The genetic algorithm is designed to optimize wind farms of any shape. 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.
Switch to matrices instead of data.frames and a lot of restructuring and performance optimization of the whole algorithm.
windfarmGA and the plotting functions now accept SimpleFeature Polygons or coordinates in table format
with long, lat or x, y column names. The terrain effect model can now be activated only by setting
topograp to TRUE and it will attempt to download the land cover raster from the European Environment Agency website.
viewshedA new set of functions, to analyze the visual impact of a wind farm.
plot_farm_3dExperimental rayshader function
The output of
windfarmGA can be further randomized/optimized with the following
RandomSearch is used to randomize all turbines of the layout whereas
RandomSearchTurb is used to randomize a single turbine
RandomSearchPlot is used to plot the outputs of those functions, compared with the
loadloadRes = RandomSearchTurbRandomSearchPlot
## Runs the same optimization, but with parallel processing and 3 cores.result_par <- genAlgoPlotWindfarmGA
result_hex <- genAlgoPlotWindfarmGA