Example notebook
[1]:
import matplotlib.pyplot as plt
from pommes import test_case_path
from pommes.io.build_input_dataset import (
build_input_parameters,
read_config_file,
)
from pommes.io.save_solution import save_solution
from pommes.model.build_model import build_model
from pommes.model.data_validation.dataset_check import check_inputs
[2]:
scenario = "ref"
suffix = "_02161113"
output_folder = f"{test_case_path}/output/{scenario}{suffix}"
solver = "highs" # ["gurobi", "xpress", "highs", "mosek"]
[3]:
config = read_config_file(file_path=test_case_path / "config.yaml")
model_parameters = build_input_parameters(config)
model_parameters = check_inputs(model_parameters)
WARNING:root:Missing variables in input dataset. Adding defaults:
storage_energy_to_power_ratio: nan (type=float64)
[4]:
model = build_model(model_parameters)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[4], line 1
----> 1 model = build_model(model_parameters)
File /opt/conda/lib/python3.13/site-packages/pommes/model/build_model.py:94, in build_model(model_parameters)
88 p = model_parameters
90 operation_year_normalization = (
91 p.operation_year_duration / p.time_step_duration.sum("hour")
92 )
---> 94 m = Model()
96 # ------------
97 # Variables
98 # ------------
99
100 # Operation - load_shedding & spillage
102 operation_load_shedding_power = m.add_variables(
103 name="operation_load_shedding_power",
104 lower=0,
(...) 109 coords=[p.area, p.hour, p.resource, p.year_op],
110 )
File /opt/conda/lib/python3.13/site-packages/linopy/model.py:181, in Model.__init__(self, solver_dir, chunk, force_dim_names, auto_mask)
179 self._variables: Variables = Variables({}, model=self)
180 self._constraints: Constraints = Constraints({}, model=self)
--> 181 self._objective: Objective = Objective(LinearExpression(None, self), self)
182 self._parameters: Dataset = Dataset()
184 self._status: str = "initialized"
File /opt/conda/lib/python3.13/site-packages/linopy/expressions.py:384, in BaseExpression.__init__(self, data, model)
381 data = assign_multiindex_safe(data, **coeffs_vars_dict)
383 # transpose with new Dataset to really ensure correct order
--> 384 data = Dataset(data.transpose(..., TERM_DIM))
386 # ensure helper dimensions are not set as coordinates
387 if drop_dims := set(HELPER_DIMS).intersection(data.coords):
388 # TODO: add a warning here, routines should be safe against this
File /opt/conda/lib/python3.13/site-packages/xarray/core/dataset.py:389, in Dataset.__init__(self, data_vars, coords, attrs)
385 ) -> None:
386 if data_vars is None:
387 data_vars = {}
388 if isinstance(data_vars, Dataset):
--> 389 raise TypeError(
390 "Passing a Dataset as `data_vars` to the Dataset constructor is"
391 " not supported. Use `ds.copy()` to create a copy of a Dataset."
392 )
TypeError: Passing a Dataset as `data_vars` to the Dataset constructor is not supported. Use `ds.copy()` to create a copy of a Dataset.
[5]:
model.solve(solver_name=solver)
save_solution(
model=model,
output_folder=output_folder,
model_parameters=model_parameters,
)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[5], line 1
----> 1 model.solve(solver_name=solver)
2
3 save_solution(
4 model=model,
NameError: name 'model' is not defined
[6]:
solution = model.solution
print(model.solution)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[6], line 1
----> 1 solution = model.solution
2 print(model.solution)
NameError: name 'model' is not defined
[7]:
dual = model.dual
print(dual)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[7], line 1
----> 1 dual = model.dual
2 print(dual)
NameError: name 'model' is not defined
[8]:
prices = dual.operation_adequacy_constraint
df = prices.to_dataframe(name="value").reset_index()
print(df)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[8], line 1
----> 1 prices = dual.operation_adequacy_constraint
2 df = prices.to_dataframe(name="value").reset_index()
3 print(df)
NameError: name 'dual' is not defined
[9]:
unique_resources = df["resource"].unique()
unique_years = df["year_op"].unique()
unique_areas = df["area"].unique()
colors = plt.cm.tab10(range(len(unique_areas)))
area_color_map = {area: colors[i] for i, area in enumerate(unique_areas)}
fig, axes = plt.subplots(
len(unique_resources),
len(unique_years),
figsize=(15, 10),
sharex=True,
sharey="row",
)
for i, resource in enumerate(unique_resources):
for j, year in enumerate(unique_years):
ax = axes[i, j]
subset = df[(df["resource"] == resource) & (df["year_op"] == year)]
for area in unique_areas:
area_data = subset[subset["area"] == area]
if not area_data.empty:
ax.plot(
area_data["hour"],
area_data["value"],
marker="o",
color=area_color_map[area],
)
if i == 0:
ax.set_title(f"Year: {year}")
if j == 0:
ax.set_ylabel(f"Resource: {resource}")
if i == len(unique_resources) - 1:
ax.set_xlabel("Hour")
legend_elements = [
plt.Line2D(
[0],
[0],
marker="o",
color=color,
linestyle="",
markersize=8,
label=area,
)
for area, color in area_color_map.items()
]
fig.legend(
handles=legend_elements,
loc="upper center",
ncol=len(unique_areas),
title="Area",
)
plt.tight_layout(rect=(0, 0, 1, 0.95))
plt.show()
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[9], line 1
----> 1 unique_resources = df["resource"].unique()
2 unique_years = df["year_op"].unique()
3 unique_areas = df["area"].unique()
4 colors = plt.cm.tab10(range(len(unique_areas)))
NameError: name 'df' is not defined
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