Version Checks (indicate both or one)

• I have confirmed this bug exists on the lastest release of PyPSA.

• I have confirmed this bug exists on the current master branch of PyPSA.

Issue Description

I'm running a simple example using PyPSA and it used to work on the previous version 0.35.2. On v1.0.0, it seems that the index in the define_operational_constraints_for_extendables (lhs_lower = dispatch - min_pu * capacity) is misnaming it to "dim_0" instead of "snapshot".

Reproducible Example

import pandas as pd
import pypsa

periods = [2025, 2030]
timestamps_2025 = pd.date_range("2025-08-11 00:00", periods=4, freq="H")
timestamps_2030 = pd.date_range("2030-08-11 00:00", periods=4, freq="H")
period_labels = [2025] * len(timestamps_2025) + [2030] * len(timestamps_2030)
timestamps = list(timestamps_2025) + list(timestamps_2030)
multi_snapshots = pd.MultiIndex.from_arrays(
    [period_labels, timestamps], names=["period", "timestamp"]
)
network = pypsa.Network()
network.set_snapshots(multi_snapshots)
weightings = pd.Series(
    [1.0, 1.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0], index=multi_snapshots, name="objective"
)
network.snapshot_weightings = weightings
network.snapshot_weightings["period"] = network.snapshots.get_level_values("period")

network.investment_periods = pd.Index([2025, 2030])
network.investment_period_weightings["discount_rate"] = 0.05
network.investment_period_weightings["objective"] = {2025: 1, 2030: 1}
network.investment_period_weightings["years"] = {2025: 5, 2030: 5}

if "period" in network.snapshot_weightings.columns:
    network.snapshot_weightings = network.snapshot_weightings.drop(columns="period")

network.add("Bus", "bus0")
network.add("Carrier", "gas", co2_emissions=0.5)  # tCO2 per MWh
network.add("Carrier", "wind", co2_emissions=0.0)
# Add fossil generator (with emissions)
network.add(
    "Generator",
    "gen0",
    bus="bus0",
    p_nom=100,
    marginal_cost=10,
    p_nom_extendable=True,
    capital_cost=60,
    carrier="gas",
)
# Add wind generator (no emissions)
network.add(
    "Generator",
    "wind0",
    bus="bus0",
    p_nom=80,
    marginal_cost=0,
    p_nom_extendable=True,
    capital_cost=100,
    carrier="wind",
)

load_series = pd.Series(120, index=network.snapshots)
network.add("Load", "load0", bus="bus0", p_set=load_series)

availability = pd.DataFrame(
    {
        "gen0": [1.0, 0.8, 0.5, 0.4] * 2,
        "wind0": [0.4, 0.2, 0.3, 0.1] * 2,
    },
    index=network.snapshots,
)
network.generators_t.p_max_pu = availability

positive_snapshots = weightings[weightings > 0].index
network.set_snapshots(positive_snapshots)
network.snapshot_weightings = weightings.loc[positive_snapshots]
model = network.optimize.create_model(multi_investment_periods=True)

solve_status, solve_condition = network.optimize.solve_model(
    assign_all_duals=True,
    solver_name="highs",
)

Expected Behavior

Traceback (most recent call last):
File "C:\Users\mbui\Desktop\git\Snakemake_Minimal_Example\min_example.py", line 69, in
model = network.optimize.create_model(multi_investment_periods=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\mbui\Desktop\github\PyPSA\pypsa\optimization\optimize.py", line 568, in create_model
define_operational_constraints_for_extendables(
File "C:\Users\mbui\Desktop\github\PyPSA\pypsa\optimization\constraints.py", line 185, in define_operational_constraints_for_extendables
lhs_lower = dispatch - min_pu * capacity
~~~~~~~~~^~~~~~~~~~~~~~~~~~~
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\linopy\variables.py", line 500, in sub
return self.to_linexpr() - other
~~~~~~~~~~~~~~~~~~^~~~~~~
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\linopy\expressions.py", line 1329, in sub
return self.add(-other)
^^^^^^^^^^^^^^^^^^^^
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\linopy\expressions.py", line 1301, in add
return merge([self, other], cls=self.class)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\linopy\expressions.py", line 2004, in merge
ds = xr.concat([d[["coeffs", "vars"]] for d in data], dim, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\xarray\structure\concat.py", line 295, in concat
return _dataset_concat(
^^^^^^^^^^^^^^^^
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\xarray\structure\concat.py", line 613, in _dataset_concat
align(
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\xarray\structure\alignment.py", line 968, in align
aligner.align()
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\xarray\structure\alignment.py", line 660, in align
self.align_indexes()
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\xarray\structure\alignment.py", line 497, in align_indexes
update_dicts(key, joined_index, joined_index_vars, need_reindex)
File "C:\Users\mbui.venv\snakemake_pypsa_p312\Lib\site-packages\xarray\structure\alignment.py", line 419, in update_dicts
raise AlignmentError(
xarray.structure.alignment.AlignmentError: cannot align objects on coordinate 'period' because of conflicting indexes
first index: PandasIndex(MultiIndex([(2025, '2025-08-11 00:00:00'),
(2025, '2025-08-11 01:00:00'),
(2025, '2025-08-11 03:00:00'),
(2030, '2030-08-11 00:00:00'),
(2030, '2030-08-11 02:00:00'),
(2030, '2030-08-11 03:00:00')],
name='dim_0'))
second index: PandasIndex(MultiIndex([(2025, '2025-08-11 00:00:00'),
(2025, '2025-08-11 01:00:00'),
(2025, '2025-08-11 03:00:00'),
(2030, '2030-08-11 00:00:00'),
(2030, '2030-08-11 02:00:00'),
(2030, '2030-08-11 03:00:00')],
name='snapshot'))
first variable: <xarray.IndexVariable 'dim_0' (dim_0: 6)> Size: 48B
second variable: <xarray.IndexVariable 'snapshot' (snapshot: 6)> Size: 48B
[6 values with dtype=int64]

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