Welcome to FOXES¶

Farm Optimization and eXtended yield Evaluation Software

FOXES is a modular wind farm and wake modelling code written in Python by Fraunhofer IWES. 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.

The fast performance of foxes is owed to vectorization and parallelization, and it is intended to be used for large wind farms and large timeseries inflow data. The parallelization on local or remote clusters is supported, based on mpi4py or dask.distributed. The wind farm optimization capabilities invoke the foxes-opt package which as well supports vectorization and parallelization.

Source code repository (and issue tracker):

https://github.com/FraunhoferIWES/foxes

Please report code issues under the github link above.

License¶

MIT

Contents¶

• Citation
  • Journal paper
  • Version specific DOI

• Installation
  • Requirements
  • TLDR; Quick installation guide
  • Installation via pip
  • Installation via conda

• Overview - how to setup foxes

• Inputs
  • Wind farm layouts
  • Ambient inflow states

• Models
  • Model types
  • Rotor models
  • Turbine types
  • Wake models
  • Wake frames
  • Wake deflections
  • Partial wakes
  • Turbine models
  • Farm controllers
  • Ground models
  • Point models
  • Vertical profiles

• Parallelization
  • Available engines
  • Default engine
  • Engine selection through a with-block
  • Remarks & recommendations

• Input parameter files
  • foxes_yaml
  • foxes_windio

• Examples
  • The model book
  • Single row of turbines
  • Timeseries data
  • Multi-height wind data
  • Wind rose data
  • Wind sector management
  • Heterogeneous flow
  • Power mask
  • Yawed rotor wakes
  • Dynamic Wakes 1
  • Dynamic Wakes 2
  • Dynamic Wakes 3
  • Blockage modelling 1
  • Blockage modelling 2
  • Turbine operation flags
  • Partial wakes verification
  • ICON-DREAM data
  • Turbine-based ambient flow data

• Optimization

• API

• Static data
  • Wind farm layout data
  • Ambient states data
  • Power and thrust curves
  • File paths

• Testing

• Changelog

Contributing¶

1. Fork foxes on github.

2. Create a branch (git checkout -b new_branch)

3. Commit your changes (git commit -am “your awesome message”)

4. Push to the branch (git push origin new_branch)

5. Create a pull request here

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 p rojects 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). We furthermore acknowledge funding by the Horizon Europe project FLOW (Atmospheric Flow, Loads and pOwer for Wind energy - grant id 101084205) and AIRE (EU Program Horizon Europe, grant agreement 101083716).