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: 10.4121/5627f587-e98b-4d61-a814-926fa33eef2d

Piao, Longjian; de Vries, Laurens; de Weerdt, Mathijs; Yorke-Smith, Neil (2025): Simulation model for the publication: "Exposing a Locational Energy Market to Uncertainty". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/5627f587-e98b-4d61-a814-926fa33eef2d.v1

Categories

• Artificial Intelligence and Image Processing
• Energy Storage, Distribution and Supply
• Economics
• Energy
• Information and Computing Sciences

Keywords

agent-based model DC distribution system electricity market design Pecan Street prosumers Python

Licence

CC BY-NC-SA 4.0

Interoperability

• RO-Crate Metadata

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by Longjian Piao, Laurens de Vries , Mathijs de Weerdt , Neil Yorke-Smith

Simulation model written in Python, corresponding to the submitted article: "Exposing a Locational Energy Market to Uncertainty" This is an agent-based simulation of a local DC network with prosumers.

History

• 2025-09-01 first online, published, posted

Publisher

4TU.ResearchData

Format

script/.py

References

• https://doi.org/10.4233/uuid:55f24f9e-7ce3-4864-89dd-2a4a514a642b

Funding

• TAILOR (grant code 952215) European Union
• ERA-Net Smart Grids Plus (grant code 646039) European Union

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science;
TU Delft, Faculty of Technology, Policy and Management