History¶

v0.1.0-alpha¶

This is the initial release of foxes - ready for testing.

So far not many models have been transferred from the Fraunhofer IWES in-house predecessor flappy, they will be added in the following versions. Also optimization is not yet included. We are just getting started here!

Enjoy - we are awaiting comments and issues, thanks for testing.

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.1.0

v0.1.1-alpha¶

• New code style, created by black

• Small fixes, discovered by flake8

• Tests now via pytest instead of unittest

• Introducing github workflow for automatic testing

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.1.1

v0.1.2-alpha¶

• Adding support for Python 3.9, 3.10

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.1.2

v0.1.3-alpha¶

• Adding docu: https://fraunhoferiwes.github.io/foxes.docs/index.html

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.1.3

v0.1.4-alpha¶

• Fixes

  • Static data: Adding missing data wind_rotation.nc to manifest

• Models

  • New wake model added: TurbOParkWake from Orsted

  • New turbine type added: PCtSingleFiles, reads power and thrust curves from two separate files

  • New turbulence intensity wake model added: IECTI2019/Frandsen and IECTI2005

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.1.4

v0.2.0-alpha¶

• Core

  • Introducing the concept of runners

• Opt

  • New sub package: foxes.opt, install by pip install foxes[opt]. This introduces the capability to run wind farm optimizations. As examples layout optimization for simple cases are given, see below.

• Models

  • New turbine model: Thrust2Ct, calculates ct from thrust values

  • New turbine type: NullType, a turbine type with only rotor diameter and hub height data

  • Renamed PCtSingleFiles into PCtTwoFiles

• Output

  • New output: WindRoseOutput, providing a plotly figure that shows a rose-type histogram

  • New output: AmbientWindRoseOutput, providing rose-type plotly figures of ambient data (no wake calculation involved)

• Algorithms

  • Improved Downwind: Now with option for ambient runs (no wakes)

• Utils

  • New utility: show_plotly_fig, opens a window that shows a plotly figure (instead of browser)

  • New runners: DefaultRunner, DaskRunner. The latter features parallel runs via dask

• Examples

  • Introducing two sub-folders of examples: foxes and foxes.opt

  • New example: wind_rose, calculation of wind rose states data

  • New example: layout_single_state, wind farm layout optimization for a single wind state

  • New example: layout_wind_rose, wind farm layout optimization for wind rose states

• Notebooks

  • New notebook: layout_opt.ipynb, demonstrating a simple layout optimization case

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.2.0

v0.2.1-alpha¶

• Input:

  • New input: MultiHeightStates and MultiHeightTimeseries, for input data at several height levels, e.g. WRF results at one point

• Output:

  • New output: FarmResultsEval, calculates sum, mean, min, max over states or turbines for the whole wind farm. Also calculates capacity, efficiency, yield, P75, P90.

  • New output: ResultsWriter, writes farm results or pandas data to csv file

  • Renaming: AmbientRosePlotOutput is now called StatesRosePlotOutput

• Notebooks:

  • New notebook: multi_height.ipynb, demonstrating the usage of multi-height wind input data

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.2.1

v0.2.2-alpha¶

• Bug fixes

  • Bug fixed in MultiHeightStates for wind veer cases

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.2.2

v0.2.3-alpha¶

• Input states

  • Improved: SingleStateStates now supports profiles

• Turbine models

  • New model PowerMask: Derates or boosts a turbine

• Examples

  • New: power_mask, demonstrates derating and boost

• Utils

  • New: cubic_roots, solves a cubic equation

• Output

  • New: StateTurbineMap, creates heat maps for state-turbine data

  • New: TurbineTypeCurves, creates power and thrust curve plots

  • Improved: FarmLayoutOutput now supports scatter color by variable

• Documentation

  • Adding forgotten foxes.opt to API

• Notebooks:

  • Now including results as colored layout plots

  • New notebook: wind_rose.ipynb, demonstrating how to calculate wind roses

  • New notebook: power_mask.ipynb, showing derating and boost via a power mask

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.2.3

v0.2.4-alpha¶

• Bug fixes

  • Hotfix for bug in TurbineTypeCurves output

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.2.4

v0.2.5-alpha¶

• Core:

  • New: ExtendedStates, allows for adding point data models to states

• Input:

  • Improved: FieldDataNC, now with support for spatially uniform variables

• Turbine types:

  • New: WsRho2PCtTwoFiles, air density dependent power and ct curves

• Turbine models:

  • New: SectorManagement, sets variables by range rules on other variables

• Point models:

  • New: SetUniformData, set uniform variables (optionally state dependent)

• Examples:

