Highlights
- •The global electric vehicle (EV) stock is expected to reach 125 million by 2030.
- •Smart charging is required for the efficient integration of EVs into power grids.
- •datafev is an open-source Python library to develop and test EV charging strategies.
- •datafev provides reference algorithms, simulation, and scenario generation routines.
Abstract
Keywords
Current code version | v1.0.0 |
Permanent link to code/repository used for this code version | https://github.com/SoftwareImpacts/SIMPAC-2022-309 |
Code Ocean compute capsule | |
Legal Code License | MIT |
Code versioning system used | git |
Software code languages, tools, and services used | Python 3 |
Compilation requirements, operating environments & dependencies | datafev can be used independently of the hardware. The Python site-package requirements are numpy, pandas, matplotlib, pyomo, and openpyxl. Additionally, a mathematical programming solver, which is supported by the pyomo optimization modeling library, is required. |
If available Link to developer documentation/manual | https://datafev.fein-aachen.org |
Support email for questions | mailto:[email protected] |
1. Introduction
2. Software architecture and functionalities
datafev in Python Package Index - PyPI URL https://pypi.org/project/datafev/1.0.0/.
3. Impact
- Gümrükcü Erdem
- Ponci Ferdinanda
- Monti Antonello
- Guidi Giuseppe
- D’Arco Salvatore
- Suul Jon Are
4. Illustrative example



CRediT authorship contribution statement
Declaration of Competing Interest

Acknowledgments
References
datafev in Python Package Index - PyPI URL https://pypi.org/project/datafev/1.0.0/.
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- Pandapower—An open-source python tool for convenient modeling, analysis, and optimization of electric power systems.IEEE Trans. Power Syst. 2018; 33: 6510-6521https://doi.org/10.1109/TPWRS.2018.2829021
Tomo Takahashi, Shigeru Tamura, Day-Ahead Planning for EV Aggregators Based on Statistical Analysis of Road Traffic Data in Japan, in: 2020 International Conference on Smart Grids and Energy Systems, SGES, 2020, pp. 117–122.
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- Optimal Management for Megawatt Level Electric Vehicle Charging Stations with a Grid Interface Based on Modular Multilevel Converter.IEEE Access. 2021; : 1https://doi.org/10.1109/ACCESS.2021.3137544
- Decentralized energy management concept for urban charging hubs with multiple V2G aggregators.IEEE Trans. Transp. Electr. 2022; : 1https://doi.org/10.1109/TTE.2022.3208627
- Results report for the project MoMeWEC.SINTEF Report. 2022;
- FuChar – Grid and charging infrastructure of the future.2021 (URL https://Www.Sintef.No/Projectweb/Fuchar/)
- FLOW – Flexible energy systems Leveraging the Optimal integration of EVs deployment Wave.2021 (URL https://cordis.europa.eu/project/id/101056730)
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