f38681f134
The source URL has changed. It represents the year 2012 and is only for buildings, not district heating. So the capacities for urban central are now set to zero from this source.
128 lines
4.5 KiB
Python
128 lines
4.5 KiB
Python
# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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"""
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Builds table of existing heat generation capacities for initial planning
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horizon.
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"""
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import country_converter as coco
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import numpy as np
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import pandas as pd
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cc = coco.CountryConverter()
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def build_existing_heating():
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# retrieve existing heating capacities
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# Add existing heating capacities, data comes from the study
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# "Mapping and analyses of the current and future (2020 - 2030)
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# heating/cooling fuel deployment (fossil/renewables) "
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# https://energy.ec.europa.eu/publications/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment-fossilrenewables-1_en
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# file: "WP2_DataAnnex_1_BuildingTechs_ForPublication_201603.xls" -> "existing_heating_raw.csv".
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# data is for buildings only (i.e. NOT district heating) and represents the year 2012
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# TODO start from original file
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existing_heating = pd.read_csv(snakemake.input.existing_heating,
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index_col=0,
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header=0)
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# data for Albania, Montenegro and Macedonia not included in database
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existing_heating.loc["Albania"] = np.nan
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existing_heating.loc["Montenegro"] = np.nan
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existing_heating.loc["Macedonia"] = np.nan
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existing_heating.fillna(0.0, inplace=True)
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# convert GW to MW
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existing_heating *= 1e3
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existing_heating.index = cc.convert(existing_heating.index, to="iso2")
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# coal and oil boilers are assimilated to oil boilers
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existing_heating["oil boiler"] = (
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existing_heating["oil boiler"] + existing_heating["coal boiler"]
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)
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existing_heating.drop(["coal boiler"], axis=1, inplace=True)
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# distribute technologies to nodes by population
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pop_layout = pd.read_csv(snakemake.input.clustered_pop_layout, index_col=0)
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nodal_heating = existing_heating.loc[pop_layout.ct]
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nodal_heating.index = pop_layout.index
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nodal_heating = nodal_heating.multiply(pop_layout.fraction, axis=0)
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district_heat_info = pd.read_csv(snakemake.input.district_heat_share, index_col=0)
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dist_fraction = district_heat_info["district fraction of node"]
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urban_fraction = district_heat_info["urban fraction"]
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energy_layout = pd.read_csv(
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snakemake.input.clustered_pop_energy_layout, index_col=0
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)
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uses = ["space", "water"]
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sectors = ["residential", "services"]
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nodal_sectoral_totals = pd.DataFrame(dtype=float)
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for sector in sectors:
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nodal_sectoral_totals[sector] = energy_layout[
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[f"total {sector} {use}" for use in uses]
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].sum(axis=1)
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nodal_sectoral_fraction = nodal_sectoral_totals.div(
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nodal_sectoral_totals.sum(axis=1), axis=0
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)
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nodal_heat_name_fraction = pd.DataFrame(index=district_heat_info.index,
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dtype=float)
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nodal_heat_name_fraction["urban central"] = 0.
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for sector in sectors:
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nodal_heat_name_fraction[f"{sector} rural"] = nodal_sectoral_fraction[sector]*(1 - urban_fraction)
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nodal_heat_name_fraction[f"{sector} urban decentral"] = nodal_sectoral_fraction[sector]*urban_fraction
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nodal_heat_name_tech = pd.concat(
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{
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name: nodal_heating.multiply(nodal_heat_name_fraction[name], axis=0)
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for name in nodal_heat_name_fraction.columns
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},
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axis=1,
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names=["heat name", "technology"],
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)
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# move all ground HPs to rural, all air to urban
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for sector in sectors:
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nodal_heat_name_tech[(f"{sector} rural", "ground heat pump")] += (
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nodal_heat_name_tech[("urban central", "ground heat pump")]
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* nodal_sectoral_fraction[sector]
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+ nodal_heat_name_tech[(f"{sector} urban decentral", "ground heat pump")]
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)
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nodal_heat_name_tech[(f"{sector} urban decentral", "ground heat pump")] = 0.0
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nodal_heat_name_tech[
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(f"{sector} urban decentral", "air heat pump")
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] += nodal_heat_name_tech[(f"{sector} rural", "air heat pump")]
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nodal_heat_name_tech[(f"{sector} rural", "air heat pump")] = 0.0
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nodal_heat_name_tech[("urban central", "ground heat pump")] = 0.0
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nodal_heat_name_tech.to_csv(snakemake.output.existing_heating_distribution)
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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(
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"build_existing_heating_distribution",
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simpl="",
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clusters=48,
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planning_horizons=2050,
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)
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build_existing_heating()
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