fleets of EVs that only utilizes currently available technologies and data, such that it can be applied in practice. The method relies only on available data at charge point operators. The presented approach uses offline aggregated planning to determine a robust fill-level. Subsequently, this fill-level is used in online control to maximise the quality of service to users while being able to provide flexibility to the energy system. Simulation results using real data show that the self-consumption of PV energy can be improved from 72.0% to 85.4%. Furthermore, the energy not served is reduced from 5.9% to 2.8%.
Original languageEnglish
Title of host publication2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9781665455541
ISBN (Print)978-1-6654-5557-2
DOIs
Publication statusPublished - 6 Dec 2023
Event2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) - University of Strathclyde, Glasgow, United Kingdom
Duration: 31 Oct 20233 Nov 2023

Conference

Conference2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
Country/TerritoryUnited Kingdom
CityGlasgow
Period31/10/233/11/23

Keywords

  • Computers
  • Simulation
  • Quality of service
  • Companies
  • Electric vehicles
  • Smart grids
  • Planning

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