Note
You can download this example as a Jupyter notebook or start it in interactive mode.
Biomass, synthetic fuels and carbon management
In this example we show how to manage different biomass stocks with different potentials and costs, synthetic fuel production, direct air capture (DAC) and carbon capture and usage/sequestration/cycling (CCU/S/C).
Demand for electricity and diesel transport have to be met from various biomass sources, natural gas with possibility for carbon capture, electrolysis for hydrogen production, direct air capture of CO2, and diesel synthesis via Fischer-Tropsch.
The system has to reach a target of net negative emissions over the period.
All numbers/costs/efficiencies are fictitious to allow easy analysis.
[1]:
import pypsa
import numpy as np
import matplotlib.pyplot as plt
First tell PyPSA that links can have multiple outputs by overriding the component_attrs. This can be done for as many buses as you need with format busi for i = 2,3,4,5,….
See https://pypsa.org/doc/components.html#link-with-multiple-outputs-or-inputs
[2]:
override_component_attrs = pypsa.descriptors.Dict({k : v.copy() for k,v in pypsa.components.component_attrs.items()})
override_component_attrs["Link"].loc["bus2"] = ["string",np.nan,np.nan,"2nd bus","Input (optional)"]
override_component_attrs["Link"].loc["bus3"] = ["string",np.nan,np.nan,"3rd bus","Input (optional)"]
override_component_attrs["Link"].loc["efficiency2"] = ["static or series","per unit",1.,"2nd bus efficiency","Input (optional)"]
override_component_attrs["Link"].loc["efficiency3"] = ["static or series","per unit",1.,"3rd bus efficiency","Input (optional)"]
override_component_attrs["Link"].loc["p2"] = ["series","MW",0.,"2nd bus output","Output"]
override_component_attrs["Link"].loc["p3"] = ["series","MW",0.,"3rd bus output","Output"]
[3]:
n = pypsa.Network(override_component_attrs=override_component_attrs)
n.set_snapshots(range(10))
Add a constant electrical load
[4]:
n.add("Bus","bus")
n.add("Load","load",bus="bus",
p_set=1.)
Add a constant demand for transport
[5]:
n.add("Bus","transport")
n.add("Load","transport",bus="transport",
p_set=1.)
n.add("Bus","diesel")
n.add("Store","diesel",bus="diesel",
e_cyclic=True,
e_nom=1000.)
Add a bus for Hydrogen storage.
[6]:
n.add("Bus","hydrogen")
n.add("Store","hydrogen",bus="hydrogen",
e_cyclic=True,
e_nom=1000.)
#n.add("Load","hydrogen",
# bus="hydrogen",
# p_set=1.)
n.add("Link","electrolysis",
p_nom=2.,
efficiency=0.8,
bus0="bus",
bus1="hydrogen")
Allow production of diesel from H2 and CO2 using Fischer-Tropsch
[7]:
n.add("Link","FT",
p_nom=4,
bus0="hydrogen",
bus1="diesel",
bus2="co2 stored",
efficiency=1.,
efficiency2=-1)
#minus sign because opposite to how fossil fuels used:
#CH4 burning puts CH4 down, atmosphere up
n.add("Carrier","co2",
co2_emissions=-1.)
#this tracks CO2 in the atmosphere
n.add("Bus","co2 atmosphere",
carrier="co2")
#NB: can also be negative
n.add("Store","co2 atmosphere",
e_nom=1000,
e_min_pu=-1,
bus="co2 atmosphere")
#this tracks CO2 stored, e.g. underground
n.add("Bus","co2 stored")
#NB: can also be negative
n.add("Store","co2 stored",
e_nom = 1000,
e_min_pu=-1,
bus="co2 stored")
Direct air capture consumes electricity to take CO2 from the air to the underground store
[8]:
n.add("Link","DAC",
bus0="bus",
bus1="co2 stored",
bus2 = "co2 atmosphere",
efficiency=1,
efficiency2=-1,
p_nom=5.)
