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GNU GENERAL PUBLIC LICENSE MIT License
Version 3, 29 June 2007
Copyright 2017-2021 The PyPSA-Eur Authors
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under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
<http://www.gnu.org/licenses/>.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<http://www.gnu.org/philosophy/why-not-lgpl.html>.

2
README.md
View File

@ -65,6 +65,6 @@ the additional sectors.
# Licence # Licence
The code in PyPSA-Eur-Sec is released as free software under the The code in PyPSA-Eur-Sec is released as free software under the
[GPLv3](http://www.gnu.org/licenses/gpl-3.0.en.html), see LICENSE.txt. [MIT License](https://opensource.org/licenses/MIT), see `LICENSE.txt`.
However, different licenses and terms of use may apply to the various However, different licenses and terms of use may apply to the various
input data. input data.

5
config.default.yaml
View File

@ -223,7 +223,8 @@ sector:
co2_vent: true co2_vent: true
SMR: true SMR: true
co2_sequestration_potential: 200 #MtCO2/a sequestration potential for Europe co2_sequestration_potential: 200 #MtCO2/a sequestration potential for Europe
co2_sequestration_cost: 20 #EUR/tCO2 for transport and sequestration of CO2 co2_sequestration_cost: 10 #EUR/tCO2 for sequestration of CO2
co2_network: false
cc_fraction: 0.9 # default fraction of CO2 captured with post-combustion capture cc_fraction: 0.9 # default fraction of CO2 captured with post-combustion capture
hydrogen_underground_storage: true hydrogen_underground_storage: true
use_fischer_tropsch_waste_heat: true use_fischer_tropsch_waste_heat: true
@ -420,6 +421,7 @@ plotting:
lines: k lines: k
transmission lines: k transmission lines: k
H2: m H2: m
H2 liquefaction: m
hydrogen storage: m hydrogen storage: m
battery: slategray battery: slategray
battery storage: slategray battery storage: slategray
@ -466,6 +468,7 @@ plotting:
hot water storage: '#BBBBBB' hot water storage: '#BBBBBB'
hot water charging: '#BBBBBB' hot water charging: '#BBBBBB'
hot water discharging: '#999999' hot water discharging: '#999999'
CO2 pipeline: '#999999'
CHP: r CHP: r
CHP heat: r CHP heat: r
CHP electric: r CHP electric: r

4
doc/index.rst
View File

@ -134,7 +134,7 @@ it.
Licence Licence
======= =======
The code in PyPSA-Eur-Sec is released as free software under the `GPLv3 The code in PyPSA-Eur-Sec is released as free software under the
<http://www.gnu.org/licenses/gpl-3.0.en.html>`_, see `MIT license <https://opensource.org/licenses/MIT>`_, see
`LICENSE <https://github.com/PyPSA/pypsa-eur-sec/blob/master/LICENSE.txt>`_. `LICENSE <https://github.com/PyPSA/pypsa-eur-sec/blob/master/LICENSE.txt>`_.
However, different licenses and terms of use may apply to the various input data. However, different licenses and terms of use may apply to the various input data.

