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Data, code and results behind the journal article "Electric Vehicles as Mobile Flexibility Resources: Alleviating Grid Congestion with Location-Aware Vehicle-to-Grid" (under review). Alvaro Menendez-Agudin , Pavol Bauer Gautham Ram Chandra Mouli

4TU.ResearchDatavia 4TU.ResearchData (via DataCite) · bijgewerkt 23 oktober 2026

Wat erin zit

This dataset supports a simulation study on whether location-aware V2G can alleviate congestion in distribution grids. Three strategies of increasing spatial flexibility (stationary V2G, locational V2G and relocation V2G by a fleet operator guided by congestion prices) are compared on two SimBench medium-voltage grids (one urban, one semi-urban) for a summer and a winter day, using a mixed-integer linear programme coupled to an AC power flow (pandapower). The impact on residential feeders is then assessed on SimBench low-voltage grids using two coordination schemes: MV top-down, where the MV solution is imposed and refined iteratively, and LV bottom-up, where each LV grid optimises its own EVs against a blended congestion price. The dataset contains scenario parameters, station definitions and instructions to obtain the (not redistributed) SimBench grids, synthetic EV mobility chains, the Python code of the MV and LV models and plotting scripts, and the results of 12 MV scenarios plus 144 LV runs with summary tables and figures.

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