Note

You can download this example as a Jupyter notebook or start it in interactive mode.

Constraining the total capacity per bus and carrier

In this small example, we limit the nominal capacity of generators of the same production carrier at the same bus.

Therefore, we introduce a column nom_min_{carrier} and nom_max_{carrier} in the buses dataframe. These are then used as lower and upper bounds of generators of the same carrier at the same bus.

We start with importing a small example network.

[1]:
import pypsa
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In [1], line 1
----> 1 import pypsa

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/pypsa/__init__.py:10
      1 # -*- coding: utf-8 -*-
      4 """
      5 Python for Power Systems Analysis (PyPSA)
      6
      7 Grid calculation library.
      8 """
---> 10 from pypsa import (
     11     components,
     12     contingency,
     13     descriptors,
     14     examples,
     15     geo,
     16     io,
     17     linopf,
     18     linopt,
     19     networkclustering,
     20     opf,
     21     opt,
     22     optimization,
     23     pf,
     24     plot,
     25 )
     26 from pypsa.components import Network, SubNetwork
     28 __version__ = "0.21.2"

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/pypsa/components.py:50
     37 from pypsa.io import (
     38     export_to_csv_folder,
     39     export_to_hdf5,
   (...)
     47     import_series_from_dataframe,
     48 )
     49 from pypsa.opf import network_lopf, network_opf
---> 50 from pypsa.optimization.optimize import OptimizationAccessor
     51 from pypsa.pf import (
     52     calculate_B_H,
     53     calculate_dependent_values,
   (...)
     62     sub_network_pf,
     63 )
     64 from pypsa.plot import iplot, plot

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/pypsa/optimization/__init__.py:7
      1 #!/usr/bin/env python3
      2 # -*- coding: utf-8 -*-
      3 """
      4 Build optimisation problems from PyPSA networks with Linopy.
      5 """
----> 7 from pypsa.optimization import abstract, constraints, optimize, variables
      8 from pypsa.optimization.optimize import create_model

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/pypsa/optimization/constraints.py:9
      6 import logging
      8 import pandas as pd
----> 9 from linopy.expressions import LinearExpression, merge
     10 from numpy import arange, cumsum, inf, nan, roll
     11 from scipy import sparse

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/linopy/__init__.py:9
      1 #!/usr/bin/env python3
      2 # -*- coding: utf-8 -*-
      3 """
      4 Created on Wed Mar 10 11:03:06 2021.
      5
      6 @author: fabulous
      7 """
----> 9 from linopy import model, remote
     10 from linopy.expressions import merge
     11 from linopy.io import read_netcdf

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/linopy/model.py:22
     20 from linopy import solvers
     21 from linopy.common import best_int, replace_by_map
---> 22 from linopy.constraints import (
     23     AnonymousConstraint,
     24     AnonymousScalarConstraint,
     25     Constraints,
     26 )
     27 from linopy.eval import Expr
     28 from linopy.expressions import LinearExpression, ScalarLinearExpression

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/linopy/constraints.py:21
     18 from scipy.sparse import coo_matrix
     19 from xarray import DataArray, Dataset
---> 21 from linopy import expressions, variables
     22 from linopy.common import (
     23     _merge_inplace,
     24     has_assigned_model,
   (...)
     27     replace_by_map,
     28 )
     31 class Constraint(DataArray):

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/linopy/expressions.py:23
     20 from xarray.core.dataarray import DataArrayCoordinates
     21 from xarray.core.groupby import _maybe_reorder, peek_at
---> 23 from linopy import constraints, variables
     24 from linopy.common import as_dataarray
     27 def exprwrap(method, *default_args, **new_default_kwargs):

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/site-packages/linopy/variables.py:398
    393     roll = varwrap(DataArray.roll)
    395     rolling = varwrap(DataArray.rolling)
--> 398 @dataclass(repr=False)
    399 class Variables:
    400     """
    401     A variables container used for storing multiple variable arrays.
    402     """
    404     labels: Dataset = Dataset()

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/dataclasses.py:1211, in dataclass.<locals>.wrap(cls)
   1210 def wrap(cls):
-> 1211     return _process_class(cls, init, repr, eq, order, unsafe_hash,
   1212                           frozen, match_args, kw_only, slots,
   1213                           weakref_slot)

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/dataclasses.py:959, in _process_class(cls, init, repr, eq, order, unsafe_hash, frozen, match_args, kw_only, slots, weakref_slot)
    956         kw_only = True
    957     else:
    958         # Otherwise it's a field of some type.
--> 959         cls_fields.append(_get_field(cls, name, type, kw_only))
    961 for f in cls_fields:
    962     fields[f.name] = f

File ~/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.21.2/lib/python3.11/dataclasses.py:816, in _get_field(cls, a_name, a_type, default_kw_only)
    812 # For real fields, disallow mutable defaults.  Use unhashable as a proxy
    813 # indicator for mutability.  Read the __hash__ attribute from the class,
    814 # not the instance.
    815 if f._field_type is _FIELD and f.default.__class__.__hash__ is None:
--> 816     raise ValueError(f'mutable default {type(f.default)} for field '
    817                      f'{f.name} is not allowed: use default_factory')
    819 return f

ValueError: mutable default <class 'xarray.core.dataset.Dataset'> for field labels is not allowed: use default_factory
[2]:
n = pypsa.examples.ac_dc_meshed(from_master=True)
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [2], line 1
----> 1 n = pypsa.examples.ac_dc_meshed(from_master=True)

NameError: name 'pypsa' is not defined

Now add a second wind generator at bus ‘Frankfurt’ and limit the combined capacity.

[3]:
n.add(
    "Generator",
    "Frankfurt Wind 2",
    bus="Frankfurt",
    capital_cost=120,
    carrier="wind",
    p_nom_extendable=True,
)

n.buses.loc[["Frankfurt", "Manchester"], "nom_min_wind"] = 2000
n.buses.loc[["Frankfurt"], "nom_max_wind"] = 2200
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [3], line 1
----> 1 n.add(
      2     "Generator",
      3     "Frankfurt Wind 2",
      4     bus="Frankfurt",
      5     capital_cost=120,
      6     carrier="wind",
      7     p_nom_extendable=True,
      8 )
     10 n.buses.loc[["Frankfurt", "Manchester"], "nom_min_wind"] = 2000
     11 n.buses.loc[["Frankfurt"], "nom_max_wind"] = 2200

NameError: name 'n' is not defined

We are running the lopf and check whether the constraint is fulfilled.

[4]:
n.lopf(pyomo=False)

print(n.generators.p_nom_opt)
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [4], line 1
----> 1 n.lopf(pyomo=False)
      3 print(n.generators.p_nom_opt)

NameError: name 'n' is not defined

Looks good! The generators of carrier ‘wind’ at bus ‘Frankfurt’ are just the limit of 2200 MW.