# get_dist_angles: Calculate distances and angles of possibly influencing... In windfarmGA: Genetic Algorithm for Wind Farm Layout Optimization

## Description

Calculate distances and angles for a turbine and all it's potentially influencing turbines.

## Usage

 `1` ```get_dist_angles(t, o, wnkl, dist, polYgon, plotAngles = FALSE) ```

## Arguments

 `t` A data.frame of the current individual with X and Y coordinates `o` A numeric value indicating the index of the current turbine `wnkl` The angle from which wake influences are considered to be negligible `dist` A numeric value indicating the distance, after which the wake effects are considered to be eliminated. `polYgon` A shapefile representing the considered area `plotAngles` A logical variable, which is used to plot the distances and angles. Default is `FALSE`

## Value

Returns a matrix with the distances and angles of potentially influencing turbines

Other Wind Energy Calculation Functions: `barometric_height()`, `calculate_energy()`, `turbine_influences()`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```library(sf) ## Exemplary input Polygon with 2km x 2km: Polygon1 <- sf::st_as_sf(sf::st_sfc( sf::st_polygon(list(cbind( c(4498482, 4498482, 4499991, 4499991, 4498482), c(2668272, 2669343, 2669343, 2668272, 2668272)))), crs = 3035 )) ## Create a random windfarm with 10 turbines t <- st_coordinates(st_sample(Polygon1, 10)) wnkl <- 20 dist <- 100000 ## Evaluate and plot for every turbine all other potentially influencing turbines potInfTur <- list() for (i in 1:(length(t[,1]))) { potInfTur[[i]] <- get_dist_angles(t = t, o = i, wnkl = wnkl, dist = dist, polYgon = Polygon1, plotAngles = TRUE) } potInfTur ```