trimton: Adjust the amount of turbines per windfarm

In YsoSirius/windfarmGA: Genetic Algorithm for Wind Farm Layout Optimization

Adjust the amount of turbines per windfarm

Description

Adjust the mutated individuals to the required amount of turbines.

Usage

trimton(mut, nturb, allparks, nGrids, trimForce, seed)

Arguments

mut	A binary matrix with the mutated individuals
nturb	A numeric value indicating the amount of required turbines
allparks	A data.frame consisting of all individuals of the current generation
nGrids	A numeric value indicating the total amount of grid cells
trimForce	If TRUE the algorithm will use a probabilistic approach to correct the windfarms to the desired amount of turbines. If FALSE the adjustment will be random. Default is FALSE
seed	Set a seed for comparability. Default is NULL

Value

Returns a binary matrix with the correct amount of turbines per individual

See Also

Other Genetic Algorithm Functions: crossover(), fitness(), genetic_algorithm(), init_population(), mutation(), selection()

Examples

## Create a random rectangular shapefile
library(sf)
Polygon1 <- sf::st_as_sf(sf::st_sfc(
  sf::st_polygon(list(cbind(
    c(0, 0, 2000, 2000, 0),
    c(0, 2000, 2000, 0, 0)
  ))),
  crs = 3035
))

## Create a uniform and unidirectional wind data.frame and plots the
## resulting wind rose
## Uniform wind speed and single wind direction
data.in <- as.data.frame(cbind(ws = 12, wd = 0))

## Calculate a Grid and an indexed data.frame with coordinates and grid cell Ids.
Grid1 <- grid_area(shape = Polygon1, size = 200, prop = 1)
Grid <- Grid1[[1]]
AmountGrids <- nrow(Grid)

startsel <- init_population(Grid, 10, 20)
wind <- as.data.frame(cbind(ws = 12, wd = 0))
wind <- list(wind, probab = 100)
fit <- fitness(
  selection = startsel, referenceHeight = 100, RotorHeight = 100,
  SurfaceRoughness = 0.3, Polygon = Polygon1, resol1 = 200, rot = 20,
  dirspeed = wind, srtm_crop = "", topograp = FALSE, cclRaster = ""
)
allparks <- do.call("rbind", fit)
## SELECTION
## print the amount of Individuals selected.
## Check if the amount of Turbines is as requested.
selec6best <- selection(fit, Grid, 2, TRUE, 6, "VAR")
selec6best <- selection(fit, Grid, 2, TRUE, 6, "FIX")
selec6best <- selection(fit, Grid, 4, FALSE, 6, "FIX")
## CROSSOVER
## u determines the amount of crossover points,
## crossPart determines the method used (Equal/Random),
## uplimit is the maximum allowed permutations
crossOut <- crossover(selec6best, 2, uplimit = 300, crossPart = "RAN")
crossOut <- crossover(selec6best, 7, uplimit = 500, crossPart = "RAN")
crossOut <- crossover(selec6best, 3, uplimit = 300, crossPart = "EQU")
## MUTATION
## Variable Mutation Rate is activated if more than 2 individuals represent
## the current best solution.
mut <- mutation(a = crossOut, p = 0.3, NULL)
## TRIMTON
## After Crossover and Mutation, the amount of turbines in a windpark change and have to be
## corrected to the required amount of turbines.
mut1 <- trimton(
  mut = mut, nturb = 10, allparks = allparks, nGrids = AmountGrids,
  trimForce = FALSE
)
colSums(mut)
colSums(mut1)

YsoSirius/windfarmGA documentation built on March 13, 2024, 8:37 a.m.