68 lines
2.1 KiB
Python
68 lines
2.1 KiB
Python
# coding: utf-8
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import logging
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import numpy as np
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import pandas as pd
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from scipy.spatial import cKDTree as KDTree
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import pycountry as pyc
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import pypsa
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import powerplantmatching as ppm
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def country_alpha_2(name):
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try:
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cntry = pyc.countries.get(name=name)
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except KeyError:
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cntry = None
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if cntry is None:
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cntry = pyc.countries.get(official_name=name)
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return cntry.alpha_2
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if 'snakemake' not in globals():
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from vresutils.snakemake import MockSnakemake, Dict
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snakemake = MockSnakemake(
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input=Dict(base_network='networks/base.nc'),
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output=['resources/powerplants.csv']
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)
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logging.basicConfig(level=snakemake.config['logging_level'])
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n = pypsa.Network(snakemake.input.base_network)
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ppl = (ppm.collection.matched_data()
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[lambda df : ~df.Fueltype.isin(('Solar', 'Wind'))]
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.pipe(ppm.cleaning.clean_technology)
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.assign(Fueltype=lambda df: (
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df.Fueltype.where(df.Fueltype != 'Natural Gas',
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df.Technology.replace('Steam Turbine', 'OCGT').fillna('OCGT'))))
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.pipe(ppm.utils.fill_geoposition))
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# ppl.loc[(ppl.Fueltype == 'Other') & ppl.Technology.str.contains('CCGT'), 'Fueltype'] = 'CCGT'
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# ppl.loc[(ppl.Fueltype == 'Other') & ppl.Technology.str.contains('Steam Turbine'), 'Fueltype'] = 'CCGT'
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ppl = ppl.loc[ppl.lon.notnull() & ppl.lat.notnull()]
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ppl_country = ppl.Country.map(country_alpha_2)
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countries = n.buses.country.unique()
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cntries_without_ppl = []
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for cntry in countries:
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substation_lv_i = n.buses.index[n.buses['substation_lv'] & (n.buses.country == cntry)]
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ppl_b = ppl_country == cntry
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if not ppl_b.any():
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cntries_without_ppl.append(cntry)
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continue
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kdtree = KDTree(n.buses.loc[substation_lv_i, ['x','y']].values)
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ppl.loc[ppl_b, 'bus'] = substation_lv_i[kdtree.query(ppl.loc[ppl_b, ['lon','lat']].values)[1]]
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if cntries_without_ppl:
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logging.warning("No powerplants known in: {}".format(", ".join(cntries_without_ppl)))
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bus_null_b = ppl["bus"].isnull()
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if bus_null_b.any():
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logging.warning("Couldn't find close bus for {} powerplants".format(bus_null_b.sum()))
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ppl.to_csv(snakemake.output[0])
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