Calculate Energy Outputs of Individuals

Calculate the energy output and efficiency rates of an individual in the current population under all given wind directions and speeds. If the terrain effect model is activated, the main calculations to model those effects will be done in this function.

Usage

calculate_energy(
  sel,
  referenceHeight,
  RotorHeight,
  SurfaceRoughness,
  wnkl,
  distanz,
  polygon1,
  RotorR,
  dirSpeed,
  srtm_crop,
  topograp,
  cclRaster,
  weibull,
  plotit = FALSE
)

Arguments

sel

A matrix of an individual of the current population

referenceHeight

The height at which the incoming wind speeds were measured. Default is RotorHeight

RotorHeight

The height of the turbine hub

SurfaceRoughness

A surface roughness length in meters. With the terrain effect model, a surface roughness is calculated for every grid cell using the elevation and land cover data. Default is 0.3

wnkl

The angle from which wake influences are considered to be negligible

distanz

The distance after which wake effects are considered to be eliminated

polygon1

The considered area as Simple Feature Polygon

RotorR

The desired rotor radius in meter

dirSpeed

The wind speed and direction data.frame

srtm_crop

A list of 3 raster, with 1) the elevation, 2) an orographic and 3) a terrain raster. Calculated in genetic_algorithm

topograp

Boolean value, which indicates if the terrain effect model should be enabled or not. Default is FALSE

cclRaster

A Corine Land Cover raster, that has to be adapted previously by hand with the surface roughness length for every land cover type. Is only used, when the terrain effect model is activated.

weibull

A boolean value that specifies whether to take Weibull parameters into account. If TRUE, the wind speed values of vdirspe are ignored. The algorithm will calculate the mean wind speed for every wind turbine according to the Weibull parameters. Default is FALSE

plotit

If TRUE, the process will be plotted. Default is FALSE

Value

Returns a list of an individual of the current generation with resulting wake effects, energy outputs, efficiency rates for every wind direction. The length of the list corresponds to the number of different wind directions.

See also

Other Wind Energy Calculation Functions: barometric_height(), get_dist_angles(), turbine_influences()

Examples

if (FALSE) {
## Create a random Polygon
library(sf)
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 uniform and unidirectional wind data.frame and plot the
## resulting wind rose
data.in <- data.frame(ws = 12, wd = 0)
windrosePlot <- plot_windrose(data = data.in, spd = data.in$ws,
                dir = data.in$wd, dirres=10, spdmax=20)

## Assign the rotor radius and a factor of the radius for grid spacing.
Rotor= 50; fcrR= 3
resGrid <- grid_area(shape = Polygon1, size = Rotor*fcrR, prop=1,
                      plotGrid = TRUE)
## Assign the indexed data frame to new variable. Element 2 of the list
## is the grid, saved as Simple Feature Polygons.
resGrid1 <- resGrid[[1]]

## Create an initial population with the indexed Grid, 15 turbines and
## 100 individuals.
initpop <- init_population(Grid = resGrid1, n = 15, nStart = 100)

## Calculate the expected energy output of the first individual of the
## population.
par(mfrow = c(1,2))
plot(Polygon1); points(initpop[[1]][,'X'],initpop[[1]][,'Y'], pch=20,cex=2)
plot(resGrid[[2]], add = TRUE)
resCalcEn <- calculate_energy(sel=initpop[[1]],referenceHeight= 50,
                   RotorHeight= 50, SurfaceRoughness = 0.14,wnkl = 20,
                   distanz = 100000, dirSpeed = data.in,
                   RotorR = 50, polygon1 = Polygon1, topograp = FALSE,
                   weibull = FALSE)
resCalcEn <- as.data.frame(resCalcEn)
plot(Polygon1, main = resCalcEn[,'Energy_Output_Red'][[1]])
points(x = resCalcEn[,'Bx'], y = resCalcEn[,'By'], pch = 20)


## Create a variable and multidirectional wind data.frame and plot the
## resulting wind rose
data.in10 <- data.frame(ws = runif(10,1,25), wd = runif(10,0,360))
windrosePlot <- plot_windrose(data = data.in10, spd = data.in10$ws,
                dir = data.in10$wd, dirres=10, spdmax=20)

## Calculate the energy outputs for the first individual with more than one
## wind direction.
resCalcEn <- calculate_energy(sel=initpop[[1]],referenceHeight= 50,
                   RotorHeight= 50, SurfaceRoughness = 0.14,wnkl = 20,
                   distanz = 100000, dirSpeed = data.in10,
                   RotorR = 50, polygon1 = Polygon1, topograp = FALSE,
                   weibull = FALSE)
}