Note
You can download this example as a Jupyter notebook or start it in interactive mode.
Flow Plot Example#
Here, we are going to import a network and plot the electricity flow
[1]:
import pypsa, os
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import pandas as pd
import warnings
from shapely.errors import ShapelyDeprecationWarning
warnings.filterwarnings("ignore", category=ShapelyDeprecationWarning)
plt.rc("figure", figsize=(10, 8))
ERROR 1: PROJ: proj_create_from_database: Open of /home/docs/checkouts/readthedocs.org/user_builds/pypsa/conda/latest/share/proj failed
Import and optimize a network#
[2]:
n = pypsa.examples.ac_dc_meshed(from_master=True)
n.optimize()
WARNING:pypsa.io:Importing network from PyPSA version v0.17.1 while current version is v0.28.0. Read the release notes at https://pypsa.readthedocs.io/en/latest/release_notes.html to prepare your network for import.
INFO:pypsa.io:Imported network ac-dc-meshed.nc has buses, carriers, generators, global_constraints, lines, links, loads
WARNING:pypsa.components:The following lines have zero x, which could break the linear load flow:
Index(['2', '3', '4'], dtype='object', name='Line')
WARNING:pypsa.components:The following lines have zero r, which could break the linear load flow:
Index(['0', '1', '5', '6'], dtype='object', name='Line')
WARNING:pypsa.components:The following lines have zero x, which could break the linear load flow:
Index(['2', '3', '4'], dtype='object', name='Line')
WARNING:pypsa.components:The following lines have zero r, which could break the linear load flow:
Index(['0', '1', '5', '6'], dtype='object', name='Line')
INFO:linopy.model: Solve problem using Glpk solver
INFO:linopy.io: Writing time: 0.13s
INFO:linopy.solvers:GLPSOL--GLPK LP/MIP Solver 5.0
Parameter(s) specified in the command line:
--lp /tmp/linopy-problem-imy_0tj6.lp --output /tmp/linopy-solve-yeqivnqa.sol
Reading problem data from '/tmp/linopy-problem-imy_0tj6.lp'...
468 rows, 188 columns, 1007 non-zeros
2678 lines were read
GLPK Simplex Optimizer 5.0
468 rows, 188 columns, 1007 non-zeros
Preprocessing...
391 rows, 187 columns, 930 non-zeros
Scaling...
A: min|aij| = 9.693e-03 max|aij| = 1.215e+00 ratio = 1.254e+02
GM: min|aij| = 5.786e-01 max|aij| = 1.728e+00 ratio = 2.987e+00
EQ: min|aij| = 3.377e-01 max|aij| = 1.000e+00 ratio = 2.961e+00
Constructing initial basis...
Size of triangular part is 391
0: obj = -2.104321118e+07 inf = 9.486e+04 (101)
162: obj = 1.210828068e+07 inf = 1.864e-11 (0) 1
* 239: obj = -3.474256041e+06 inf = 1.755e-12 (0) 1
OPTIMAL LP SOLUTION FOUND
Time used: 0.0 secs
Memory used: 0.6 Mb (656771 bytes)
Writing basic solution to '/tmp/linopy-solve-yeqivnqa.sol'...
INFO:linopy.constants: Optimization successful:
Status: ok
Termination condition: optimal
Solution: 188 primals, 468 duals
Objective: -3.47e+06
Solver model: not available
Solver message: optimal
INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, Line-ext-s-lower, Line-ext-s-upper, Link-ext-p-lower, Link-ext-p-upper, Kirchhoff-Voltage-Law were not assigned to the network.
[2]:
('ok', 'optimal')
Get mean generator power by bus and carrier:
[3]:
gen = n.generators.assign(g=n.generators_t.p.mean()).groupby(["bus", "carrier"]).g.sum()
Plot the electricity flows:
[4]:
# links are not displayed for prettier output ('link_widths=0')
n.plot(
bus_sizes=gen / 5e3,
bus_colors={"gas": "indianred", "wind": "midnightblue"},
margin=0.5,
flow="mean",
line_widths=0.1,
link_widths=0,
)
plt.show()
/home/docs/checkouts/readthedocs.org/user_builds/pypsa/conda/latest/lib/python3.11/site-packages/cartopy/mpl/feature_artist.py:144: UserWarning: facecolor will have no effect as it has been defined as "never".
warnings.warn('facecolor will have no effect as it has been '
Plot the electricity flows with a different projection and a colored map:
[5]:
# links are not displayed for prettier output ('link_widths=0')
n.plot(
bus_sizes=gen / 5e3,
bus_colors={"gas": "indianred", "wind": "midnightblue"},
margin=0.5,
flow="mean",
line_widths=0.1,
link_widths=0,
projection=ccrs.EqualEarth(),
color_geomap=True,
)
plt.show()
/home/docs/checkouts/readthedocs.org/user_builds/pypsa/conda/latest/lib/python3.11/site-packages/cartopy/mpl/feature_artist.py:144: UserWarning: facecolor will have no effect as it has been defined as "never".
warnings.warn('facecolor will have no effect as it has been '
Set arbitrary values as flow argument using the MultiIndex of n.branches():
[6]:
flow = pd.Series(10, index=n.branches().index)
[7]:
flow
[7]:
component name
Link Norwich Converter 10
Norway Converter 10
Bremen Converter 10
DC link 10
Line 0 10
1 10
2 10
3 10
4 10
5 10
6 10
dtype: int64
[8]:
# links are not displayed for prettier output ('link_widths=0')
n.plot(
bus_sizes=gen / 5e3,
bus_colors={"gas": "indianred", "wind": "midnightblue"},
margin=0.5,
flow=flow,
line_widths=2.7,
link_widths=0,
projection=ccrs.EqualEarth(),
color_geomap=True,
)
plt.show()
/home/docs/checkouts/readthedocs.org/user_builds/pypsa/conda/latest/lib/python3.11/site-packages/cartopy/mpl/feature_artist.py:144: UserWarning: facecolor will have no effect as it has been defined as "never".
warnings.warn('facecolor will have no effect as it has been '
Adjust link colors according to their mean load:
[9]:
# Pandas series with MultiIndex
# links are not displayed for prettier output ('link_widths=0')
collection = n.plot(
bus_sizes=gen / 5e3,
bus_colors={"gas": "indianred", "wind": "midnightblue"},
margin=0.5,
flow=flow,
line_widths=2.7,
link_widths=0,
projection=ccrs.EqualEarth(),
color_geomap=True,
line_colors=n.lines_t.p0.mean().abs(),
)
plt.colorbar(collection[2], fraction=0.04, pad=0.004, label="Flow in MW")
plt.show()
/home/docs/checkouts/readthedocs.org/user_builds/pypsa/conda/latest/lib/python3.11/site-packages/cartopy/mpl/feature_artist.py:144: UserWarning: facecolor will have no effect as it has been defined as "never".
warnings.warn('facecolor will have no effect as it has been '
