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📥 Data Input

Concepts: Graph representations Reference: Input Formats Network/Router API: 📥 Data Input

There are 4 alternatives to import wind farm layout data for use within OptiWindNet:

  • NumPy arrays through the OptiWindNet API

  • windIO YAML file

  • .yaml file (OptiWindNet schema)

  • .osm.pbf file

The formats themselves are specified in Supported formats; this notebook shows the loader function for each.

[1]:

from optiwindnet.svg import svgplot

NumPy arrays and the OptiWindNet API

[2]:

from itertools import pairwise

import numpy as np

[3]:

from optiwindnet.converting import L_from_site

[4]:

# all coordinates are sequences of (x, y) pairs
# if input coordinates are in arrays X and Y, use `np.column_stack((X, Y))`
# the coordinate sequence defines the polygon, last-first segment implicit
border = np.array(
    [[1951, 200], [1951, 1383], [386, 1383], [650, 708], [624, 678],
     [4, 1036], [4, 3], [1152, 3], [917, 819], [957, 854]],
    dtype=float)  # fmt: skip
# 'obstacles' is an optional location attribute
obstacles = [
    # - obstacles must be strictly inside the border polygon
    # - undefined behavior if obstacles and border overlap
    # first obstacle
    np.array([[1540, 920], [1600, 940], [1600, 1150], [1400, 1200]]),
    # [second obstacle] ...
]
substations = np.array([[696, 1063]], dtype=float)
turbines = np.array(
    [[1940, 279], [1920, 703], [1475, 696], [1839, 1250],
     [1277, 1296], [442, 1359], [737, 435], [1060, 26],
     [522, 176], [87, 35], [184, 417], [71, 878]],
    dtype=float)  # fmt: skip
R = substations.shape[0]
T = turbines.shape[0]
border_sizes = np.array(
    [border.shape[0]] + [obstacle.shape[0] for obstacle in obstacles]
)
B = border_sizes.sum()
obstacle_idxs = np.cumsum(border_sizes) + T

[5]:

L = L_from_site(
    R=R,
    T=T,
    B=B,
    border=np.arange(T, T + border.shape[0]),
    obstacles=[np.arange(a, b) for a, b in pairwise(obstacle_idxs)],
    name='Example Location',
    handle='example',
    VertexC=np.vstack((turbines, border, *obstacles, substations)),
)
svgplot(L)

[5]:
../_images/notebooks_lo11_data_input_8_0.svg

windIO YAML file

See windIO YAML and the windIO documentation for more information on that format.

[6]:

from optiwindnet.importer import L_from_windIO

[7]:

L = L_from_windIO('data/IEA37_Borssele_Irregular_System.yaml')
svgplot(L)

[7]:
../_images/notebooks_lo11_data_input_12_0.svg

YAML input file

[8]:

from optiwindnet.importer import L_from_yaml

The example YAML file is bundled with the source distribution; this notebook reads it without creating or modifying files.

[9]:

L = L_from_yaml('data/example_location.yaml')
svgplot(L)

[9]:
../_images/notebooks_lo11_data_input_16_0.svg

.osm.pbf input file (OpenStreetMap Protocol Buffer Format)

The JOSM open-source map editor is recommended if using this format: https://josm.openstreetmap.de/. In addition, the JOSM plugin pbf is required to save in the .osm.pbf format. The plugin opendata is useful for importing many common GIS file formats.

The OpenStreetMap tagging conventions OptiWindNet expects — which tags mark turbines, substations, the border and the obstacles — are described in OpenStreetMap PBF.

See optiwindnet/data/*.osm.pbf for more examples.

[10]:

from optiwindnet.importer import L_from_pbf

[11]:

L = L_from_pbf('data/example_location.osm.pbf')
svgplot(L)

[11]:
../_images/notebooks_lo11_data_input_22_0.svg