157 lines
4.5 KiB
Python
157 lines
4.5 KiB
Python
# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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"""
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Creates Voronoi shapes for each bus representing both onshore and offshore regions.
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Relevant Settings
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-----------------
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.. code:: yaml
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countries:
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.. seealso::
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Documentation of the configuration file ``config.yaml`` at
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:ref:`toplevel_cf`
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Inputs
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------
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- ``resources/country_shapes.geojson``: confer :ref:`shapes`
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- ``resources/offshore_shapes.geojson``: confer :ref:`shapes`
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- ``networks/base.nc``: confer :ref:`base`
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Outputs
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-------
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- ``resources/regions_onshore.geojson``:
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.. image:: ../img/regions_onshore.png
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:scale: 33 %
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- ``resources/regions_offshore.geojson``:
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.. image:: ../img/regions_offshore.png
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:scale: 33 %
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Description
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-----------
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"""
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import logging
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from _helpers import configure_logging
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import pypsa
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import os
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import pandas as pd
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import numpy as np
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import geopandas as gpd
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from shapely.geometry import Polygon
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from scipy.spatial import Voronoi
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logger = logging.getLogger(__name__)
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def save_to_geojson(s, fn):
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if os.path.exists(fn):
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os.unlink(fn)
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schema = {**gpd.io.file.infer_schema(s), 'geometry': 'Unknown'}
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s.to_file(fn, driver='GeoJSON', schema=schema)
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def voronoi_partition_pts(points, outline):
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"""
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Compute the polygons of a voronoi partition of `points` within the
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polygon `outline`. Taken from
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https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py
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Attributes
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----------
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points : Nx2 - ndarray[dtype=float]
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outline : Polygon
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Returns
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-------
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polygons : N - ndarray[dtype=Polygon|MultiPolygon]
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"""
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points = np.asarray(points)
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if len(points) == 1:
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polygons = [outline]
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else:
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xmin, ymin = np.amin(points, axis=0)
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xmax, ymax = np.amax(points, axis=0)
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xspan = xmax - xmin
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yspan = ymax - ymin
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# to avoid any network positions outside all Voronoi cells, append
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# the corners of a rectangle framing these points
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vor = Voronoi(np.vstack((points,
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[[xmin-3.*xspan, ymin-3.*yspan],
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[xmin-3.*xspan, ymax+3.*yspan],
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[xmax+3.*xspan, ymin-3.*yspan],
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[xmax+3.*xspan, ymax+3.*yspan]])))
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polygons = []
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for i in range(len(points)):
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poly = Polygon(vor.vertices[vor.regions[vor.point_region[i]]])
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if not poly.is_valid:
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poly = poly.buffer(0)
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poly = poly.intersection(outline)
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polygons.append(poly)
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return np.array(polygons, dtype=object)
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if __name__ == "__main__":
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if 'snakemake' not in globals():
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from _helpers import mock_snakemake
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snakemake = mock_snakemake('build_bus_regions')
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configure_logging(snakemake)
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countries = snakemake.config['countries']
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n = pypsa.Network(snakemake.input.base_network)
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country_shapes = gpd.read_file(snakemake.input.country_shapes).set_index('name')['geometry']
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offshore_shapes = gpd.read_file(snakemake.input.offshore_shapes).set_index('name')['geometry']
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onshore_regions = []
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offshore_regions = []
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for country in countries:
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c_b = n.buses.country == country
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onshore_shape = country_shapes[country]
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onshore_locs = n.buses.loc[c_b & n.buses.substation_lv, ["x", "y"]]
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onshore_regions.append(gpd.GeoDataFrame({
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'name': onshore_locs.index,
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'x': onshore_locs['x'],
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'y': onshore_locs['y'],
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'geometry': voronoi_partition_pts(onshore_locs.values, onshore_shape),
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'country': country
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}))
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if country not in offshore_shapes.index: continue
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offshore_shape = offshore_shapes[country]
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offshore_locs = n.buses.loc[c_b & n.buses.substation_off, ["x", "y"]]
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offshore_regions_c = gpd.GeoDataFrame({
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'name': offshore_locs.index,
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'x': offshore_locs['x'],
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'y': offshore_locs['y'],
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'geometry': voronoi_partition_pts(offshore_locs.values, offshore_shape),
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'country': country
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})
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offshore_regions_c = offshore_regions_c.loc[offshore_regions_c.area > 1e-2]
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offshore_regions.append(offshore_regions_c)
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save_to_geojson(pd.concat(onshore_regions, ignore_index=True), snakemake.output.regions_onshore)
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save_to_geojson(pd.concat(offshore_regions, ignore_index=True), snakemake.output.regions_offshore)
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