11
doc/release_notes.rst
View File

@ -8,6 +8,8 @@ Future release
.. note:: .. note::
This unreleased version currently requires the master branches of PyPSA, PyPSA-Eur, and the technology-data repository. This unreleased version currently requires the master branches of PyPSA, PyPSA-Eur, and the technology-data repository.
* With this release, we change the license from copyleft GPLv3 to the more
liberal MIT license with the consent of all contributors.
* Extended use of ``multiprocessing`` for much better performance * Extended use of ``multiprocessing`` for much better performance
(from up to 20 minutes to less than one minute). (from up to 20 minutes to less than one minute).
* Compatibility with ``atlite>=0.2``. Older versions of ``atlite`` will no longer work. * Compatibility with ``atlite>=0.2``. Older versions of ``atlite`` will no longer work.
@ -60,6 +62,14 @@ Future release
These are included in the environment specifications of PyPSA-Eur. These are included in the environment specifications of PyPSA-Eur.
* Consistent use of ``__main__`` block and further unspecific code cleaning. * Consistent use of ``__main__`` block and further unspecific code cleaning.
* Distinguish costs for home battery storage and inverter from utility-scale battery costs. * Distinguish costs for home battery storage and inverter from utility-scale battery costs.
* Add option to regionally resolve CO2 storage and add CO2 pipeline transport because geological storage potential,
CO2 utilisation sites and CO2 capture sites may be separated.
The CO2 network is built from zero based on the topology of the electricity grid (greenfield).
Pipelines are assumed to be bidirectional and lossless.
Furthermore, neither retrofitting of natural gas pipelines (required pressures are too high, 80-160 bar vs <80 bar)
nor other modes of CO2 transport (by ship, road or rail) are considered.
The regional representation of CO2 is activated with the config setting ``sector: co2_network: true`` but is deactivated by default.
The global limit for CO2 sequestration now applies to the sum of all CO2 stores via an ``extra_functionality`` constraint.
* Added option for hydrogen liquefaction costs for hydrogen demand in shipping. * Added option for hydrogen liquefaction costs for hydrogen demand in shipping.
This introduces a new ``H2 liquid`` bus at each location. This introduces a new ``H2 liquid`` bus at each location.
It is activated via ``sector: shipping_hydrogen_liquefaction: true``. It is activated via ``sector: shipping_hydrogen_liquefaction: true``.
@ -72,6 +82,7 @@ Future release
The transport costs are determined based on the `JRC-EU-Times Bioenergy report <http://dx.doi.org/10.2790/01017>`_ The transport costs are determined based on the `JRC-EU-Times Bioenergy report <http://dx.doi.org/10.2790/01017>`_
in the new optional rule ``build_biomass_transport_costs``. in the new optional rule ``build_biomass_transport_costs``.
Biomass transport can be activated with the setting ``sector: biomass_transport: true``. Biomass transport can be activated with the setting ``sector: biomass_transport: true``.
* Compatibility with ``xarray`` version 0.19.
PyPSA-Eur-Sec 0.5.0 (21st May 2021) PyPSA-Eur-Sec 0.5.0 (21st May 2021)
=================================== ===================================

2
doc/spatial_resolution.rst
View File

@ -50,7 +50,7 @@ then distributed by population density within)
and transport of solid biomass is possible. and transport of solid biomass is possible.
CO2: single node for Europe, but a transport and storage cost is added for CO2: single node for Europe, but a transport and storage cost is added for
sequestered CO2. sequestered CO2. Optionally: nodal, with CO2 transport via pipelines.
Liquid hydrocarbons: single node for Europe, since transport costs for Liquid hydrocarbons: single node for Europe, since transport costs for
liquids are low. liquids are low.

5
scripts/add_existing_baseyear.py
View File

@ -28,7 +28,7 @@ def add_build_year_to_new_assets(n, baseyear):
# Give assets with lifetimes and no build year the build year baseyear # Give assets with lifetimes and no build year the build year baseyear
for c in n.iterate_components(["Link", "Generator", "Store"]): for c in n.iterate_components(["Link", "Generator", "Store"]):
assets = c.df.index[~c.df.lifetime.isna() & c.df.build_year.isna()] assets = c.df.index[~c.df.lifetime.isna() & c.df.build_year==0]
c.df.loc[assets, "build_year"] = baseyear c.df.loc[assets, "build_year"] = baseyear
# add -baseyear to name # add -baseyear to name
@ -410,7 +410,8 @@ if __name__ == "__main__":
simpl='', simpl='',
clusters=45, clusters=45,
lv=1.0, lv=1.0,
sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1', opts='',
sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1',
planning_horizons=2020, planning_horizons=2020,
) )

4
scripts/build_population_layouts.py
View File

@ -90,8 +90,8 @@ if __name__ == '__main__':
for key, pop in pop_cells.items(): for key, pop in pop_cells.items():
ycoords = ('y', cutout.coords['y']) ycoords = ('y', cutout.coords['y'].data)
xcoords = ('x', cutout.coords['x']) xcoords = ('x', cutout.coords['x'].data)
values = pop.values.reshape(cutout.shape) values = pop.values.reshape(cutout.shape)
layout = xr.DataArray(values, [ycoords, xcoords]) layout = xr.DataArray(values, [ycoords, xcoords])