Meet transport with diesel
[9]:
n.add("Link","diesel car",
bus0="diesel",
bus1="transport",
bus2="co2 atmosphere",
efficiency=1.,
efficiency2=1.,
p_nom=2.)
n.add("Bus","gas")
n.add("Store","gas",
e_initial=50,
e_nom=50,
marginal_cost=20,
bus="gas")
n.add("Link","OCGT",
bus0 = "gas",
bus1 = "bus",
bus2 = "co2 atmosphere",
p_nom_extendable=True,
efficiency = 0.5,
efficiency2 = 1)
n.add("Link","OCGT+CCS",
bus0 = "gas",
bus1 = "bus",
bus2 = "co2 stored",
bus3 = "co2 atmosphere",
p_nom_extendable=True,
efficiency = 0.4,
efficiency2 = 0.9,
efficiency3 = 0.1)
Add a cheap and a expensive biomass generator.
[10]:
biomass_marginal_cost = [20.,50.]
biomass_stored = [40.,15.]
for i in range(2):
n.add("Bus","biomass"+str(i))
n.add("Store","biomass"+str(i),
bus="biomass"+str(i),
e_nom_extendable=True,
marginal_cost=biomass_marginal_cost[i],
e_nom=biomass_stored[i],
e_initial=biomass_stored[i])
#simultaneously empties and refills co2 atmosphere
n.add("Link","biomass"+str(i),
bus0 = "biomass"+str(i),
bus1 = "bus",
p_nom_extendable=True,
efficiency = 0.5)
n.add("Link","biomass+CCS"+str(i),
bus0 = "biomass"+str(i),
bus1 = "bus",
bus2 = "co2 stored",
bus3 = "co2 atmosphere",
p_nom_extendable=True,
efficiency = 0.4,
efficiency2 = 1.,
efficiency3 = -1)
#can go to -50, but at some point can't generate enough electricity for DAC and demand
target = -50
Add a global CO\(_2\) constraint.
[11]:
n.add("GlobalConstraint","co2_limit",
sense="<=",
carrier_attribute="co2_emissions",
constant=target)
[12]:
n.lopf();
INFO:pypsa.opf:Performed preliminary steps
INFO:pypsa.opf:Building pyomo model using `kirchhoff` formulation
INFO:pypsa.opf:Solving model using glpk
WARNING:pyomo.solvers:Could not locate the 'glpsol' executable, which is required for solver 'glpk'
---------------------------------------------------------------------------
ApplicationError Traceback (most recent call last)
/tmp/ipykernel_240/1812968345.py in <module>
----> 1 n.lopf();
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pypsa/components.py in lopf(self, snapshots, pyomo, solver_name, solver_options, solver_logfile, formulation, keep_files, extra_functionality, multi_investment_periods, **kwargs)
646
647 if pyomo:
--> 648 return network_lopf(self, **args)
649 else:
650 return network_lopf_lowmem(self, **args)
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pypsa/opf.py in network_lopf(network, snapshots, solver_name, solver_io, skip_pre, extra_functionality, multi_investment_periods, solver_logfile, solver_options, keep_files, formulation, ptdf_tolerance, free_memory, extra_postprocessing)
1663 solver_logfile=solver_logfile, solver_options=solver_options,
1664 keep_files=keep_files, free_memory=free_memory,
-> 1665 extra_postprocessing=extra_postprocessing)
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pypsa/opf.py in network_lopf_solve(network, snapshots, formulation, solver_options, solver_logfile, keep_files, free_memory, extra_postprocessing)
1563 network.results = network.opt.solve(*args, suffixes=["dual"], keepfiles=keep_files, logfile=solver_logfile, options=solver_options)
1564 else:
-> 1565 network.results = network.opt.solve(*args, suffixes=["dual"], keepfiles=keep_files, logfile=solver_logfile, options=solver_options)
1566
1567 if logger.isEnabledFor(logging.INFO):
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pyomo/opt/base/solvers.py in solve(self, *args, **kwds)
510 """ Solve the problem """
511
--> 512 self.available(exception_flag=True)
513 #
514 # If the inputs are models, then validate that they have been
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pyomo/opt/solver/shellcmd.py in available(self, exception_flag)
123 if exception_flag:
124 msg = "No executable found for solver '%s'"
--> 125 raise ApplicationError(msg % self.name)
126 return False
127 return True
ApplicationError: No executable found for solver 'glpk'
How do the different stores in the system behave?
