Simulation program to generate scenarios of electric vehicle fleets and simulate different charging strategies.
SpiceEV is a program to simulate different charging strategies for a defined set of vehicles and corresponding trips to and from charging stations. The output shows load profiles of the vehicle battery, the corresponding charging station, the grid connector as well as the electricity price and, if applicable, stationary batteries. Each vehicle is by default connected to a separate charging station. All charging stations of one location can be connected to one grid connector with a defined maximum power. Some charging strategies only allow for one grid connector, please check charging strategies for more information.
The first step of SpiceEV is to generate a
scenario.json contains information about the vehicles and their specific attributes (e.g. battery capacity, charging curve, etc.) as well as their trips from and to a specific charging station (so-called vehicle events). Further, the charging stations attributes, such as its maximum power, the attached grid connector and the according electricity price are defined. Depending on the scenario, a certain foresight can be applied for grid operator signals. If applicable, stationary batteries with according capacities and c_rates can be defined and fixed load profiles or local generation time series attached to a grid connector can be imported from CSV files. The input
scenario.json can be generated by one of the generate scripts.
The full documentation can be found here
Clone this repository. SpiceEV just has an optional dependency on Matplotlib. Everything else uses the Python (>= 3.6) standard library.
spice_ev as a package run:
pip install -e .
In order to run a simulation with
simulate.py a scenario JSON has to be generated first using
For this three modes are available:
statisticsGenerate a scenario JSON with trips from statistical input parameters.
csvGenerate a scenario JSON with trips listed in a CSV.
simbevGenerate a scenario JSON from SimBEV results.
Show all command line options:
python generate.py -h python simulate.py -h
Generate a scenario and store it in a JSON. By default, the mode
statistics is used.
python generate.py --output scenario.json
Run a simulation of this scenario using the
greedy charging strategy and show
plots of the results:
python simulate.py scenario.json --strategy greedy --visual
There are example configuration files in the folder examples. The required input/output must still be specified manually:
python generate.py --config examples/configs/generate.cfg python simulate.py --config examples/configs/simulate.cfg
Generate a 7-day scenario with 10 vehicles of different types and 15 minute timesteps:
python generate.py --days 7 --vehicles 6 golf --vehicles 4 sprinter --interval 15 --output scenario.json
Include a fixed load in the scenario:
python generate.py --include-fixed-load-csv fixed_load.csv --output scenario.json
Please note that included file paths are relative to the scenario file location. Consider this directory structure:
├── scenarios │ ├── price │ │ ├── price.csv │ ├── my_scenario │ │ ├── fixed_load.csv │ │ ├── scenario.json
fixed_load.csv is in the same directory as the
scenario.json, hence no relative path is specified.
To include the price and fixed load timeseries:
python generate.py --include-price-csv ../price/price.csv --include-fixed-load-csv fixed_load.csv --output scenario.json
Calculate and include schedule:
python generate_schedule.py --scenario scenario.json --input examples/data/grid_situation.csv --output schedules/schedule_example.csv
SpiceEV supports scenarios generated by the SimBEV tool. Convert SimBEV output files to a SpiceEV scenario:
python generate.py simbev --simbev /path/to/simbev/output/ --output scenario.json
SpiceEV is licensed under the MIT License as described in the file LICENSE