venco.py

venco.py: A Python model to represent the charging flexibility and vehicle-to-grid potential of electric vehicles in energy system models - Published in JOSS (2025)

https://gitlab.com/dlr-ve/esy/vencopy/vencopy

Science Score: 89.0%

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Found 1 DOI reference(s) in JOSS metadata
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11 of 13 committers (84.6%) from academic institutions
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Published in Journal of Open Source Software

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Repository

A data processing tool offering demand and flexibility profiles for future electric vehicle fleets in an aggregated manner.

Basic Info

Host: gitlab.com
Owner: dlr-ve
License: bsd-3-clause
Default Branch: main

Statistics

Stars: 1
Forks: 1
Open Issues: 0
Releases: 0

Created over 2 years ago

https://gitlab.com/dlr-ve/esy/vencopy/vencopy/blob/main/

# Welcome to venco.py!

- Authors: Niklas Wulff, Fabia Miorelli
- Contact: vencopy@dlr.de

# Contents

- [Description](#description)
- [Installation](#installation)
- [Codestyle](#codestyle)
- [Documentation](#documentation)
- [Useful Links](#useful-links)
- [Want to contribute?](#want-to-contribute)

## 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 apply the tool](https://dlr-ve.gitlab.io/esy/vencopy/vencopy/gettingstarted/installation.html#installation-for-users)

[I want to contribute to the codebase, the documentation or the tutorials](https://dlr-ve.gitlab.io/esy/vencopy/vencopy/gettingstarted/installation.html#installation-for-developers)

In order to start using venco.py, check out our [tutorials](https://dlr-ve.gitlab.io/esy/vencopy/vencopy/gettingstarted/start.html). For this you won't need any additional data.

To run venco.py in full mode, you will need the data set Mobilitt 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 be able to build the documentation locally on your machine you should additionally install the following three packages in your vencopy environment : sphinx, sphinx_rtd_theme and rst2pdf.
After that you can build the documentation locally from a conda bash with the following command:

```python
sphinx-build -b html ./docs/ ./build/
```

## Useful Links

- Documentation: https://dlr-ve.gitlab.io/esy/vencopy/vencopy/
- Source code: https://gitlab.com/dlr-ve/esy/vencopy/vencopy
- PyPI release: https://pypi.org/project/vencopy/
- Licence: https://opensource.org/licenses/BSD-3-Clause

## Want to contribute?

Please read our contribute section in the documentation and reach out to Fabia
(fabia.miorelli@dlr.de). If you experience difficulties on set up or have other technical questions, join our
[gitter community](https://gitter.im/vencopy/community)

Owner

Name: dlr-ve
Login: dlr-ve
Kind: organization

Repositories: 11
Profile: https://gitlab.com/dlr-ve

JOSS Publication

venco.py: A Python model to represent the charging flexibility and vehicle-to-grid potential of electric vehicles in energy system models

Published

April 22, 2025

DOI

10.21105/joss.06896

Volume 10, Issue 108, Page 6896