Merge remote-tracking branch 'origin/master' into country-specific-dh-forward-temperatures
This commit is contained in:
AmosSchledorn
commit
6c9bcae6f0
@ -67,7 +67,6 @@ snapshots:
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# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#enable
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enable:
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retrieve: auto
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prepare_links_p_nom: false
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retrieve_databundle: true
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retrieve_cost_data: true
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build_cutout: false
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@ -370,6 +369,23 @@ biomass:
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- Sludge
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municipal solid waste:
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- Municipal waste
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share_unsustainable_use_retained:
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2020: 1
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2025: 0.66
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2030: 0.33
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2035: 0
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2040: 0
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2045: 0
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2050: 0
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share_sustainable_potential_available:
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2020: 0
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2025: 0.33
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2030: 0.66
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2035: 1
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2040: 1
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2045: 1
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2050: 1
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# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solar-thermal
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solar_thermal:
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@ -749,7 +765,7 @@ industry:
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# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#costs
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costs:
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year: 2030
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version: v0.9.0
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version: v0.9.1
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social_discountrate: 0.02
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fill_values:
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FOM: 0
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@ -1067,6 +1083,7 @@ plotting:
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services rural biomass boiler: '#c6cf98'
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services urban decentral biomass boiler: '#dde5b5'
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biomass to liquid: '#32CD32'
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unsustainable bioliquids: '#32CD32'
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electrobiofuels: 'red'
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BioSNG: '#123456'
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# power transmission
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@ -53,7 +53,6 @@ extensions = [
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autodoc_mock_imports = [
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"atlite",
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"snakemake",
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"pycountry",
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"rioxarray",
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"country_converter",
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"tabula",
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@ -5,3 +5,5 @@ classes ,,,
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-- solid biomass,--,Array of biomass comodity,The comodity that are included as solid biomass
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-- not included,--,Array of biomass comodity,The comodity that are not included as a biomass potential
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-- biogas,--,Array of biomass comodity,The comodity that are included as biogas
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share_unsustainable_use_retained,--,Dictionary with planning horizons as keys., Share of unsustainable biomass use retained using primary production of Eurostat data as reference
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share_sustainable_potential_available,--,Dictionary with planning horizons as keys., Share determines phase-in of ENSPRESO biomass potentials
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|
@ -1,6 +1,5 @@
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,Unit,Values,Description
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enable,str or bool,"{auto, true, false}","Switch to include (true) or exclude (false) the retrieve_* rules of snakemake into the workflow; 'auto' sets true|false based on availability of an internet connection to prevent issues with snakemake failing due to lack of internet connection."
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prepare_links_p_nom,bool,"{true, false}","Switch to retrieve current HVDC projects from `Wikipedia <https://en.wikipedia.org/wiki/List_of_HVDC_projects>`_"
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retrieve_databundle,bool,"{true, false}","Switch to retrieve databundle from zenodo via the rule :mod:`retrieve_databundle` or whether to keep a custom databundle located in the corresponding folder."
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retrieve_cost_data,bool,"{true, false}","Switch to retrieve technology cost data from `technology-data repository <https://github.com/PyPSA/technology-data>`_."
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build_cutout,bool,"{true, false}","Switch to enable the building of cutouts via the rule :mod:`build_cutout`."
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|
@ -41,11 +41,6 @@ Rule ``build_cutout``
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.. automodule:: build_cutout
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Rule ``prepare_links_p_nom``
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===============================
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.. automodule:: prepare_links_p_nom
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.. _base:
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Rule ``base_network``
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@ -12,6 +12,12 @@ Upcoming Release
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* Added option to use country-specific district heating forward and return temperatures. Defaults to lower temperatures in Scandinavia.
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* Added unsustainable biomass potentials for solid, gaseous, and liquid biomass. The potentials can be phased-out and/or
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substituted by the phase-in of sustainable biomass types using the config parameters
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``biomass: share_unsustainable_use_retained`` and ``biomass: share_sustainable_potential_available``.
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* The rule ``prepare_links_p_nom`` was removed since it was outdated and not used.