  • New: sector_management, demonstrates how to model wind sector management

• Notebooks:

  • New: sector_man.ipynb, demonstrates how to model wind sector management

  • New: data.ipynb, lists and shows the static data

• Bug fixes:

  • Fix for bug with option col_models in farm layout from csv

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.2.5

v0.2.6-alpha¶

• Output:

  • Improved: FarmResultsEval can now handle NaN data in Einstein sums

  • Improved: ResultsWriter can now also write turbine names

• Turbine models:

  • New: TableFactors, multiplies variables with data from a two dimensional table

  • New: YAW2YAWM, calculates yaw deltas from absolute yaw and wind direction

  • New YAWM2YAW, calculates absolute yaw from yaw deltas and wind direction

  • Generalized: kTI, now includes optional offset kb

• Turbine types:

  • Changed: Now yaw correction of P and CT switched on by default

• Point models:

  • New: TKE2TI, calculates turbulence intensity from TKE

• Wake models:

  • New: PorteAgel, calculates wakes based on the Bastankhah PorteAgel 2016 wake model

• Wake frames:

  • New: YawedWake, bends wakes in yawed conditions

• Wake superposition models:

  • Improved: LinearSuperposition, now includes options for lower/higher limits of total wake deltas

• Examples:

  • New: compare_wakes, compares wake models along horizontal lines

  • New: yawed_wake, demonstrates wake bending by yawing a rotor

• Notebooks:

  • New: yawed_wake.ipynb, demonstrates wake bending by yawing a rotor

• Bug fixes:

  • Fix for bug with ExtendedStates, now it is actually working

  • Fix for bug with wake width in CrespoHernandezTIWake

  • Fix for bug with YAW and WD when using the YAWM2YAW turbine model

  • Fix for bug in TurbOPark wake model, double counting constant offset in sigma

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.2.6

v0.3.0-alpha¶

• Core:

  • Models now with simplified structure, reduces memory load during calculations

• Algorithms:

  • New: Iterative, iterative wind farm calculation until convergence has been reached

• Input:

  • Improved: FieldDataNC now accepts xarray Dataset or file pattern str as input

  • New: ShearedProfile, Vertical WS profile can be determined with shear exponent

• Output:

  • Improved: FlowPlots2D replacing horizontal/vertical –> xy, xz, yz, more intuitive

• Wake models:

  • New: TurbOParkIX, integrates wake corrected TI along centreline for wake width sigma.

• Wake frames:

  • Improved: All yawed wake frames now also support centreline data integration

• Notebooks:

  • New: overview.ipynb, summarizes the setup steps

• Bug fixes:

  • Fix for bug in TurbOPark wake model: Brackets in Eq. (4) were wrong

  • Fix for bug with long streamlines

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.3.0

v0.3.1-alpha¶

• Input states:

  • Improved: FieldDataNC now supports states subset selection

• Wake frames:

  • Improved: Streamlines now with maximal length option

• Turbine models:

  • New: Calculator, simple variable calculation via user function

• Opt:

  • Now two abstract problems in core: FarmOptProblem and FarmVarsProblem, the latter invokes the SetFarmVars turbine model

  • New opt problem: RegularLayoutOptProblem, searches for a regular grid layout

  • New opt problem: GeomRegGrids, finds regular grid layout by purely geometrical means (no wind farm calculation)

  • New opt problem: GeomLayout, turbine positioning based on xy variables, also purely geometrical

  • New opt problem: GeomLayoutGridded, a purely geometrical optimization on a gridded background

• Examples:

  • New in foxes.opt: Example layout_regular_grid, demonstrates regular grid layout optimization

  • New in foxes.opt: Example geom_reggrids, purely geometrical regular layout optimization

• Utils:

  • New functions for shape file handling: read_shp, shp2csv, read_shp_polygons

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.3.1

v0.3.2-alpha¶

• Bug fixes:

  • Fix for bug in FarmResultsEval that affected time range calculations under Windows

  • Bug fixes for FarmResultsEval with time series data

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.3.2

v0.3.3-alpha¶

• Utils:

  • Now geopandas_helpers can handle interior areas

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.3.3

v0.3.4-alpha¶

• Installation:

  • foxes now supports Python 3.11

• Input:

  • New layout input option: add_from_df, adding turbines from a pandas DataFrame

  • New interface to windIO case yaml files

• Turbine types:

  • New turbine type CpCtFile, reads CP and CT data from file or pandas DataFrame

  • New turbine type CpCtFromTwo, reads CP and CT data from two files or pandas DataFrames

  • Improved: Turbine types now calculate P_nominal as maximum, if not explicitely given

• Constants:

  • Introducing P_UNITS, used in turbine types and output evaluation

• States:

