Simulated results: Agent-based model of short-term and long-term allocation of electric vehicle charging resources in Netlogo

DOI:10.4121/62183ba0-cd85-4289-8369-f254226baac7.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/62183ba0-cd85-4289-8369-f254226baac7

Datacite citation style

van der Koogh, Mylene; Lukszo, Zofia; Chappin, Emile J.L.; Heller, Renee (2024): Simulated results: Agent-based model of short-term and long-term allocation of electric vehicle charging resources in Netlogo . Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/62183ba0-cd85-4289-8369-f254226baac7.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

The allocation of charging resources was simulated with three roll-out strategies to prioritize new charging infrastructure in 9 neighborhoods. The goal was to determine how different strategies affect the allocation of chargers, the grid capacity and the occurence of spillover behavior in charging.

This dataset contains the results of the simulations of the agent-based model (see https://data.4tu.nl/datasets/50c0329b-e9e2-4b52-ba4d-51657311f1b6 for model).


The following files are available:

revcid_nieuw experiment_anticipatory_24_4_25Runs-stats.csv 

revcid_nieuw experiment_demand_24_4_25Runs-stats.csv

revcid_nieuw experiment_equity_24_4_25Runs-spreadsheet.csv 


Each file contains the output parameter for each neighborhoods during one of the three strategies. The simulations were made for 10 years in time, and each strategy was simulated 25 times (in 25 runs). The CSV output contains the output parameters on a neighborhood level. The first two letters of the parameter name are identifiers for the neighborhood.


History

  • 2024-07-22 first online, published, posted

Publisher

4TU.ResearchData

Format

CSV output files

Funding

  • Future Charging (grant code RAAK.PRO03.128) [more info...] NWO

Organizations

TU Delft, Faculty of Technology, Policy and Management, Department of Engineering, Systems and Services
Amsterdam University of Applied Sciences, Faculty of Technology, Energy & Innovation

DATA

Files (4)