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* Changed heat pump COP approximation for central heating to be based on `Jensen et al. (2018) <https://backend.orbit.dtu.dk/ws/portalfiles/portal/151965635/MAIN_Final.pdf>`__ and a default forward temperature of 90C. This is more realistic for district heating than the previously used approximation method.
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* split solid biomass potentials into solid biomass and municipal solid waste. Add option to use municipal solid waste. This option is only activated in combination with the flag ``waste_to_energy``
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@ -17,7 +17,6 @@ tabula-py
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# cartopy
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scikit-learn
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pycountry
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pyyaml
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seaborn
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memory_profiler
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@ -18,7 +18,6 @@ dependencies:
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# Dependencies of the workflow itself
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- xlrd
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- openpyxl!=3.1.1
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- pycountry
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- seaborn
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- snakemake-minimal>=8.14
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- memory_profiler
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@ -2,21 +2,6 @@
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#
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# SPDX-License-Identifier: MIT
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if config["enable"].get("prepare_links_p_nom", False):
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rule prepare_links_p_nom:
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output:
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"data/links_p_nom.csv",
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log:
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logs("prepare_links_p_nom.log"),
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threads: 1
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resources:
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mem_mb=1500,
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/prepare_links_p_nom.py"
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rule build_electricity_demand:
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params:
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@ -106,8 +91,8 @@ rule build_shapes:
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params:
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countries=config_provider("countries"),
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input:
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naturalearth=ancient("data/bundle/naturalearth/ne_10m_admin_0_countries.shp"),
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eez=ancient("data/bundle/eez/World_EEZ_v8_2014.shp"),
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naturalearth=ancient("data/naturalearth/ne_10m_admin_0_countries_deu.shp"),
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eez=ancient("data/eez/World_EEZ_v12_20231025_gpkg/eez_v12.gpkg"),
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nuts3=ancient("data/bundle/NUTS_2013_60M_SH/data/NUTS_RG_60M_2013.shp"),
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nuts3pop=ancient("data/bundle/nama_10r_3popgdp.tsv.gz"),
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nuts3gdp=ancient("data/bundle/nama_10r_3gdp.tsv.gz"),
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@ -347,7 +347,8 @@ rule build_biomass_potentials:
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"https://zenodo.org/records/10356004/files/ENSPRESO_BIOMASS.xlsx",
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keep_local=True,
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),
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nuts2="data/bundle/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson", # https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/#nuts21
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eurostat="data/eurostat/Balances-April2023",
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nuts2="data/bundle/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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nuts3_population=ancient("data/bundle/nama_10r_3popgdp.tsv.gz"),
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swiss_cantons=ancient("data/ch_cantons.csv"),
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@ -360,7 +361,7 @@ rule build_biomass_potentials:
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biomass_potentials=resources(
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"biomass_potentials_s{simpl}_{clusters}_{planning_horizons}.csv"
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),
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threads: 1
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threads: 8
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resources:
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mem_mb=1000,
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log:
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@ -956,6 +957,7 @@ rule prepare_sector_network:
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countries=config_provider("countries"),
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adjustments=config_provider("adjustments", "sector"),
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emissions_scope=config_provider("energy", "emissions"),
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biomass=config_provider("biomass"),
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RDIR=RDIR,
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heat_pump_sources=config_provider("sector", "heat_pump_sources"),
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heat_systems=config_provider("sector", "heat_systems"),
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@ -4,6 +4,7 @@
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import requests
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from datetime import datetime, timedelta
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from shutil import move, unpack_archive
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if config["enable"].get("retrieve", "auto") == "auto":
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config["enable"]["retrieve"] = has_internet_access()
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@ -15,8 +16,6 @@ if config["enable"]["retrieve"] is False:
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if config["enable"]["retrieve"] and config["enable"].get("retrieve_databundle", True):