12
scripts/plot_network.py
View File

@ -398,7 +398,8 @@ def plot_series(network, carrier="AC", name="test"):
supply = pd.DataFrame(index=n.snapshots) supply = pd.DataFrame(index=n.snapshots)
for c in n.iterate_components(n.branch_components): for c in n.iterate_components(n.branch_components):
for i in range(2): n_port = 4 if c.name=='Link' else 2
for i in range(n_port):
supply = pd.concat((supply, supply = pd.concat((supply,
(-1) * c.pnl["p" + str(i)].loc[:, (-1) * c.pnl["p" + str(i)].loc[:,
c.df.index[c.df["bus" + str(i)].isin(buses)]].groupby(c.df.carrier, c.df.index[c.df["bus" + str(i)].isin(buses)]].groupby(c.df.carrier,
@ -522,10 +523,11 @@ if __name__ == "__main__":
snakemake = mock_snakemake( snakemake = mock_snakemake(
'plot_network', 'plot_network',
simpl='', simpl='',
clusters=48, clusters=45,
lv=1.0, lv=1.5,
sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1', opts='',
planning_horizons=2050, sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1',
planning_horizons=2030,
) )
overrides = override_component_attrs(snakemake.input.overrides) overrides = override_component_attrs(snakemake.input.overrides)

