AtmosphericModels

This package provides functions for modelling the influence of the atmosphere on wind energy systems. It models the air density, the vertical wind profile and the wind turbulence. Further functions to import measured data are planned.

Installation

Install Julia 1.10 or later, if you haven't already.

First, create a new Julia project:

mkdir test
cd test
julia --project=.

You can now add AtmosphericModels from Julia's package manager, by typing

using Pkg
pkg"add AtmosphericModels"

at the Julia prompt.

Running the tests

Launch Julia using this project and run the tests:

julia --project
julia> using Pkg
julia> Pkg.test("AtmosphericModels")

Running the examples

If you check out the project using git, you can more easily run the examples:

git clone https://github.com/OpenSourceAWE/AtmosphericModels.jl
cd AtmosphericModels.jl

Launch Julia using this project with julia --project and run the example menu:

include("examples/menu.jl")

The first time will take some time, because the graphic libraries will get installed, the second time it is fast.

Usage

Calculate the height dependant wind speed

Make sure that the folder data exist and contains the files system_nearshore.yaml and settings_nearshore.yaml. These configuration files contain the wind profile parameters, fitted to the near shore location Maasvlakte, NL on a specific day.

using AtmosphericModels, KiteUtils
set_data_path("data")
set = load_settings("system.yaml"; relax=true)
am = AtmosphericModel(set)

height = 100.0
wf = calc_wind_factor(am, height)

The result is the factor with which the ground wind speed needs to be multiplied to get the wind speed at the given height.

Using the turbulent wind field

You can get a wind vector as function of x,y,z and time using the following code:

using AtmosphericModels, KiteUtils

set_data_path("data")
set = load_settings("system.yaml"; relax=true)
am::AtmosphericModel = AtmosphericModel(set)

@info "Ground wind speed: $(am.set.v_wind) m/s"

wf::WindField = WindField(am, am.set.v_wind)
x, y, z = 20.0, 0.0, 200.0
t = 0.0
vx, vy, vz = get_wind(wf, am, x, y, z, t)
@time get_wind(am, x, y, z, t)
@info "Wind at x=$(x), y=$(y), z=$(z), t=$(t): v_x=$(vx), v_y=$(vy), v_z=$(vz)"
@info "Wind speed: $(sqrt(vx^2 + vy^2 + vz^2)) m/s"

It is suggested to check out the code using git before executing this example, because it requires that a data directory with the correct files system.yaml and settings.yaml exists. See below how to do that.

Plot a wind profile

using AtmosphericModels, KiteUtils, ControlPlots
am = AtmosphericModel(se())

heights = 6:1000
wf = [calc_wind_factor(am, height, Int(EXPLOG)) for height in heights]

plot(heights, wf, xlabel="height [m]", ylabel="wind factor", fig="Nearshore")

Wind profile nearshore

using AtmosphericModels, ControlPlots, KiteUtils
am = AtmosphericModel(se())
AtmosphericModels.se().alpha = 0.234  # set the exponent of the power law

heights = 6:200
wf = [calc_wind_factor(am, height, Int(EXP)) for height in heights]

plot(heights, wf, xlabel="height [m]", ylabel="wind factor", fig="Onshore")

Air density

using AtmosphericModels, BenchmarkTools, KiteUtils
am = AtmosphericModel(se())
@benchmark calc_rho(am, height) setup=(height=Float64((6.0+rand()*500.0)))

This gives 4.85 ns as result. Plot the air density:

heights = 6:1000
rhos = [calc_rho(am, height) for height in heights]
plot(heights, rhos, legend=false, xlabel="height [m]", ylabel="air density [kg/m³]")

Airdensity