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datafiles = [
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"je-e-21.03.02.xls",
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"eez/World_EEZ_v8_2014.shp",
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"naturalearth/ne_10m_admin_0_countries.shp",
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"NUTS_2013_60M_SH/data/NUTS_RG_60M_2013.shp",
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"nama_10r_3popgdp.tsv.gz",
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"nama_10r_3gdp.tsv.gz",
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@ -215,6 +214,64 @@ if config["enable"]["retrieve"]:
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move(input[0], output[0])
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||||
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if config["enable"]["retrieve"]:
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rule retrieve_eez:
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params:
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zip="data/eez/World_EEZ_v12_20231025_gpkg.zip",
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output:
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gpkg="data/eez/World_EEZ_v12_20231025_gpkg/eez_v12.gpkg",
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run:
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import os
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import requests
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from uuid import uuid4
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name = str(uuid4())[:8]
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org = str(uuid4())[:8]
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response = requests.post(
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"https://www.marineregions.org/download_file.php",
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params={"name": "World_EEZ_v12_20231025_gpkg.zip"},
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data={
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"name": name,
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"organisation": org,
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"email": f"{name}@{org}.org",
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"country": "Germany",
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"user_category": "academia",
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"purpose_category": "Research",
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"agree": "1",
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||||
},
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||||
)
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|
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with open(params["zip"], "wb") as f:
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f.write(response.content)
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output_folder = Path(params["zip"]).parent
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unpack_archive(params["zip"], output_folder)
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os.remove(params["zip"])
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|
||||
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||||
|
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if config["enable"]["retrieve"]:
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# Download directly from naciscdn.org which is a redirect from naturalearth.com
|
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# (https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-countries/)
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# Use point-of-view (POV) variant of Germany so that Crimea is included.
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rule retrieve_naturalearth_countries:
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input:
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storage(
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||||
"https://naciscdn.org/naturalearth/10m/cultural/ne_10m_admin_0_countries_deu.zip"
|
||||
),
|
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params:
|
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zip="data/naturalearth/ne_10m_admin_0_countries_deu.zip",
|
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output:
|
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countries="data/naturalearth/ne_10m_admin_0_countries_deu.shp",
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run:
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move(input[0], params["zip"])
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output_folder = Path(output["countries"]).parent
|
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unpack_archive(params["zip"], output_folder)
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os.remove(params["zip"])
|
||||
|
||||
|
||||
if config["enable"]["retrieve"]:
|
||||
# Some logic to find the correct file URL
|
||||
# Sometimes files are released delayed or ahead of schedule, check which file is currently available
|
||||
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@ -13,11 +13,51 @@ import geopandas as gpd
|
||||
import numpy as np
|
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import pandas as pd
|
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from _helpers import configure_logging, set_scenario_config
|
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from build_energy_totals import build_eurostat
|
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|
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logger = logging.getLogger(__name__)
|
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AVAILABLE_BIOMASS_YEARS = [2010, 2020, 2030, 2040, 2050]
|
||||
|
||||
|
||||
def _calc_unsustainable_potential(df, df_unsustainable, share_unsus, resource_type):
|
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"""
|
||||
Calculate the unsustainable biomass potential for a given resource type or
|
||||
regex.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
df : pd.DataFrame
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The dataframe with sustainable biomass potentials.
|
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df_unsustainable : pd.DataFrame
|
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The dataframe with unsustainable biomass potentials.
|
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share_unsus : float
|
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The share of unsustainable biomass potential retained.
|
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resource_type : str or regex
|
||||
The resource type to calculate the unsustainable potential for.
|
||||
|
||||
Returns
|
||||
-------
|
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pd.Series
|
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The unsustainable biomass potential for the given resource type or regex.
