ChaProEV

This repository contains the ChaProEV (Charging Profiles of Electric Vehicles)
model.

Status

The ChaProEV model is currently released and useable. This version
has been used in projects and can be used in future projects.
Please contact the authors below if you have questions or requests to get
model runs at some point.

Authors and contact

Omar Usmani ([email protected])

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

if __name__ == '__main__':
    case_name: str = 'Mopo'
    ChaProEV.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

if __name__ == '__main__':
    case_name: str = 'test_case'
    ChaProEV.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

1. 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)

2. 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.

3. 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).

4. 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

1. 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
2. S. Johanndeiter, N. Helistö, J. Kiviluoma, V. Bertsch, Price formation
   and intersectoral distributional eects in a fully decarbonised european
   electricity market
3. 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