Farm Optimization and eXtended yield Evaluation Software
Project description
foxes
Farm Optimization and eXtended yield Evaluation Software
Overview
The software foxes
is a modular wind farm simulation and wake modelling toolbox which is based on engineering wake models. It has many applications, for example
- Wind farm optimization, e.g. layout optimization or wake steering,
- Wind farm post-construction analysis,
- Wake model studies, comparison and validation,
- Wind farm simulations invoking complex model chains.
Currently the modelled time scales are related to 10-min averages or longer periods, and also statistical data like wind rose data can be modelled. High-frequency effects are not supported.
Source code: https://github.com/FraunhoferIWES/foxes
PyPi reference: https://pypi.org/project/foxes/
Requirements
The supported Python versions are:
Python 3.7
Python 3.8
Python 3.9
Python 3.10
Installation
Virtual Python environment
We recommend working in a Python virtual environment and install foxes
there. Such an environment can be created by
python -m venv /path/to/my_venv
and afterwards be activated by
source /path/to/my_venv/bin/activate
All subsequent installation commands via pip
can then be executed directly within the active environment without changes. After your work with foxes
is done you can leave the environment by the command deactivate
.
Standard users
As a standard user, you can install the latest release via pip by
pip install foxes
This in general corresponds to the main
branch at github. Alternatively, you can decide to install the latest pre-release developments by
pip install git+https://github.com/FraunhoferIWES/foxes/tree/dev
Developers
The first step as a developer is to clone the foxes
repository by
git clone https://github.com/FraunhoferIWES/foxes.git
Enter the root directory by cd foxes
. Then you can either install from this directory via
pip install -e .
Alternatively, add the foxes
directory to your PYTHONPATH
, e.g. by running
export PYTHONPATH=`pwd`:$PYTHONPATH
from the root foxes
directory, and then
pip install -r requirements.txt
Minimal example
For detailed examples of how to run foxes, check the examples
and notebooks
folders in this repository. A minimal running example is the following, based on provided static csv
data files:
import foxes
states = foxes.input.states.Timeseries("timeseries_3000.csv.gz", ["WS", "WD","TI","RHO"])
farm = foxes.WindFarm()
foxes.input.farm_layout.add_from_file(farm,"test_farm_67.csv",turbine_models=["Pct"])
mbook = foxes.ModelBook("NREL-5MW-D126-H90.csv")
algo = foxes.algorithms.Downwind(mbook, farm, states, ["Jensen_linear_k007"])
algo.calc_farm()
print(farm_results)
Acknowledgements
The development of foxes and its predecessors flapFOAM and flappy (internal - non public) has been supported through multiple publicly funded research projects. We acknowledge in particular the funding by the Federal Ministry of Economic Affairs and Climate Action (BMWK) through the projects Smart Wind Farms (grant no. 0325851B), GW-Wakes (0325397B) and X-Wakes (03EE3008A) as well as the funding by the Federal Ministry of Education and Research (BMBF) in the framework of the project H2Digital (03SF0635).
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