|
||||
"""
|
||||
|
||||
if "|" in resource_type:
|
||||
resource_potential = df_unsustainable.filter(regex=resource_type).sum(axis=1)
|
||||
else:
|
||||
resource_potential = df_unsustainable[resource_type]
|
||||
|
||||
return (
|
||||
df.apply(
|
||||
lambda c: c.sum()
|
||||
/ df.loc[df.index.str[:2] == c.name[:2]].sum().sum()
|
||||
* resource_potential.loc[c.name[:2]],
|
||||
axis=1,
|
||||
)
|
||||
.mul(share_unsus)
|
||||
.clip(lower=0)
|
||||
)
|
||||
|
||||
|
||||
def build_nuts_population_data(year=2013):
|
||||
pop = pd.read_csv(
|
||||
snakemake.input.nuts3_population,
|
||||
@ -211,15 +251,104 @@ def convert_nuts2_to_regions(bio_nuts2, regions):
|
||||
return bio_regions
|
||||
|
||||
|
||||
def add_unsustainable_potentials(df):
|
||||
"""
|
||||
Add unsustainable biomass potentials to the given dataframe. The difference
|
||||
between the data of JRC and Eurostat is assumed to be unsustainable
|
||||
biomass.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
df : pd.DataFrame
|
||||
The dataframe with sustainable biomass potentials.
|
||||
unsustainable_biomass : str
|
||||
Path to the file with unsustainable biomass potentials.
|
||||
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
The dataframe with added unsustainable biomass potentials.
|
||||
"""
|
||||
if "GB" in snakemake.config["countries"]:
|
||||
latest_year = 2019
|
||||
else:
|
||||
latest_year = 2021
|
||||
idees_rename = {"GR": "EL", "GB": "UK"}
|
||||
df_unsustainable = (
|
||||
build_eurostat(
|
||||
countries=snakemake.config["countries"],
|
||||
input_eurostat=snakemake.input.eurostat,
|
||||
nprocesses=int(snakemake.threads),
|
||||
)
|
||||
.xs(
|
||||
max(min(latest_year, int(snakemake.wildcards.planning_horizons)), 1990),
|
||||
level=1,
|
||||
)
|
||||
.xs("Primary production", level=2)
|
||||
.droplevel([1, 2, 3])
|
||||
)
|
||||
|
||||
df_unsustainable.index = df_unsustainable.index.str.strip()
|
||||
df_unsustainable = df_unsustainable.rename(
|
||||
{v: k for k, v in idees_rename.items()}, axis=0
|
||||
)
|
||||
|
||||
bio_carriers = [
|
||||
"Primary solid biofuels",
|
||||
"Biogases",
|
||||
"Renewable municipal waste",
|
||||
"Pure biogasoline",
|
||||
"Blended biogasoline",
|
||||
"Pure biodiesels",
|
||||
"Blended biodiesels",
|
||||
"Pure bio jet kerosene",
|
||||
"Blended bio jet kerosene",
|
||||
"Other liquid biofuels",
|
||||
]
|
||||
|
||||
df_unsustainable = df_unsustainable[bio_carriers]
|
||||
|
||||
# Phase out unsustainable biomass potentials linearly from 2020 to 2035 while phasing in sustainable potentials
|
||||
share_unsus = params.get("share_unsustainable_use_retained").get(investment_year)
|
||||
|
||||
df_wo_ch = df.drop(df.filter(regex="CH\d", axis=0).index)
|
||||
|
||||
# Calculate unsustainable solid biomass
|
||||
df_wo_ch["unsustainable solid biomass"] = _calc_unsustainable_potential(
|
||||
df_wo_ch, df_unsustainable, share_unsus, "Primary solid biofuels"
|
||||
)
|
||||
|
||||
# Calculate unsustainable biogas
|
||||
df_wo_ch["unsustainable biogas"] = _calc_unsustainable_potential(
|
||||
df_wo_ch, df_unsustainable, share_unsus, "Biogases"
|
||||
)
|
||||
|
||||
# Calculate unsustainable bioliquids
|
||||