  • Bug fixed in FieldDataNC with loading multiple files

• Core:

  • Improved DataCalcModel: Now cleaner treatment of runs with progress_bar=False. Also now slimmer for distributed scheduler

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.3.4

v0.3.5-alpha¶

• General:

  • Moving identifier-type entries from foxes.variables to foxes.constants

• Models:

  • New wake superposition model ProductSuperposition, computing factorized wake deltas

  • New turbine model: RotorCentreCalc, calculates data at rotor centre, irrespective of rotor model

• Bug fixes:

  • Bug fixed that caused problems when restarting the SectorManagement turbine model, e.g. for flow plots

• Documentation:

  • Completely new style, fixing issues with incomplete API entries

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.3.5

v0.4.0¶

• Models:

  • Improved: New option to specify wake growth variable name, such that multiple kTI models could be used, resulting in different k‘s for different wake models

  • New turbine model: LookupTable, interpolates data based on a multi-dimensional lookup table

• Utils:

  • Improved DaskRunner: Now supports clusters that run the Slurm queueing system

• Examples:

  • New: timeseries_slurm, shows how to run foxes on a HPC with Slurm queueing system

• Optimization:

  • Improved: foxes.opt is now able to optimize for flow variables (at selected points in space) in addition to turbine variables

• Documentation:

  • Improved API docu, now based on python-apigen

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.4.0

v0.4.1¶

• Algorithms:

  • Improved: Iterative now iterates through outer loop instead of within chunk

• Models:

  • New wake frame: Timelines, propagates wakes for spatially uniform time series

• Tests:

  • New test: consistency/iterative, checks if iterative algorithm gives same result

• Examples:

  • New example: timelines, demonstrates the usage of the Timelines wake frame

  • Improved: All examples were update for the correct usage of the DaskRunner

• Notebooks:

  • New notebook: timelines.ipynb, showing how to use the Timelines wake frame in a notebook

• Data:

  • New states data timeseries_100.csv.gz, a short timeseries with timestep 1 min, varying wind direction only

• Output:

  • Improved: FlowPlots2D now has the optional argument runner, for computing plots with the chosen parallelization settings

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.4.1

v0.4.2¶

• Bug fixes:

  • Fix of bug that slowed down TurbOParkIX by considering all TI wakes instead of only source turbine wake during integration

  • Fix of bug that prevented plotly wind roses to be shown in the documentation

  • Fix in docu that excluded the algorithm models from the API

• Output:

  • New: Animator, creates animations based on generators that yield lists of artists

• Examples:

  • Improved: timelines now includes turbine REWS signal in animations

• Notebooks:

  • Improved: timelines.ipynb now includes turbine REWS signal in animations

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.4.2

v0.4.3¶

• Output:

  • Improved: RosePlotOutput and StatesRosePlotOutput now optionally return the binned data

• Models:

  • New vertical profile: DataProfile, data based profile from file or pandas DataFrame

  • Improved ti superposition: Now supporting n-th power superposition

  • Improved wake model TurbOParkIX: New option for consideration of all wakes in ti integral

• Bug fixes:

  • Fixed bug with windio input that resulted in wrong wind rose weights

  • Fixed bug with FlowPlots2D with value bounds in contour plots

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.4.3

v0.4.4¶

• Testing automated publishing to PyPi via workflow

v0.4.5¶

• Models:

  • New rotor model: LevelRotor, calculates the REWS from different height levels

  • New turbine type: WsTI2PCtFromTwo, reads turbulence-dependent ct- and power curves

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.4.5

v0.5¶

• Dependencies:

  • Dropping support for Python 3.7, due to netcdf4 dependency

• Core:

  • Simplified model initialization/finalization. Removing the keep_models idea, instead all models are now kept in the algorithm’s idata memory until finalization. Adding a new model now mostly requires that the sub_models and the load_data functions are overloaded, if applicable. The initialize and finalize only need to be addressed explicitly in non-standard cases.

• Algorithms:

  • New algorithm: Sequential, step wise evaluation of states for simulation environments that do not support chunking

  • Improved: Iterative now supports under-relaxation of parameters

• Output:

  • New sub package: output.flow_plots_2d is now a package instead of a module

• Models:

  • This version introduces induction models for modelling blockage effects.

  • New induction model: RHB, the classic Rankine-half-body model.

