Note

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

Security-Constrained Optimisation

In this example, the dispatch of generators is optimised using the security-constrained linear OPF, to guaranteed that no branches are overloaded by certain branch outages.

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

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]:
network = pypsa.examples.scigrid_de(from_master=True)
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [2], line 1
----> 1 network = pypsa.examples.scigrid_de(from_master=True)

NameError: name 'pypsa' is not defined

There are some infeasibilities without line extensions.

[3]:
for line_name in ["316", "527", "602"]:
    network.lines.loc[line_name, "s_nom"] = 1200

now = network.snapshots[0]
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [3], line 2
      1 for line_name in ["316", "527", "602"]:
----> 2     network.lines.loc[line_name, "s_nom"] = 1200
      4 now = network.snapshots[0]

NameError: name 'network' is not defined

Performing security-constrained linear OPF

[4]:
branch_outages = network.lines.index[:15]
network.sclopf(now, branch_outages=branch_outages, solver_name="cbc")
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [4], line 1
----> 1 branch_outages = network.lines.index[:15]
      2 network.sclopf(now, branch_outages=branch_outages, solver_name="cbc")

NameError: name 'network' is not defined

For the PF, set the P to the optimised P.

[5]:
network.generators_t.p_set = network.generators_t.p_set.reindex(
    columns=network.generators.index
)
network.generators_t.p_set.loc[now] = network.generators_t.p.loc[now]

network.storage_units_t.p_set = network.storage_units_t.p_set.reindex(
    columns=network.storage_units.index
)
network.storage_units_t.p_set.loc[now] = network.storage_units_t.p.loc[now]
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [5], line 1
----> 1 network.generators_t.p_set = network.generators_t.p_set.reindex(
      2     columns=network.generators.index
      3 )
      4 network.generators_t.p_set.loc[now] = network.generators_t.p.loc[now]
      6 network.storage_units_t.p_set = network.storage_units_t.p_set.reindex(
      7     columns=network.storage_units.index
      8 )

NameError: name 'network' is not defined

Check no lines are overloaded with the linear contingency analysis

[6]:
p0_test = network.lpf_contingency(now, branch_outages=branch_outages)
p0_test
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [6], line 1
----> 1 p0_test = network.lpf_contingency(now, branch_outages=branch_outages)
      2 p0_test

NameError: name 'network' is not defined

Check loading as per unit of s_nom in each contingency

[7]:
max_loading = (
    abs(p0_test.divide(network.passive_branches().s_nom, axis=0)).describe().loc["max"]
)
max_loading
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [7], line 2
      1 max_loading = (
----> 2     abs(p0_test.divide(network.passive_branches().s_nom, axis=0)).describe().loc["max"]
      3 )
      4 max_loading

NameError: name 'p0_test' is not defined
[8]:
np.allclose(max_loading, np.ones((len(max_loading))))
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In [8], line 1
----> 1 np.allclose(max_loading, np.ones((len(max_loading))))

NameError: name 'np' is not defined