df_wo_ch["unsustainable bioliquids"] = _calc_unsustainable_potential(
|
||||
df_wo_ch,
|
||||
df_unsustainable,
|
||||
share_unsus,
|
||||
resource_type="gasoline|diesel|kerosene|liquid",
|
||||
)
|
||||
|
||||
share_sus = params.get("share_sustainable_potential_available").get(investment_year)
|
||||
df *= share_sus
|
||||
|
||||
df = df.join(df_wo_ch.filter(like="unsustainable")).fillna(0)
|
||||
|
||||
return df
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if "snakemake" not in globals():
|
||||
|
||||
from _helpers import mock_snakemake
|
||||
|
||||
snakemake = mock_snakemake(
|
||||
"build_biomass_potentials",
|
||||
simpl="",
|
||||
clusters="5",
|
||||
planning_horizons=2050,
|
||||
clusters="37",
|
||||
planning_horizons=2020,
|
||||
)
|
||||
|
||||
configure_logging(snakemake)
|
||||
@ -269,6 +398,8 @@ if __name__ == "__main__":
|
||||
grouper = {v: k for k, vv in params["classes"].items() for v in vv}
|
||||
df = df.T.groupby(grouper).sum().T
|
||||
|
||||
df = add_unsustainable_potentials(df)
|
||||
|
||||
df *= 1e6 # TWh/a to MWh/a
|
||||
df.index.name = "MWh/a"
|
||||
|
||||
|
||||
@ -26,7 +26,7 @@ Inputs
|
||||
.. image:: img/countries.png
|
||||
:scale: 33 %
|
||||
|
||||
- ``data/bundle/eez/World_EEZ_v8_2014.shp``: World `exclusive economic zones <https://en.wikipedia.org/wiki/Exclusive_economic_zone>`_ (EEZ)
|
||||
- ``data/eez/World_EEZ_v12_20231025_gpkg/eez_v12.gpkg ``: World `exclusive economic zones <https://en.wikipedia.org/wiki/Exclusive_economic_zone>`_ (EEZ)
|
||||
|
||||
.. image:: img/eez.png
|
||||
:scale: 33 %
|
||||
@ -73,22 +73,16 @@ from functools import reduce
|
||||
from itertools import takewhile
|
||||
from operator import attrgetter
|
||||
|
||||
import country_converter as coco
|
||||
import geopandas as gpd
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import pycountry as pyc
|
||||
from _helpers import configure_logging, set_scenario_config
|
||||
from shapely.geometry import MultiPolygon, Polygon
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def _get_country(target, **keys):
|
||||
assert len(keys) == 1
|
||||
try:
|
||||
return getattr(pyc.countries.get(**keys), target)
|
||||
except (KeyError, AttributeError):
|
||||
return np.nan
|
||||
cc = coco.CountryConverter()
|
||||
|
||||
|
||||
def _simplify_polys(polys, minarea=0.1, tolerance=None, filterremote=True):
|
||||
@ -135,22 +129,15 @@ def countries(naturalearth, country_list):
|
||||
return s
|
||||
|
||||
|
||||
def eez(country_shapes, eez, country_list):
|
||||
def eez(eez, country_list):
|
||||
df = gpd.read_file(eez)
|
||||
df = df.loc[
|
||||
df["ISO_3digit"].isin(
|
||||
[_get_country("alpha_3", alpha_2=c) for c in country_list]
|
||||
)
|
||||
]
|
||||
df["name"] = df["ISO_3digit"].map(lambda c: _get_country("alpha_2", alpha_3=c))
|
||||
iso3_list = cc.convert(country_list, src="ISO2", to="ISO3")
|
||||
df = df.query("ISO_TER1 in @iso3_list and POL_TYPE == '200NM'").copy()
|
||||
df["name"] = cc.convert(df.ISO_TER1, src="ISO3", to="ISO2")
|
||||
s = df.set_index("name").geometry.map(
|
||||
lambda s: _simplify_polys(s, filterremote=False)
|
||||
)
|
||||
s = gpd.GeoSeries(
|
||||
{k: v for k, v in s.items() if v.distance(country_shapes[k]) < 1e-3},