• Examples:

  • New example: sequential, demonstrating the usage of the sequential algorithm

  • New example: induction_RHB, showing the Rankine-half-body model for blockage

• Notebooks:

  • New notebook: blockage.ipynb, demonstrating how to apply the RHB induction model to a wind farm

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.5

v0.5.1¶

• Dependencies:

  • The windio package is now an optional dependency, to be installed by hand if needed. This is due to windio being not available at conda-forge

• Notebooks:

  • New notebook: sequential.ipynb, creating an animation showing state-by-state wake propagation

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.5.1

v0.5.2¶

• Algorithms:

  • Improved Downwind: Now optional arguments that allow calculation of subsets in calc_farm and calc_points, e.g. a selection of states

• Output:

  • New output: PointCalculator, a wrapper for the calc_points function of the algorithm

  • New output: SliceData, creating arrays, DataFrames or Datasets from 2D slices

  • Improved FlowPlots2D: Completely refactored, data based on SliceData. New option for creating figures for subsets of states only.

• Vertical profiles:

  • Now optional support for ustar input data instead of reference data

• Turbine types:

  • Fix for Cp-based models with interpolation within sparse input data

• Wake models:

  • Renaming: BastankhahWake class now called Bastankhah2014. Models in the model book are also renamed from Bastankhah to Bastankhah2014

  • Renaming: PorteAgelWake class now called Bastankhah2016. Models in the model book are also renamed from PorteAgel to Bastankhah2016

  • Renaming: RHB class now called RankineHalfBody

  • Fix: RankineHalfBody no longer shows a jump at the rotor disc, but a small region of constant deficit instead

  • New default values: Bastankhah2014 now has default value sbeta_factor=0.2 (previously 0.25). Models with the previous value are available in the model book as Bastankhah025 etc.

• Wake superpositions:

  • Restructured: Now simplified classes for WS or TI superposition only (less general but simpler), e.g. WSLinear or TIQuadratic, etc. Also in the model book the models are now called ws_linear or ti_quadratic, etc.

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.5.2

v0.5.2.1¶

• Bug fixes:

  • Bugs fixed that messed up the colorbar and the title in animations

• Notebooks:

  • Improved animations in timelines.ipynb and sequential.ipynb

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.5.2.1

v0.6¶

• Dependencies:

  • Replacing dependency on plotly by dependency on windrose, since the latter is lighter

• Core:

  • This version introduces AxialInductionModel classes, computing the axial induction factor a(ct)

• Wake models:

  • Reformulating beta in terms of induction in Bastankhah2014 and CrespoHernandez

  • New default: Bastankhah2014, Bastankhah2016, TurbOPark and TurbOParkIX now with default axial induction model Madsen

  • New induction wake models: Rathmann, SelfSimilar and SelfSimilar2020, for blockage modelling

  • Introducing WakeMirror wrapper around wake models, modelling wake reflection from ground or horizontal plane via virtual mirrored turbines

• Wake frames:

  • Renaming Streamlines to Streamlines2D, no changes in model book names

• Axial induction models:

  • New induction model: BetzAxialInduction, the classic a = 0.5(1 - sqrt(1-ct)) relation. In the model book this is called Betz.

  • New induction model: MadsenAxialInduction, a third-order polynomial approximation of a(ct). In the model book this is called Madsen.

• Output:

  • Improved: FlowPlots2D now includes an option for indicating the rotor disk by a colored line

  • Improved: RosePlotOutput no longer depends on plotly, but on the new utility TabWindroseAxes

• Utils:

  • New: TabWindroseAxes, a derivative of windrose.WindroseAxes for input data that is based on bins with weights (and not timeseries)

• Notebooks:

  • New: blockage_comparison.ipynb, comparing four turbine induction models

• Bug fixes:

  • Fix for bug in Streamlines2D when used in combination with WakeMirror

• Tests:

  • Fresh flappy v0.6.2 test data for all Bastankhah and CrespoHernandez wakes, also without the sbeta limitation

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.6

v0.6.1¶

• Input:

  • New ambient states: TabStates, single tab-file input

• Data

  • New static data: winds100.tab, an example tab file

• Examples:

  • New example: tab_file, demonstrating the usage of the TabStates

• Bug fixes:

  • Bug fixed for RankineHalfBody turbine induction model that produced wrong results for wind directions unequal 270 degrees

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.6.1

v0.6.2¶

• Models:

  • New partial wakes model: PartialCentre, evaluating wake deltas at the rotor centre point only

• Inputs:

  • New farm layout input: add_random, adds turbines at random positions, respecting a minimal distance

  • New states creation: random_timseries_data, creates uniform random timeseries data

• Utils:

  • New function random_xy_square, generates random xy positions with minimal distance

• Examples:

  • New example: random_timeseries, computes a random farm in a random timeseries. Both sizes are defined by user input

Full Changelog: https://github.com/FraunhoferIWES/foxes/commits/v0.6.2