Merge branch 'master' into encapsulate-resource-dir
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commit
3db6a65c04
@ -606,9 +606,34 @@ industry:
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MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv
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NH3_process_emissions: 24.5
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petrochemical_process_emissions: 25.5
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HVC_primary_fraction: 1.
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HVC_mechanical_recycling_fraction: 0.
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HVC_chemical_recycling_fraction: 0.
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#HVC primary/recycling based on values used in Neumann et al https://doi.org/10.1016/j.joule.2023.06.016, linearly interpolated between 2020 and 2050
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#2020 recycling rates based on Agora https://static.agora-energiewende.de/fileadmin/Projekte/2021/2021_02_EU_CEAP/A-EW_254_Mobilising-circular-economy_study_WEB.pdf
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#fractions refer to the total primary HVC production in 2020
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#assumes 6.7 Mtplastics produced from recycling in 2020
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HVC_primary_fraction:
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2020: 1.0
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2025: 0.9
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2030: 0.8
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2035: 0.7
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2040: 0.6
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2045: 0.5
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2050: 0.4
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HVC_mechanical_recycling_fraction:
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2020: 0.12
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2025: 0.15
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2030: 0.18
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2035: 0.21
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2040: 0.24
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2045: 0.27
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2050: 0.30
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HVC_chemical_recycling_fraction:
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2020: 0.0
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2025: 0.0
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2030: 0.04
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2035: 0.08
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2040: 0.12
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2045: 0.16
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2050: 0.20
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HVC_production_today: 52.
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MWh_elec_per_tHVC_mechanical_recycling: 0.547
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MWh_elec_per_tHVC_chemical_recycling: 6.9
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@ -68,6 +68,14 @@ Upcoming Release
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* A ``test.sh`` script was added to the repository to run the tests locally.
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* Default settings for recycling rates and primary product shares of high-value
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chemicals have been set in accordance with the values used in `Neumann et al.
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(2023) <https://doi.org/10.1016/j.joule.2023.06.016>`_ linearly interpolated
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between 2020 and 2050. The recycling rates are based on data from `Agora
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Energiewende (2021)
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<https://static.agora-energiewende.de/fileadmin/Projekte/2021/2021_02_EU_CEAP/A-EW_254_Mobilising-circular-economy_study_WEB.pdf>`_.
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PyPSA-Eur 0.9.0 (5th January 2024)
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==================================
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@ -48,6 +48,7 @@ dependencies:
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- tabula-py
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- pyxlsb
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- graphviz
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- pre-commit
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# Keep in conda environment when calling ipython
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- ipython
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@ -482,7 +482,7 @@ def add_heating_capacities_installed_before_baseyear(
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"Link",
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nodes,
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suffix=f" {name} gas boiler-{grouping_year}",
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bus0=spatial.gas.nodes,
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bus0="EU gas" if "EU gas" in spatial.gas.nodes else nodes + " gas",
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bus1=nodes + " " + name + " heat",
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bus2="co2 atmosphere",
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carrier=name + " gas boiler",
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@ -1319,22 +1319,6 @@ def add_storage_and_grids(n, costs):
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n, "H2 pipeline ", carriers=["DC", "gas pipeline"]
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)
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h2_pipes["p_nom"] = 0.0
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if snakemake.input.get("custom_h2_pipelines"):
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fn = snakemake.input.custom_h2_pipelines
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custom_pipes = pd.read_csv(fn, index_col=0)
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h2_pipes = pd.concat([h2_pipes, custom_pipes])
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# drop duplicates according to buses (order can be different) and keep pipe with highest p_nom
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h2_pipes["buses_sorted"] = h2_pipes[["bus0", "bus1"]].apply(sorted, axis=1)
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h2_pipes = (
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h2_pipes.sort_values("p_nom")
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.drop_duplicates(subset=["buses_sorted"], keep="last")
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.drop(columns="buses_sorted")
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)
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# TODO Add efficiency losses
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n.madd(
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"Link",
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@ -1343,7 +1327,6 @@ def add_storage_and_grids(n, costs):
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bus1=h2_pipes.bus1.values + " H2",
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p_min_pu=-1,
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p_nom_extendable=True,
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p_nom_min=h2_pipes.p_nom.values,
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length=h2_pipes.length.values,
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capital_cost=costs.at["H2 (g) pipeline", "fixed"] * h2_pipes.length.values,
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carrier="H2 pipeline",
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