|
||||
crs=df.crs,
|
||||
)
|
||||
s = s.to_frame("geometry")
|
||||
s = s.to_frame("geometry").set_crs(df.crs)
|
||||
s.index.name = "name"
|
||||
return s
|
||||
|
||||
@ -262,9 +249,7 @@ if __name__ == "__main__":
|
||||
country_shapes = countries(snakemake.input.naturalearth, snakemake.params.countries)
|
||||
country_shapes.reset_index().to_file(snakemake.output.country_shapes)
|
||||
|
||||
offshore_shapes = eez(
|
||||
country_shapes, snakemake.input.eez, snakemake.params.countries
|
||||
)
|
||||
offshore_shapes = eez(snakemake.input.eez, snakemake.params.countries)
|
||||
offshore_shapes.reset_index().to_file(snakemake.output.offshore_shapes)
|
||||
|
||||
europe_shape = gpd.GeoDataFrame(
|
||||
|
||||
@ -1,95 +0,0 @@
|
||||
#!/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
|
||||
)
|
||||
@ -63,6 +63,7 @@ def define_spatial(nodes, options):
|
||||
|
||||
if options.get("biomass_spatial", options["biomass_transport"]):
|
||||
spatial.biomass.nodes = nodes + " solid biomass"
|
||||
spatial.biomass.bioliquids = nodes + " bioliquids"
|
||||
spatial.biomass.locations = nodes
|
||||
spatial.biomass.industry = nodes + " solid biomass for industry"
|
||||
spatial.biomass.industry_cc = nodes + " solid biomass for industry CC"
|
||||
@ -70,6 +71,7 @@ def define_spatial(nodes, options):
|
||||
spatial.msw.locations = nodes
|
||||
else:
|
||||
spatial.biomass.nodes = ["EU solid biomass"]
|
||||
spatial.biomass.bioliquids = ["EU unsustainable bioliquids"]
|
||||
spatial.biomass.locations = ["EU"]
|
||||
spatial.biomass.industry = ["solid biomass for industry"]
|
||||
spatial.biomass.industry_cc = ["solid biomass for industry CC"]
|
||||
@ -2261,8 +2263,14 @@ def add_biomass(n, costs):
|
||||
biogas_potentials_spatial = biomass_potentials["biogas"].rename(
|
||||
index=lambda x: x + " biogas"
|
||||
)
|
||||
unsustainable_biogas_potentials_spatial = biomass_potentials[
|
||||
"unsustainable biogas"
|
||||
].rename(index=lambda x: x + " biogas")
|
||||
else:
|
||||
biogas_potentials_spatial = biomass_potentials["biogas"].sum()
|
||||
unsustainable_biogas_potentials_spatial = biomass_potentials[
|
||||
"unsustainable biogas"
|
||||
].sum()
|
||||
|
||||
if options.get("biomass_spatial", options["biomass_transport"]):
|
||||
solid_biomass_potentials_spatial = biomass_potentials["solid biomass"].rename(
|
||||
@ -2271,11 +2279,27 @@ def add_biomass(n, costs):
|
||||
msw_biomass_potentials_spatial = biomass_potentials[
|
||||
"municipal solid waste"
|
||||
].rename(index=lambda x: x + " municipal solid waste")
|
||||
unsustainable_solid_biomass_potentials_spatial = biomass_potentials[
|
||||
"unsustainable solid biomass"
|
||||
].rename(index=lambda x: x + " solid biomass")
|
||||
|
||||
else:
|
||||
solid_biomass_potentials_spatial = biomass_potentials["solid biomass"].sum()
|
||||
msw_biomass_potentials_spatial = biomass_potentials[
|
||||
"municipal solid waste"
|
||||
].sum()
|
||||
unsustainable_solid_biomass_potentials_spatial = biomass_potentials[
|
||||
"unsustainable solid biomass"
|
||||
].sum()
|
||||
|
||||
if options["regional_oil_demand"]:
|
||||
unsustainable_liquid_biofuel_potentials_spatial = biomass_potentials[
|
||||
"unsustainable bioliquids"
