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Techno-economic comparison of grid reinforcement and battery-buffered electric vehicle fast charging stations

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Abstract

Connecting fast charging stations to the electric grid usually requires an upgrade with new transformer stations and cables to accommodate the higher loading. Battery-based solutions can be operated following different control objectives and support the grid to reduce the investment need in conventional assets. A grid planning algorithm is developed to perform this comparison.
The impact of the rollout of distributed energy resources on a Danish urban grid is assessed, based on a forecasted scenario and the geographical distribution of new loads and generators until 2045. Fast charging stations are added to this rollout, and the resulting grid issues are mitigated using a conventional grid reinforcement method. In a second iteration, batteries are installed in combination with fast charging stations to support them. The remaining capacity is used to solve the previously mentioned grid issues, using controllers that achieve good performance. The technical and economic impact of the conventional grid reinforcement and the battery-based one are compared in a cost–benefit analysis. Depending on cost sensitivities, the battery-based alternative can range from being 40 % cheaper to over 1400 % more expensive than a conventional grid extension—despite potential investment deferrals, which are often outweighed by higher capital costs and energy losses. Across all battery connection topologies and price sensitivities, the conventional grid upgrade solution remains the most cost-efficient one in 89 % of all investigated cases, with the battery-buffered one being only competitive in edge cases.
Original languageEnglish
Article number101789
JournalSustainable Energy, Grids and Networks
Volume43
Number of pages14
ISSN2352-4677
DOIs
Publication statusPublished - 2025

Keywords

  • Electric vehicles
  • Fast charging
  • Grid planning
  • Distribution networks
  • Batteries
  • Distributed energy services
  • Battery sizing optimisation

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