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
What's in it
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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