Package: windfarmGA 5.0.0

Sebastian Gatscha

windfarmGA: Genetic Algorithm for Wind Farm Layout Optimization

The genetic algorithm is designed to optimize wind farms of any shape. Each layout is encoded as n unique grid-cell identifiers. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.

Authors:Sebastian Gatscha [aut, cre, cph]

windfarmGA_5.0.0.tar.gz
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windfarmGA_5.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
windfarmGA/json (API)

# Install 'windfarmGA' in R:
install.packages('windfarmGA', repos = c('https://ysosirius.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ysosirius/windfarmga/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • big_shape - A POLYGON with an area of ~70 km2
  • hole_shape - A POLYGON with a hole
  • multi_shape - A MULTIPOLYGON with 3 Polygons
  • resulthex - A resulting matrix of 'genetic_algorithm' with 10 iterations and a hexagonal grid derived from 'sp_polygon'
  • resultrect - A resulting matrix of 'genetic_algorithm' with 50 generations and a rectangular grid derived from 'sp_polygon'
  • sp_polygon - The rectangular POLYGON used to create 'resultrect' & 'resulthex'

On CRAN:

Conda:

windfarm-layoutoptimizationgenetic-algorithmrenewable-energycpp

5.19 score 31 stars 25 scripts 607 downloads 54 exports 16 dependencies

Last updated from:e969baac41. Checks:4 ERROR, 11 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR351
linux-devel-x86_64OK408
source / vignettesOK237
linux-release-arm64ERROR326
linux-release-x86_64OK410
macos-release-arm64OK205
macos-release-x86_64OK635
macos-oldrel-arm64OK249
macos-oldrel-x86_64OK1036
windows-devel-arm64ERROR595
windows-devel-x86_64OK430
windows-release-arm64ERROR555
windows-release-x86_64OK414
windows-oldrel-x86_64OK382
wasm-releaseOK167

Exports:as_windfarmGAbarometric_heightcalculate_energycircle_intersectioncrossoverexplore_resultfitnessga_optionsgeneration_layoutsgenetic_algorithmget_dist_anglesget_gridsgrid_areahexa_areainit_populationis_doparallel_installedis_elevatr_installedis_foreach_installedis_ggplot2_installedis_leaflet_installedis_parallel_installedis_plotly_installedis_shiny_installedisSpatialmutationplot_cell_heatmapplot_cloudplot_developmentplot_evolutionplot_generationplot_leafletplot_parkfitnessplot_populationplot_power_curveplot_random_searchplot_resultplot_viewshedplot_windfarmGAplot_windrosepopulation_censusrandom_searchrandom_search_singleread_power_curveselectionset_crossoversplitAtswap_mutationterrain_modeltrimtonturbine_influenceswake_coneswind_from_serieswind_from_uvwindata_format

Dependencies:calibrateclassclassIntDBIe1071KernSmoothmagrittrMASSproxyRColorBrewerRcpps2sfterraunitswk

Readme and manuals

Help Manual

Help pageTopics
windfarmGA: Genetic Algorithm for Wind Farm Layout OptimizationwindfarmGA-package windfarmGA
Mark a genetic_algorithm resultas_windfarmGA plot.windfarmGA print.windfarmGA
Calculates Air Density, Air Pressure and Temperature according to the Barometric Height Formulabarometric_height
A POLYGON with an area of ~70 km2big_shape
Calculate Energy Outputs of Individualscalculate_energy
Get area of intersecting circlescircle_intersection
Crossover Methodcrossover
Shiny explorer for a GA resultexplore_result
Evaluate the Individual Fitness valuesfitness
Get or set windfarmGA optionsga_options
Layouts evaluated in one generationgeneration_layouts
Run a Genetic Algorithm to optimize a wind farm layoutgenetic_algorithm
Calculate distances and angles of possibly influencing turbinesget_dist_angles
Map layouts to grid coordinatesget_grids
Make a grid from a Simple Feature Polygongrid_area
Polygon to Hexagonal Gridshexa_area
A POLYGON with a holehole_shape
Create a random initial Populationinit_population
Transform to Simple Feature PolygonsisSpatial
A MULTIPOLYGON with 3 Polygonsmulti_shape
Mutation Methodmutation
Is the package installed or notis_doparallel_installed is_elevatr_installed is_foreach_installed is_ggplot2_installed is_leaflet_installed is_parallel_installed is_plotly_installed is_shiny_installed package_installed
Enumerate the Combinations or Permutations of the Elements of a Vectorpermutations
Heatmap of probed grid cellsplot_cell_heatmap
Per-generation fitness / efficiency / energyplot_cloud
When the best layout improvedplot_development
Energy and efficiency over generationsplot_evolution
Plot all layouts of one generationplot_generation
Plot a wind warm with leafletplot_leaflet
Fitness and operator ratesplot_parkfitness
Plot population size, cells and efficiencyplot_population
Manufacturer power curveplot_power_curve
Plot the result of a randomized output.plot_random_search
Plot the best resultsplot_result
Plot visibilityplot_viewshed
Plot the results of an optimization runplot_windfarmGA
Plot a Windroseplot_windrose
Population size and diversity per generationpopulation_census
Randomize the output of the Genetic Algorithmrandom_search
Randomize the location of a single turbinerandom_search_single
Read a manufacturer or NREL/IEA power-curve tableread_power_curve
A resulting matrix of 'genetic_algorithm' with 10 iterations and a hexagonal grid derived from 'sp_polygon'resulthex
A resulting matrix of 'genetic_algorithm' with 50 generations and a rectangular grid derived from 'sp_polygon'resultrect
Selection Methodselection
Set crossover of turbine layoutsset_crossover
The rectangular POLYGON used to create 'resultrect' & 'resulthex'sp_polygon
Split matrices or numeric vectors at specific indicessplitAt
Swap mutation of turbine layoutsswap_mutation
Get terrainhic rastersterrain_model
Adjust the amount of turbines per windfarmtrimton
Find potentially influencing turbinesturbine_influences
Downwind wake search coneswake_cones
Wind rose from speed and direction serieswind_from_series
Wind rose from u/v componentswind_from_uv
Transform Winddatawindata_format