[13]:
n.stores_t.e.plot(figsize = (9,7), lw=3)
plt.tight_layout()
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_240/1715769439.py in <module>
----> 1 n.stores_t.e.plot(figsize = (9,7), lw=3)
2 plt.tight_layout()
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/plotting/_core.py in __call__(self, *args, **kwargs)
970 data.columns = label_name
971
--> 972 return plot_backend.plot(data, kind=kind, **kwargs)
973
974 __call__.__doc__ = __doc__
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/plotting/_matplotlib/__init__.py in plot(data, kind, **kwargs)
69 kwargs["ax"] = getattr(ax, "left_ax", ax)
70 plot_obj = PLOT_CLASSES[kind](data, **kwargs)
---> 71 plot_obj.generate()
72 plot_obj.draw()
73 return plot_obj.result
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/plotting/_matplotlib/core.py in generate(self)
284 def generate(self):
285 self._args_adjust()
--> 286 self._compute_plot_data()
287 self._setup_subplots()
288 self._make_plot()
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/plotting/_matplotlib/core.py in _compute_plot_data(self)
451 # no non-numeric frames or series allowed
452 if is_empty:
--> 453 raise TypeError("no numeric data to plot")
454
455 self.data = numeric_data.apply(self._convert_to_ndarray)
TypeError: no numeric data to plot
Let’s have a look at the production
[14]:
n.links_t.p0[["biomass+CCS0", "biomass+CCS1", "OCGT+CCS", "DAC"]].plot(subplots=True, figsize = (9,7))
plt.tight_layout()
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
/tmp/ipykernel_240/447846780.py in <module>
----> 1 n.links_t.p0[["biomass+CCS0", "biomass+CCS1", "OCGT+CCS", "DAC"]].plot(subplots=True, figsize = (9,7))
2 plt.tight_layout()
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/core/frame.py in __getitem__(self, key)
3462 if is_iterator(key):
3463 key = list(key)
-> 3464 indexer = self.loc._get_listlike_indexer(key, axis=1)[1]
3465
3466 # take() does not accept boolean indexers
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/core/indexing.py in _get_listlike_indexer(self, key, axis)
1312 keyarr, indexer, new_indexer = ax._reindex_non_unique(keyarr)
1313
-> 1314 self._validate_read_indexer(keyarr, indexer, axis)
1315
1316 if needs_i8_conversion(ax.dtype) or isinstance(
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/core/indexing.py in _validate_read_indexer(self, key, indexer, axis)
1372 if use_interval_msg:
1373 key = list(key)
-> 1374 raise KeyError(f"None of [{key}] are in the [{axis_name}]")
1375
1376 not_found = list(ensure_index(key)[missing_mask.nonzero()[0]].unique())
KeyError: "None of [Index(['biomass+CCS0', 'biomass+CCS1', 'OCGT+CCS', 'DAC'], dtype='object')] are in the [columns]"
At all times, the amount of carbon is constant!
[15]:
n.stores_t.e[["co2 stored","co2 atmosphere","gas","diesel"]].sum(axis=1)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
/tmp/ipykernel_240/3838290976.py in <module>
----> 1 n.stores_t.e[["co2 stored","co2 atmosphere","gas","diesel"]].sum(axis=1)
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/core/frame.py in __getitem__(self, key)
3462 if is_iterator(key):
3463 key = list(key)
-> 3464 indexer = self.loc._get_listlike_indexer(key, axis=1)[1]
3465
3466 # take() does not accept boolean indexers
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/core/indexing.py in _get_listlike_indexer(self, key, axis)
1312 keyarr, indexer, new_indexer = ax._reindex_non_unique(keyarr)
1313
-> 1314 self._validate_read_indexer(keyarr, indexer, axis)
1315
1316 if needs_i8_conversion(ax.dtype) or isinstance(
~/checkouts/readthedocs.org/user_builds/pypsa-docs-staging/envs/latest/lib/python3.7/site-packages/pandas/core/indexing.py in _validate_read_indexer(self, key, indexer, axis)
1372 if use_interval_msg:
1373 key = list(key)
-> 1374 raise KeyError(f"None of [{key}] are in the [{axis_name}]")
1375
1376 not_found = list(ensure_index(key)[missing_mask.nonzero()[0]].unique())
KeyError: "None of [Index(['co2 stored', 'co2 atmosphere', 'gas', 'diesel'], dtype='object')] are in the [columns]"