ChaProEV
This repository contains the ChaProEV (Charging Profiles of Electric Vehicles) model.
Status
The ChaProEV model is under construction and not yet ready for use. Please contact the authors below if you have questions or requests to get model runs at some point.
Authors and contact
Omar Usmani (Omar.Usmani@TNO.nl)
Licence
ChaProEV is released under the Apache 2.0 license. All accompanying documentation and manual are released under the Creative Commons BY-SA 4.0 license.
Requirements
(See requirements.txt file for versions (corresponding to Python 3.11.1, which is the version used for developing and testing the model))
Installation and use
You can install ChaProEV with pip:
pip install ChaProEV
And then import ChaProEV in your code. You can of course use the various functions of ChaProEV, but the general use case is to run the model and focus on defining your case through the scenarios and their variants. In that case, the only piece of code you need is as follows (you just need to put the name of the folder where you put your case scenarios instead of the 'Mopo' example).
from ChaProEV import ChaProEV_run
if __name__ == '__main__':
case_name: str = 'Mopo'
ChaProEV_run.run_ChaProEV(case_name)
If you installed ChaProEV with pip, then the requirements should be installed as well (see requirements.txt file if you have issues or use the contact below). To run the model, you need to put a ChaProEV.toml configuration in the folder where you run your model. You also need to have at least one scenario in your scenario/case_name (e.g. scenario/Mopo) folder. A If you want to create varaints, then you need to add a case.toml (e.g. Mopo.toml) file in the variants folder and put a variant file in the variants/case (e.g. variants/Mopo) folder. If you want to compute fleet-level values and/or do a car owndriveway/street charging split, you need to put some files in the input/case (e.g. input/Mopo) folder. You can use the examples provided in this repository. You can also unzip this file into your working folder and use 'test_case' as your case name:
from ChaProEV import ChaProEV_run
if __name__ == '__main__':
case_name: str = 'test_case'
ChaProEV_run.run_ChaProEV(case_name)
For examples of running ChaProEV and more configuration files, you can visit the ChaProEV runs repository.
General approach and structure
- Split into scenarios, modules/computations, output profiles
- USer can define a case (series of scenarios) without having to do anything with the code. They just need to edit/add scenarios and variants.
Documentation
The docmentation can be found here
Context, goals, and future developments
Driver
The primary driver for the publication and development of ChaProEV in this repository is the participation in the Mopo project (funded from European Climate, Infrastructure and Environment Executive Agency under the European Union’s HORIZON Research and Innovation Actions under grant agreement N°101095998).
Goal
The main goal of providing this repository is transparency regarding the assumptions and computations of the ChaProEV model.
Uses outside Mopo
Prior to Mopo
-
Afspraken maken: Van data tot informatie Informatiebehoeften, datastandaarden en protocollen voor provinciale systeemstudies – Deel II technische rapportage. Nina Voulis, Joeri Vendrik, Reinier van der Veen, Alexander Wirtz, Michiel Haan, Charlotte von Meijenfeldt, Edwin Matthijssen, Sebastiaan Hers, Ewoud Werkman (CE Delft, TNO, Quintel), April 2021 where a previous version of ChaProEV was used to provide charging profiles of electric vehicles at the province level (for the Dutch proivinces of North Holland and Limburg)
-
Elektrisch rijden personenauto's & logistiek: Trends en impact op het elektriciteitssyteem. Hein de Wilde, Charlotte Smit, Omar Usmani, Sebastiaan Hers (TNO), Marieke Nauta (PBL), August 2022 where a previous version of ChaProEV was used to identify potential moments where charging electric cars could result in local (i.e. neighbourhood/transformer level) network issues and see if these issues could be solved.
-
Verlagen van lokale impact laden elektrisch vervoer: De waarde en haalbarheid van potentiële oplossingen, Charlotte Smit, Hein de Wilde, Richard Westerga, Omar Usmani, Sebastiaan Hers, TNO M12721, December 2022 where a previous version of ChaProEV was used to identify and quantify potential solutions to potential local (i.e. neighbourhood/transformer level) issues due to a possible large-scale adoption of electric cars (with illustrative examples for neighbourhoods in ihe cities of Amsterdam and Lelystad).
-
TRADE-RES. A previous version of ChaProEV was used to generate reference charging profiles for a number of European countries, based on statistical differences per country. Results are in the TRADE-RES scenario database
After/during Mopo
- I.S. Jimenez, D. Ribó-Pérez, M. Cvetkovic, J. Kochems, C. Schimeczek, L. de Vries,Can an energy only market enable resource ade- quacy in a decarbonized power system? a co-simulation with two agent-based-models Applied Energy 360 (2024) 122695
- S. Johanndeiter, N. Helistö, J. Kiviluoma, V. Bertsch, Price formation and intersectoral distributional eects in a fully decarbonised european electricity market
- Sanchez Jimenez, Ingrid and Johanndeiter, Silke and de Vries, Laurens, Capacity Remuneration Mechanisms for Power Systems in Transition. Available at SSRN: https://ssrn.com/abstract=5196543 or http://dx.doi.org/10.2139/ssrn.5196543
Future
The ChaProEV will be used in other projects that will be listed here, if deemed relevant and apprpriate within the context of these projects.
Acknowledgments
 |
This project was partly develop under funding from the European Climate, Infrastructure and Environment Executive Agency under the European Union’s HORIZON Research and Innovation Actions under grant agreement N°101095998. |
1 maintainer
Metadata
1 maintainer
Release files for ChaProEV 1.3.4
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| File | Size | Uploaded | Provenance | |
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|---|---|---|---|---|
| chaproev-1.3.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.5 MB
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