pypsa-eur/scripts/prepare_links_p_nom.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# SPDX-FileCopyrightText: : 2017-2024 The PyPSA-Eur Authors
#
# SPDX-License-Identifier: MIT
"""
Extracts capacities of HVDC links from `Wikipedia.

<https://en.wikipedia.org/wiki/List_of_HVDC_projects>`_.

Relevant Settings
-----------------

.. code:: yaml

    enable:
        prepare_links_p_nom:

.. seealso::
    Documentation of the configuration file ``config/config.yaml`` at
    :ref:`toplevel_cf`

Inputs
------

*None*

Outputs
-------

- ``data/links_p_nom.csv``: A plain download of https://en.wikipedia.org/wiki/List_of_HVDC_projects#Europe plus extracted coordinates.

Description
-----------

*None*
"""

import logging

import pandas as pd
from _helpers import configure_logging, set_scenario_config

logger = logging.getLogger(__name__)


def multiply(s):
    return s.str[0].astype(float) * s.str[1].astype(float)


def extract_coordinates(s):
    regex = (
        r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(N|S) " r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(E|W)"
    )
    e = s.str.extract(regex, expand=True)
    lat = (
        e[0].astype(float) + (e[1].astype(float) + e[2].astype(float) / 60.0) / 60.0
    ) * e[3].map({"N": +1.0, "S": -1.0})
    lon = (
        e[4].astype(float) + (e[5].astype(float) + e[6].astype(float) / 60.0) / 60.0
    ) * e[7].map({"E": +1.0, "W": -1.0})
    return lon, lat


if __name__ == "__main__":
    if "snakemake" not in globals():
        from _helpers import mock_snakemake  # rule must be enabled in config

        snakemake = mock_snakemake("prepare_links_p_nom", simpl="")
    configure_logging(snakemake)
    set_scenario_config(snakemake)

    links_p_nom = pd.read_html(
        "https://en.wikipedia.org/wiki/List_of_HVDC_projects", header=0, match="SwePol"
    )[0]

    mw = "Power (MW)"
    m_b = links_p_nom[mw].str.contains("x").fillna(False)

    links_p_nom.loc[m_b, mw] = links_p_nom.loc[m_b, mw].str.split("x").pipe(multiply)
    links_p_nom[mw] = (
        links_p_nom[mw].str.extract("[-/]?([\d.]+)", expand=False).astype(float)
    )

    links_p_nom["x1"], links_p_nom["y1"] = extract_coordinates(
        links_p_nom["Converterstation 1"]
    )
    links_p_nom["x2"], links_p_nom["y2"] = extract_coordinates(
        links_p_nom["Converterstation 2"]
    )

    links_p_nom.dropna(subset=["x1", "y1", "x2", "y2"]).to_csv(
        snakemake.output[0], index=False
    )