Vehicle Energy Consumption in Python: A tool to simulate load flexibility of electric vehicle fleets.
Project description
Welcome to venco.py!
- Authors: Niklas Wulff, Fabia Miorelli
- Contact: vencopy@dlr.de
Contents
Description
A data processing tool estimating hourly electric demand and flexibility profiles for future electric vehicle fleets. Profiles are targeted to be scalable for the use in large-scale energy system models.
Installation
Depending on if you want to use venco.py or if you want to contribute, there are two different installation procedures described in venco.py's documentation:
I want to contribute to the codebase, the documentation or the tutorials
In order to start using venco.py, check out our tutorials. For this you won't need any additional data.
To run venco.py in full mode, you will need the data set Mobilität in Deutschland (German for mobility in Germany). You can request it here from the clearingboard transport: https://daten.clearingstelle-verkehr.de/order-form.html Alternatively you can use venco.py with any National Travel Survey or mobility pattern dataset.
Codestyle
We use PEP-8, with the exception of UpperCamelCase for class names.
Documentation
The documentation can be found here: https://dlr-ve.gitlab.io/esy/vencopy/vencopy/ To build the documentation from a conda bash with an activated environment type:
sphinx-build -b html ./docs/ ./build/
Useful Links
- Documentation: https://dlr-ve.gitlab.io/esy/vencopy/vencopy/
- Source code: https://gitlab.com/dlr-ve/vencopy
- PyPI release: https://pypi.org/project/vencopy/
- Licence: https://opensource.org/licenses/BSD-3-Clause
Want to contribute?
Great, welcome on the venco.py team! Please read our contribute section in the documentation and reach out to Niklas (niklas.wulff@dlr.de). If you experience difficulties on set up or have other technical questions, join our gitter community
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