|
||||
].rename(index=lambda x: x + " bioliquids")
|
||||
else:
|
||||
unsustainable_liquid_biofuel_potentials_spatial = biomass_potentials[
|
||||
"unsustainable bioliquids"
|
||||
].sum()
|
||||
|
||||
n.add("Carrier", "biogas")
|
||||
n.add("Carrier", "solid biomass")
|
||||
@ -2400,6 +2424,81 @@ def add_biomass(n, costs):
|
||||
p_nom_extendable=True,
|
||||
)
|
||||
|
||||
if biomass_potentials.filter(like="unsustainable").sum().sum() > 0:
|
||||
|
||||
# Create timeseries to force usage of unsustainable potentials
|
||||
e_max_pu = pd.DataFrame(1, index=n.snapshots, columns=spatial.gas.biogas)
|
||||
e_max_pu.iloc[-1] = 0
|
||||
|
||||
n.madd(
|
||||
"Store",
|
||||
spatial.gas.biogas,
|
||||
suffix=" unsustainable",
|
||||
bus=spatial.gas.biogas,
|
||||
carrier="unsustainable biogas",
|
||||
e_nom=unsustainable_biogas_potentials_spatial,
|
||||
marginal_cost=costs.at["biogas", "fuel"],
|
||||
e_initial=unsustainable_biogas_potentials_spatial,
|
||||
e_nom_extendable=False,
|
||||
e_max_pu=e_max_pu,
|
||||
)
|
||||
|
||||
e_max_pu = pd.DataFrame(1, index=n.snapshots, columns=spatial.biomass.nodes)
|
||||
e_max_pu.iloc[-1] = 0
|
||||
|
||||
n.madd(
|
||||
"Store",
|
||||
spatial.biomass.nodes,
|
||||
suffix=" unsustainable",
|
||||
bus=spatial.biomass.nodes,
|
||||
carrier="unsustainable solid biomass",
|
||||
e_nom=unsustainable_solid_biomass_potentials_spatial,
|
||||
marginal_cost=costs.at["fuelwood", "fuel"],
|
||||
e_initial=unsustainable_solid_biomass_potentials_spatial,
|
||||
e_nom_extendable=False,
|
||||
e_max_pu=e_max_pu,
|
||||
)
|
||||
|
||||
n.madd(
|
||||
"Bus",
|
||||
spatial.biomass.bioliquids,
|
||||
location=spatial.biomass.locations,
|
||||
carrier="unsustainable bioliquids",
|
||||
unit="MWh_LHV",
|
||||
)
|
||||
|
||||
e_max_pu = pd.DataFrame(
|
||||
1, index=n.snapshots, columns=spatial.biomass.bioliquids
|
||||
)
|
||||
e_max_pu.iloc[-1] = 0
|
||||
|
||||
n.madd(
|
||||
"Store",
|
||||
spatial.biomass.bioliquids,
|
||||
suffix=" unsustainable",
|
||||
bus=spatial.biomass.bioliquids,
|
||||
carrier="unsustainable bioliquids",
|
||||
e_nom=unsustainable_liquid_biofuel_potentials_spatial,
|
||||
marginal_cost=costs.at["biodiesel crops", "fuel"],
|
||||
e_initial=unsustainable_liquid_biofuel_potentials_spatial,
|
||||
e_nom_extendable=False,
|
||||
e_max_pu=e_max_pu,
|
||||
)
|
||||
|
||||
n.madd(
|
||||
"Link",
|
||||
spatial.biomass.bioliquids,
|
||||
bus0=spatial.biomass.bioliquids,
|
||||
bus1=spatial.oil.nodes,
|
||||
bus2="co2 atmosphere",
|
||||
carrier="unsustainable bioliquids",
|
||||
efficiency=1,
|
||||
efficiency2=-costs.at["solid biomass", "CO2 intensity"]
|
||||
+ costs.at["BtL", "CO2 stored"],
|
||||
p_nom=unsustainable_liquid_biofuel_potentials_spatial,
|
||||
marginal_cost=costs.at["BtL", "VOM"],
|
||||
)
|
||||
|
||||
n.madd(
|
||||
"Link",
|
||||
spatial.gas.biogas_to_gas,
|
||||
@ -4131,6 +4230,7 @@ def add_enhanced_geothermal(n, egs_potentials, egs_overlap, costs):
|
||||
# %%
|
||||
if __name__ == "__main__":
|
||||
if "snakemake" not in globals():
|
||||
|
||||
from _helpers import mock_snakemake
|
||||
|
||||
snakemake = mock_snakemake(
|
||||
|
||||
Loading…
Reference in New Issue
Block a user