90 lines
2.8 KiB
Python
90 lines
2.8 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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# coding: utf-8
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"""
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Adds dynamic line rating timeseries to the base network.
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Relevant Settings
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-----------------
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.. code:: yaml
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lines:
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cutout:
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line_rating:
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.. seealso::
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Documentation of the configuration file ``config.yaml`
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Inputs
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------
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- ``data/cutouts``:
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- ``networks/base.nc``: confer :ref:`base`
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Outputs
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-------
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- ``resources/line_rating.nc``
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Description
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-----------
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The rule :mod:`build_line_rating` calculates the line rating for transmission lines.
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The line rating provides the maximal capacity of a transmission line considering the heat exchange with the environment.
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The folloing heat gains and losses are considered:
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- heat gain through resistive losses
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- heat gain trough solar radiation
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- heat loss through radiation of the trasnmission line
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- heat loss through forced convection with wind
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- heat loss through natural convection
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With a heat balance considering the maximum temperature threshold of the tranmission line,
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the maximal possible capacity factor "s_max_pu" for each transmission line at each time step is calculated.
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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 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 Point, LineString as Line
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import atlite
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import xarray as xr
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def calculate_line_rating(n):
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relevant_lines=n.lines[(n.lines['underground']==False) & (n.lines['under_construction']==False)]
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buses = relevant_lines[["bus0", "bus1"]].values
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x = n.buses.x
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y = n.buses.y
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shapes = [Line([Point(x[b0], y[b0]), Point(x[b1], y[b1])]) for (b0, b1) in buses]
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shapes = gpd.GeoSeries(shapes, index=relevant_lines.index)
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cutout = atlite.Cutout(snakemake.input.cutout)
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if relevant_lines.r_pu.eq(0).all():
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#Overwrite standard line resistance with line resistance obtained from line type
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relevant_lines["r_pu"]=relevant_lines.join(n.line_types["r_per_length"], on=["type"])['r_per_length']/1000 #in meters
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Imax=cutout.line_rating(shapes, relevant_lines.r_pu)
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da = xr.DataArray(data=np.sqrt(3) * Imax * relevant_lines["v_nom"].values.reshape(-1,1) * relevant_lines["num_parallel"].values.reshape(-1,1)/1e3, #in mW
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attrs=dict(description="Maximal possible power in MW for given line considering line rating"))
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return da
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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_line_rating', network='elec', simpl='',
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clusters='6', ll='copt', opts='Co2L-24H')
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configure_logging(snakemake)
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n = pypsa.Network(snakemake.input.base_network)
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da=calculate_line_rating(n)
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da.to_netcdf(snakemake.output[0]) |