149
scripts/prepare_sector_network.py
View File

@ -37,6 +37,8 @@ def define_spatial(nodes):
spatial.nodes = nodes spatial.nodes = nodes
# biomass
spatial.biomass = SimpleNamespace() spatial.biomass = SimpleNamespace()
if options["biomass_transport"]: if options["biomass_transport"]:
@ -52,6 +54,21 @@ def define_spatial(nodes):
spatial.biomass.df = pd.DataFrame(vars(spatial.biomass), index=nodes) spatial.biomass.df = pd.DataFrame(vars(spatial.biomass), index=nodes)
# co2
spatial.co2 = SimpleNamespace()
if options["co2_network"]:
spatial.co2.nodes = nodes + " co2 stored"
spatial.co2.locations = nodes
spatial.co2.vents = nodes + " co2 vent"
else:
spatial.co2.nodes = ["co2 stored"]
spatial.co2.locations = ["EU"]
spatial.co2.vents = ["co2 vent"]
spatial.co2.df = pd.DataFrame(vars(spatial.co2), index=nodes)
def emission_sectors_from_opts(opts): def emission_sectors_from_opts(opts):
@ -87,6 +104,40 @@ def get(item, investment_year=None):
return item return item
def create_network_topology(n, prefix, connector=" -> "):
"""
Create a network topology like the power transmission network.
Parameters
----------
n : pypsa.Network
prefix : str
connector : str
Returns
-------
pd.DataFrame with columns bus0, bus1 and length
"""
ln_attrs = ["bus0", "bus1", "length"]
lk_attrs = ["bus0", "bus1", "length", "underwater_fraction"]
candidates = pd.concat([
n.lines[ln_attrs],
n.links.loc[n.links.carrier == "DC", lk_attrs]
]).fillna(0)
positive_order = candidates.bus0 < candidates.bus1
candidates_p = candidates[positive_order]
swap_buses = {"bus0": "bus1", "bus1": "bus0"}
candidates_n = candidates[~positive_order].rename(columns=swap_buses)
candidates = pd.concat([candidates_p, candidates_n])
topo = candidates.groupby(["bus0", "bus1"], as_index=False).mean()
topo.index = topo.apply(lambda c: prefix + c.bus0 + connector + c.bus1, axis=1)
return topo
def co2_emissions_year(countries, opts, year): def co2_emissions_year(countries, opts, year):
""" """
Calculate CO2 emissions in one specific year (e.g. 1990 or 2018). Calculate CO2 emissions in one specific year (e.g. 1990 or 2018).
@ -136,9 +187,6 @@ def build_carbon_budget(o, fn):
#emissions at the beginning of the path (last year available 2018) #emissions at the beginning of the path (last year available 2018)
e_0 = co2_emissions_year(countries, opts, year=2018) e_0 = co2_emissions_year(countries, opts, year=2018)
#emissions in 2019 and 2020 assumed equal to 2018 and substracted
carbon_budget -= 2 * e_0
planning_horizons = snakemake.config['scenario']['planning_horizons'] planning_horizons = snakemake.config['scenario']['planning_horizons']
t_0 = planning_horizons[0] t_0 = planning_horizons[0]
@ -353,6 +401,9 @@ def patch_electricity_network(n):
update_wind_solar_costs(n, costs) update_wind_solar_costs(n, costs)
n.loads["carrier"] = "electricity" n.loads["carrier"] = "electricity"
n.buses["location"] = n.buses.index n.buses["location"] = n.buses.index
# remove trailing white space of load index until new PyPSA version after v0.18.
n.loads.rename(lambda x: x.strip(), inplace=True)
n.loads_t.p_set.rename(lambda x: x.strip(), axis=1, inplace=True)
def add_co2_tracking(n, options): def add_co2_tracking(n, options):
@ -379,26 +430,26 @@ def add_co2_tracking(n, options):
) )
# this tracks CO2 stored, e.g. underground # this tracks CO2 stored, e.g. underground
n.add("Bus", n.madd("Bus",
"co2 stored", spatial.co2.nodes,
location="EU", location=spatial.co2.locations,
carrier="co2 stored" carrier="co2 stored"
) )
n.add("Store", n.madd("Store",
"co2 stored", spatial.co2.nodes,
e_nom_extendable=True, e_nom_extendable=True,
e_nom_max=options['co2_sequestration_potential'] * 1e6, e_nom_max=np.inf,
capital_cost=options['co2_sequestration_cost'], capital_cost=options['co2_sequestration_cost'],
carrier="co2 stored", carrier="co2 stored",
bus="co2 stored" bus=spatial.co2.nodes
) )
if options['co2_vent']: if options['co2_vent']:
n.add("Link", n.madd("Link",
"co2 vent", spatial.co2.vents,
bus0="co2 stored", bus0=spatial.co2.nodes,
bus1="co2 atmosphere", bus1="co2 atmosphere",
carrier="co2 vent", carrier="co2 vent",
efficiency=1., efficiency=1.,
@ -406,6 +457,28 @@ def add_co2_tracking(n, options):
) )
def add_co2_network(n, costs):
logger.info("Adding CO2 network.")
co2_links = create_network_topology(n, "CO2 pipeline ")
cost_onshore = (1 - co2_links.underwater_fraction) * costs.at['CO2 pipeline', 'fixed'] * co2_links.length
cost_submarine = co2_links.underwater_fraction * costs.at['CO2 submarine pipeline', 'fixed'] * co2_links.length
capital_cost = cost_onshore + cost_submarine
n.madd("Link",
co2_links.index,
bus0=co2_links.bus0.values + " co2 stored",
bus1=co2_links.bus1.values + " co2 stored",
p_min_pu=-1,
p_nom_extendable=True,
length=co2_links.length.values,
capital_cost=capital_cost.values,
carrier="CO2 pipeline",
lifetime=costs.at['CO2 pipeline', 'lifetime']
)
def add_dac(n, costs): def add_dac(n, costs):
heat_carriers = ["urban central heat", "services urban decentral heat"] heat_carriers = ["urban central heat", "services urban decentral heat"]
@ -419,7 +492,7 @@ def add_dac(n, costs):
locations, locations,
suffix=" DAC", suffix=" DAC",
bus0="co2 atmosphere", bus0="co2 atmosphere",
bus1="co2 stored", bus1=spatial.co2.df.loc[locations, "nodes"].values,
bus2=locations.values, bus2=locations.values,
bus3=heat_buses, bus3=heat_buses,
carrier="DAC", carrier="DAC",
@ -850,7 +923,8 @@ def insert_electricity_distribution_grid(n, costs):
marginal_cost=n.generators.loc[solar, 'marginal_cost'], marginal_cost=n.generators.loc[solar, 'marginal_cost'],
capital_cost=costs.at['solar-rooftop', 'fixed'], capital_cost=costs.at['solar-rooftop', 'fixed'],
efficiency=n.generators.loc[solar, 'efficiency'], efficiency=n.generators.loc[solar, 'efficiency'],
p_max_pu=n.generators_t.p_max_pu[solar] p_max_pu=n.generators_t.p_max_pu[solar],
lifetime=costs.at['solar-rooftop', 'lifetime']
) )
n.add("Carrier", "home battery") n.add("Carrier", "home battery")
@ -1069,10 +1143,11 @@ def add_storage(n, costs):
