SimBEV

Simulation of electric vehicle charging demand.

Documentation

The full documentation can be found here

Installation

Install using pip

First, clone via SSH using

git clone [email protected]:rl-institut/simbev.git /local/path/to/simbev/

Make sure you have Python >= 3.8 installed, let's create a virtual env:

virtualenv --python=python3.8 simbev
source simbev/bin/activate

Install package with

pip install -e /local/path/to/simbev/

Install using conda

Make sure you have conda installed, e.g. miniconda. Then create the env:

conda env create -n simbev -f /local/path/to/simbev/environment.yml
conda activate simbev

Run simBEV

Get the data

If you want to run SimBEV in the mode using probabilities, a data set is available here

Create a scenario

• You can use a default scenario or define a custom one in the directory scenarios
• Run simbev with the desired scenario: python -m simbev path/to/config (defaults to python -m simbev scenarios/default/configs/default.cfg)
• Results are created in the subdirectory results in the scenario directory

Set parameters for your scenario

Select regio-type for the mobility characteristics:

• regiotypes: Ländliche Regionen LR_Klein - Kleinstädtischer, dörflicher Raum LR_Mitte - Mittelstädte, städtischer Raum LR_Zentr - Zentrale Stadt Stadtregionen SR_Klein - Kleinstädtischer, dörflicher Raum SR_Mitte - Mittelstädte, städtischer Raum SR_Gross - Regiopolen, Großstädte SR_Metro - Metropole

Change vehicle configuration

• battery capacity
• charging power (slow and fast)
• consumption

Decide how many vehicles should be simulated

• note: more than 5000 vehicles of one type in one region is not necessary, if you want to analyze more, scale it accordingly

License

see LICENSE