[feature] KeyError: 'bus_dc'

[quant12345]

Feature Checklist

• Searched the issues page for similar feature requests

• Read the relevant sections of the documentation

• Browse the repository, tutorials and tests for already existing functionalities

Feature Type

• Adding new functionality to pandapower

• Changing existing functionality in pandapower

• Removing existing functionality in pandapower

Problem Description

In the julia build (3.9, 2) I see three tests with an error: KeyError: 'bus_dc'.
I assume this is because a non-existent key is being accessed.
results.py -> _get_aranged_lookup - row 83

this line:
if len(net[bus_table]) == 0:

Running the test: pytest pandapower/test/opf/test_pandamodels_runpm.py::test_runpm_multi_vstab

I tried adding setdefault before the line that causes the error:

net.setdefault(bus_table, np.array([], dtype=np.int64))# creates a dictionary key if it doesn't exist

but another error occurs:

FAILED pandapower/test/opf/test_pandamodels_runpm.py::test_runpm_multi_vstab - AttributeError: 'numpy.ndarray' object has no attribute 'index'

I haven't been able to figure out how the 'bus_dc' data is formed yet. Or is it in development and not ready yet?

Feature Description

Additional Context

No response

Label

• Relevant labels are selected

[yasirroni]

Hi @quant12345, can you test this on matpowercaseframes to? PowerModels accept arbitrary data as far as I know and matpowercaseframes not implemented that yet.

[quant12345]

Hi @yasirroni, my modest knowledge in this area is not enough. I have not yet figured out how the data is formed. I can assume that a dataframe should be created in the 'bus_dc' table, but it is not clear where it is formed. The error clearly says that there is no such key in the dictionary.
You created a topic today, I saw that it concerns julia. In Actions I saw

the following failure:

FAILED pandapower/test/opf/test_TNEP.py::test_pm_tnep_cigre_dc - julia.core.JuliaError: Exception 'LoadError: ArgumentError: Package PandaModels does not have PowerModels in its dependencies:
- You may have a partially installed environment. Try `Pkg.instantiate()`
  to ensure all packages in the environment are installed.
- Or, if you have PandaModels checked out for development and have
  added PowerModels as a dependency but haven't updated your primary
  environment's manifest file, try `Pkg.resolve()`.
- Otherwise you may need to report an issue with PandaModels
in expression starting at /home/runner/.julia/packages/PandaModels/H0sdB/src/PandaModels.jl:1' occurred while calling julia code:
using PandaModels
FAILED pandapower/test/opf/test_TNEP.py::test_pm_tnep_cigre_ac_S - julia.core.JuliaError: Exception 'UndefVarError: `run_powermodels_tnep` not defined' occurred while calling julia code:
run_powermodels_tnep(buffer_file)
FAILED pandapower/test/opf/test_pandamodels_runpm.py::test_compare_pwl_and_poly - pandapower.auxiliary.OPFNotConverged: PowerModels.jl OPF not converged
FAILED pandapower/test/opf/test_pandamodels_runpm.py::test_without_ext_grid - pandapower.auxiliary.OPFNotConverged: PowerModels.jl OPF not converged
FAILED pandapower/test/opf/test_pandamodels_runpm.py::test_storage_opt - KeyError: 'bus_dc'
FAILED pandapower/test/opf/test_pandamodels_runpm.py::test_runpm_multi_vstab - KeyError: 'bus_dc'
FAILED pandapower/test/opf/test_pandamodels_runpm.py::test_runpm_qflex_and_multi_qflex - KeyError: 'bus_dc'

I have the same thing locally in tests, except for the lines with FAILED pandapower/test/opf/test_TNEP.py.

[yasirroni]

Hi @quant12345, I finally success installing PandaModels. Now, I'm also stuck with this same issue, that is bus_dc.

[SimonUlm]

I think this is caused by the commit fcf7bd7. This also makes the SimBench plugin unusable.

[yasirroni]

Change to stable branch on master, test passed. Thanks @SimonUlm.

[vogt31337]

@quant12345 is this stil relevant?

[quant12345]

@vogt31337 I saw that in PR #2455 tests for julia (3.9, 2) pass. Need to ask @mfranz13 if there will be any more fixes in the code?

[mfranz13]

There was some unnecessary key dropping from the net object in the result extraction from PandaModels. Thanks for mentioning this issue to me.