Update for compatibility with latest PyPSA-eur master branch
Remove non-renewable generator and storage units from electricity-only base network, since they're added differently here with links. Remove unncessary cruft from config.yaml which is not used by PyPSA-Eur-Sec (e.g. renewable configuration parameters). Rename "naptha" to correct "naphtha".
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Tom Brown
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README.md
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README.md
@ -17,20 +17,25 @@ the additional sectors.
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Currently the scripts to solve and process the resulting PyPSA models
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are also included in PyPSA-Eur-Sec, although they could in future be
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better integrated with the corresponding scripts in PyPSA-Eur.
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better integrated with the corresponding scripts in PyPSA-Eur. A
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stumbling block to sharing solve_network.py between PyPSA-Eur and
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PyPSA-Eur-Sec is the different extra_functionality required to build
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storage and CHP constraints.
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# Installation
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First install [PyPSA-Eur](https://github.com/PyPSA/pypsa-eur) and all
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its dependencies.
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its dependencies. Clone the repository:
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```shell
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projects % git clone git@github.com:PyPSA/pypsa-eur.git
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```
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then download and unpack all the data files.
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Create a parallel directory for PyPSA-Eur-Sec with:
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```shell
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projects % git clone git@github.com:nworbmot/pypsa-eur-sec.git
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```
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## Data requirements
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The Data requirements include JRC-IDEES-2015, JRC biomass potentials,
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67
config.yaml
67
config.yaml
@ -2,7 +2,7 @@ logging_level: INFO
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results_dir: 'results/'
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summary_dir: results
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run: '190416-modular-test'
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run: '190418-test-rebase'
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scenario:
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sectors: [E] # ,E+EV,E+BEV,E+BEV+V2G] # [ E+EV, E+BEV, E+BEV+V2G ]
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@ -35,73 +35,11 @@ electricity:
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conventional_carriers: [] # nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
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atlite:
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nprocesses: 4
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cutout_dir: '../pypsa-eur/cutouts'
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cutouts:
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europe-2013-era5:
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module: era5
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xs: [-12., 35.]
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ys: [72., 33.]
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years: [2013, 2013]
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europe-2013-sarah:
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module: sarah
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resolution: 0.2
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xs: [-12., 42.]
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ys: [65., 33.]
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years: [2013, 2013]
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renewable:
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onwind:
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cutout: europe-2013-era5
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resource:
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method: wind
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turbine: Vestas_V112_3MW
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# ScholzPhd Tab 4.3.1: 10MW/km^2
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capacity_per_sqm: 3
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# correction_factor: 0.93
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corine:
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#The selection of CORINE Land Cover [1] types that are allowed for wind and solar are based on [2] p.42 / p.28
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#
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#[1] https://www.eea.europa.eu/ds_resolveuid/C9RK15EA06
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#
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#[2] Scholz, Y. (2012). Renewable energy based electricity supply at low costs: development of the REMix model and application for Europe.
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grid_codes: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
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24, 25, 26, 27, 28, 29, 31, 32]
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distance: 1000
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distance_grid_codes: [1, 2, 3, 4, 5, 6]
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natura: true
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offwind:
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cutout: europe-2013-era5
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resource:
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method: wind
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turbine: NREL_ReferenceTurbine_5MW_offshore
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# ScholzPhd Tab 4.3.1: 10MW/km^2
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capacity_per_sqm: 3
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height_cutoff: 50
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# correction_factor: 0.93
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corine:
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grid_codes: [44, 255]
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natura: true
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solar:
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cutout: europe-2013-sarah
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resource:
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method: pv
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panel: CSi
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orientation:
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slope: 35.
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azimuth: 180.
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# ScholzPhd Tab 4.3.1: 170 MW/km^2
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capacity_per_sqm: 1.7
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correction_factor: 0.877
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corine:
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grid_codes: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
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18, 19, 20, 26, 31, 32]
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natura: true
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hydro:
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cutout: europe-2013-era5
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carriers: [ror, PHS, hydro]
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PHS_max_hours: 6
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biomass:
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year: 2030
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@ -216,7 +154,8 @@ plotting:
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energy_threshold: 50.
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vre_techs: ["onwind", "offwind", "solar", "ror"]
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vre_techs: ["onwind", "offwind-ac", "offwind-dc", "solar", "ror"]
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renewable_storage_techs: ["PHS","hydro"]
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conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
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storage_techs: ["hydro+PHS", "battery", "H2"]
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# store_techs: ["Li ion", "water tanks"]
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@ -10,7 +10,7 @@ def build_industrial_demand():
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totals = pd.Series(data=[1100.,1814.,586.,400.,580.,186.],
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index=["industry new electricity","industry process heat",
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"naptha feedstock","shipping H2","aviation kerosene","process emissions"])
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"naphtha feedstock","shipping H2","aviation kerosene","process emissions"])
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industrial_demand = pd.DataFrame({i : population["total"]*totals[i]*1e6/population["total"].sum() for i in totals.index })
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@ -37,6 +37,21 @@ override_component_attrs["Link"].loc["p3"] = ["series","MW",0.,"3rd bus output",
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def remove_elec_base_techs(n):
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"""remove conventional generators (e.g. OCGT) and storage units (e.g. batteries and H2)
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from base electricity-only network, since they're added here differently using links
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"""
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to_keep = {"generators" : snakemake.config["plotting"]["vre_techs"],
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"storage_units" : snakemake.config["plotting"]["renewable_storage_techs"]}
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n.carriers = n.carriers.loc[to_keep["generators"] + to_keep["storage_units"]]
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for components, techs in iteritems(to_keep):
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df = getattr(n,components)
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to_remove = df.carrier.value_counts().index^techs
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print("removing {} with carrier {}".format(components,to_remove))
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df.drop(df.index[df.carrier.isin(to_remove)],inplace=True)
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def add_co2_tracking(n):
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@ -1141,7 +1156,7 @@ def add_industry(network):
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network.add("Load",
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"Fischer-Tropsch",
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bus="Fischer-Tropsch",
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p_set = industrial_demand.loc[nodes,["aviation kerosene","naptha feedstock"]].sum().sum()/8760.)
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p_set = industrial_demand.loc[nodes,["aviation kerosene","naphtha feedstock"]].sum().sum()/8760.)
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network.madd("Load",
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nodes,
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@ -1200,6 +1215,8 @@ if __name__ == "__main__":
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costs = prepare_costs()
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remove_elec_base_techs(n)
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add_co2_tracking(n)
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add_generation(n)
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