OOWL: Onshore and Offshore Wind Layouts

OOWL: Onshore and Offshore Wind Layouts#

OOWL (pronounced /aʊl/ like owl) draws wind farms with an exact turbine count inside a boundary you describe, placed by the method you pick. One description draws one farm or a thousand.

_images/2d36a9b1a9acb6991e748738f9eff5f910d7bc646b99154a8a296c5c25f617a9.png

One offshore boundary, four layout families, 64 turbines in every panel.

Install#

pip install oowl

Installation covers pip, pixi, and a development checkout.

Draw one farm#

Describe the scenario, then draw from it.

import matplotlib.pyplot as plt

import oowl
from oowl import boundaries as B
from oowl import layouts as L

boundary = B.Rectangle(9, 5, area=45_000_000)
spec = oowl.Sampler(boundary, L.Grid(n_turbines=92, lattice_angle=60, seed=4))

farm = spec.sample()[0]
print(farm.n_turbines, "turbines at", farm.positions.shape, "coordinates")

ax = farm.plot()

92 turbines at (92, 2) coordinates
_images/ffda5d648d6bc45265a06ac3f529c84117d3d5c9693e5c11c5830b17177a992f.png

Draw a population#

Give a value a range and the description becomes a population.

population = oowl.Sampler(
    boundary=B.OffshorePolygon,
    layout=L.Grid,
    n_turbines=(40, 120),
    density={"minimum_spacing": 800.0},
    seed=7,
)

fig, axes = plt.subplots(1, 3, figsize=(11.0, 3.4))
for ax, drawn in zip(axes, population.sample(3)):
    drawn.plot(ax=ax, title=f"n = {drawn.n_turbines}")
fig.tight_layout()
_images/5426e213e97aef3f2d5690752da9111792234fe132450ebd608891f8fab49036.png

Seeds are derived per scenario, so farm i is the same however many are drawn.

The six layers#

Layer

What it decides

boundaries

the farm area, including holes, partitions and regions

strings

optional line guides to place turbines along

layouts

exact turbine placement inside the area

surfaces

optional terrain or bathymetry

resources

wind conditions, sampled with stability

turbines

turbine models, per position

A scenario is a Farm, or a Cluster when n_farms is given or domain scatters a region of sites.

Where to go next#