if options['methanation']: if options['methanation']:
n.madd("Link", n.madd("Link",
nodes + " Sabatier", spatial.nodes,
suffix=" Sabatier",
bus0=nodes + " H2", bus0=nodes + " H2",
bus1="EU gas", bus1="EU gas",
bus2="co2 stored", bus2=spatial.co2.nodes,
p_nom_extendable=True, p_nom_extendable=True,
carrier="Sabatier", carrier="Sabatier",
efficiency=costs.at["methanation", "efficiency"], efficiency=costs.at["methanation", "efficiency"],
@ -1084,10 +1159,11 @@ def add_storage(n, costs):
if options['helmeth']: if options['helmeth']:
n.madd("Link", n.madd("Link",
nodes + " helmeth", spatial.nodes,
suffix=" helmeth",
bus0=nodes, bus0=nodes,
bus1="EU gas", bus1="EU gas",
bus2="co2 stored", bus2=spatial.co2.nodes,
carrier="helmeth", carrier="helmeth",
p_nom_extendable=True, p_nom_extendable=True,
efficiency=costs.at["helmeth", "efficiency"], efficiency=costs.at["helmeth", "efficiency"],
@ -1100,11 +1176,12 @@ def add_storage(n, costs):
if options['SMR']: if options['SMR']:
n.madd("Link", n.madd("Link",
nodes + " SMR CC", spatial.nodes,
suffix=" SMR CC",
bus0="EU gas", bus0="EU gas",
bus1=nodes + " H2", bus1=nodes + " H2",
bus2="co2 atmosphere", bus2="co2 atmosphere",
bus3="co2 stored", bus3=spatial.co2.nodes,
p_nom_extendable=True, p_nom_extendable=True,
carrier="SMR CC", carrier="SMR CC",
efficiency=costs.at["SMR CC", "efficiency"], efficiency=costs.at["SMR CC", "efficiency"],
@ -1453,7 +1530,7 @@ def add_heat(n, costs):
bus1=nodes[name], bus1=nodes[name],
bus2=nodes[name] + " urban central heat", bus2=nodes[name] + " urban central heat",
bus3="co2 atmosphere", bus3="co2 atmosphere",
bus4="co2 stored", bus4=spatial.co2.df.loc[nodes[name], "nodes"].values,
carrier="urban central gas CHP CC", carrier="urban central gas CHP CC",
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at['central gas CHP', 'fixed']*costs.at['central gas CHP', 'efficiency'] + costs.at['biomass CHP capture', 'fixed']*costs.at['gas', 'CO2 intensity'], capital_cost=costs.at['central gas CHP', 'fixed']*costs.at['central gas CHP', 'efficiency'] + costs.at['biomass CHP capture', 'fixed']*costs.at['gas', 'CO2 intensity'],
@ -1720,7 +1797,7 @@ def add_biomass(n, costs):
bus1=urban_central, bus1=urban_central,
bus2=urban_central + " urban central heat", bus2=urban_central + " urban central heat",
bus3="co2 atmosphere", bus3="co2 atmosphere",
bus4="co2 stored", bus4=spatial.co2.df.loc[urban_central, "nodes"].values,
carrier="urban central solid biomass CHP CC", carrier="urban central solid biomass CHP CC",
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at[key, 'fixed'] * costs.at[key, 'efficiency'] + costs.at['biomass CHP capture', 'fixed'] * costs.at['solid biomass', 'CO2 intensity'], capital_cost=costs.at[key, 'fixed'] * costs.at[key, 'efficiency'] + costs.at['biomass CHP capture', 'fixed'] * costs.at['solid biomass', 'CO2 intensity'],
@ -1774,7 +1851,7 @@ def add_industry(n, costs):
bus0=spatial.biomass.nodes, bus0=spatial.biomass.nodes,
bus1=spatial.biomass.industry, bus1=spatial.biomass.industry,
bus2="co2 atmosphere", bus2="co2 atmosphere",
bus3="co2 stored", bus3=spatial.co2.nodes,
carrier="solid biomass for industry CC", carrier="solid biomass for industry CC",
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at["cement capture", "fixed"] * costs.at['solid biomass', 'CO2 intensity'], capital_cost=costs.at["cement capture", "fixed"] * costs.at['solid biomass', 'CO2 intensity'],
@ -1807,12 +1884,13 @@ def add_industry(n, costs):
efficiency2=costs.at['gas', 'CO2 intensity'] efficiency2=costs.at['gas', 'CO2 intensity']
) )
n.add("Link", n.madd("Link",
"gas for industry CC", spatial.co2.locations,
suffix=" gas for industry CC",
bus0="EU gas", bus0="EU gas",
bus1="gas for industry", bus1="gas for industry",
bus2="co2 atmosphere", bus2="co2 atmosphere",
bus3="co2 stored", bus3=spatial.co2.nodes,
carrier="gas for industry CC", carrier="gas for industry CC",
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at["cement capture", "fixed"] * costs.at['gas', 'CO2 intensity'], capital_cost=costs.at["cement capture", "fixed"] * costs.at['gas', 'CO2 intensity'],
@ -1943,7 +2021,7 @@ def add_industry(n, costs):
nodes + " Fischer-Tropsch", nodes + " Fischer-Tropsch",
bus0=nodes + " H2", bus0=nodes + " H2",
bus1="EU oil", bus1="EU oil",
bus2="co2 stored", bus2=spatial.co2.nodes,
carrier="Fischer-Tropsch", carrier="Fischer-Tropsch",
efficiency=costs.at["Fischer-Tropsch", 'efficiency'], efficiency=costs.at["Fischer-Tropsch", 'efficiency'],
capital_cost=costs.at["Fischer-Tropsch", 'fixed'], capital_cost=costs.at["Fischer-Tropsch", 'fixed'],
@ -2032,11 +2110,12 @@ def add_industry(n, costs):
) )
#assume enough local waste heat for CC #assume enough local waste heat for CC
n.add("Link", n.madd("Link",
"process emissions CC", spatial.co2.locations,
suffix=" process emissions CC",
bus0="process emissions", bus0="process emissions",
bus1="co2 atmosphere", bus1="co2 atmosphere",
bus2="co2 stored", bus2=spatial.co2.nodes,
carrier="process emissions CC", carrier="process emissions CC",
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at["cement capture", "fixed"], capital_cost=costs.at["cement capture", "fixed"],
@ -2126,10 +2205,11 @@ if __name__ == "__main__":
snakemake = mock_snakemake( snakemake = mock_snakemake(
'prepare_sector_network', 'prepare_sector_network',
simpl='', simpl='',
clusters=48, clusters=45,
lv=1.0, lv=1.0,
opts='',
sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1', sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
planning_horizons=2020, planning_horizons=2030,
) )
logging.basicConfig(level=snakemake.config['logging_level']) logging.basicConfig(level=snakemake.config['logging_level'])
@ -2210,6 +2290,9 @@ if __name__ == "__main__":
if "noH2network" in opts: if "noH2network" in opts:
remove_h2_network(n) remove_h2_network(n)
if options["co2_network"]:
add_co2_network(n, costs)
for o in opts: for o in opts:
m = re.match(r'^\d+h$', o, re.IGNORECASE) m = re.match(r'^\d+h$', o, re.IGNORECASE)
if m is not None: if m is not None:

