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Data, code and results behind the journal article: "Integrating Vehicle to Grid into Shared Electric Vehicle Relocation under Locational Congestion Prices" (under review). Alvaro Menendez Agudin, Cas Oudijk, Pavol Bauer, Gautham Ram Chandra Mouli

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

Wat erin zit

This dataset supports a simulation-based optimisation study on how V2G and location- and time-dependent congestion prices can be integrated into the operation of a one-way, station-based shared EV fleet. A mixed-integer linear programme jointly schedules vehicle relocation, charging and V2G over one day (48 steps of 30 minutes) for a fleet of 50 EVs serving 271 trips of 75 users across 10 stations (residential, workplace and city-centre). Five strategies (private EVs, shared EVs, V2G, congestion-price V2G and peak minimisation) are compared for a summer and a winter day. The dataset contains station-level price, load, PV, congestion-price and grid-limit series (based on MFFBAS and ENTSO-E data, with congestion prices modelled after GOPACS), inter-station distances and trip demand derived from synthetic weekly trip chains, the Python/Pyomo code, and the outputs of the 10 scenarios with summary files for cost and peak comparison.

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