19
scripts/solve_network.py
View File

@ -3,6 +3,7 @@
import pypsa import pypsa
import numpy as np import numpy as np
import pandas as pd
from pypsa.linopt import get_var, linexpr, define_constraints from pypsa.linopt import get_var, linexpr, define_constraints
@ -150,8 +151,26 @@ def add_chp_constraints(n):
define_constraints(n, lhs, "<=", 0, 'chplink', 'backpressure') define_constraints(n, lhs, "<=", 0, 'chplink', 'backpressure')
def add_co2_sequestration_limit(n, sns):
co2_stores = n.stores.loc[n.stores.carrier=='co2 stored'].index
if co2_stores.empty or ('Store', 'e') not in n.variables.index:
return
vars_final_co2_stored = get_var(n, 'Store', 'e').loc[sns[-1], co2_stores]
lhs = linexpr((1, vars_final_co2_stored)).sum()
rhs = n.config["sector"].get("co2_sequestration_potential", 200) * 1e6
name = 'co2_sequestration_limit'
define_constraints(n, lhs, "<=", rhs, 'GlobalConstraint',
'mu', axes=pd.Index([name]), spec=name)
def extra_functionality(n, snapshots): def extra_functionality(n, snapshots):
add_battery_constraints(n) add_battery_constraints(n)
add_co2_sequestration_limit(n, snapshots)
def solve_network(n, config, opts='', **kwargs): def solve_network(n, config, opts='', **kwargs):