[bug] The identified bug of function pandapower.converter.from_mpc for .m file #2403

Len02805 · 2024-09-23T09:07:40Z

Bug report checklis

Searched the issues page for similar reports
Read the relevant sections of the documentation
Browse the tutorials and tests for usefull code snippets and examples of use
Reproduced the issue after updating with pip install --upgrade pandapower (or git pull)
Tried basic troubleshooting (if a bug/error) like restarting the interpreter and checking the pythonpath

Reproducible Example

import pandapower as pp
net = pp.converter.from_mpc('/Your/path/to/Matpower/Cases/case69.m', f_hz=50, validate_conversion=False)
pp.runpp(net)

Issue Description and Traceback

The original file case69.m from https://github.com/MATPOWER/matpower/blob/master/data/case69.m cannot be converted to the right pp network. Actually, a lof of .m file under this dir (github.com/MATPOWER/matpower/blob/master/data) cannot be successfully processed.

This is becase the following code para in the ending of .m file is not corrected processed by "from_mpc" function:

%% convert brach impedances from Ohms to p.u.
[PQ, PV, REF, NONE, BUS_I, BUS_TYPE, PD, QD, GS, BS, BUS_AREA, VM, ...
    VA, BASE_KV, ZONE, VMAX, VMIN, LAM_P, LAM_Q, MU_VMAX, MU_VMIN] = idx_bus;
[F_BUS, T_BUS, BR_R, BR_X, BR_B, RATE_A, RATE_B, RATE_C, ...
    TAP, SHIFT, BR_STATUS, PF, QF, PT, QT, MU_SF, MU_ST, ...
    ANGMIN, ANGMAX, MU_ANGMIN, MU_ANGMAX] = idx_brch;
Vbase = mpc.bus(1, BASE_KV) * 1e3;      %% in Volts
Sbase = mpc.baseMVA * 1e6;              %% in VA
mpc.branch(:, [BR_R BR_X]) = mpc.branch(:, [BR_R BR_X]) / (Vbase^2 / Sbase);

%% convert loads from kW to MW
mpc.bus(:, [PD, QD]) = mpc.bus(:, [PD, QD]) / 1e3;

So for this .m file, if you add the follwoing code after

pandapower/pandapower/converter/matpower/from_mpc.py

Line 100 in a99f884

mpc_frames = CaseFrames(mpc_file)

    if mpc_file[-8:]=="case69.m":
        print("Activated for case 69")
        baseMVA69 = 10
        Sbase69 = baseMVA69 * 1e6
        Vbase69 = 12.66 * 1e3
        mpc_frames.branch[["BR_R", "BR_X"]] = mpc_frames.branch[["BR_R", "BR_X"]] / (Vbase69**2 / Sbase69)
        mpc_frames.bus[["PD", "QD"]] = mpc_frames.bus[["PD", "QD"]]/1000

Then the reproducible Example can be successfully run by pandapower as smoothly and accurately as the matlab :)

However, this is the customized method for this spcific .m file. It would be helpful if you guys could rewrite a more general method.

Expected Behavior

Fix the bug as I mentioned :)

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2ee5a58015ef6f4d15c7226110c9aab8140
python : 3.9.15.final.0
python-bits : 64
OS : Darwin
OS-release : 23.3.0
Version : Darwin Kernel Version 23.3.0: Thu Dec 21 02:29:41 PST 2023; root:xnu-10002.81.5~11/RELEASE_ARM64_T8122
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

pandas : 2.2.2
numpy : 1.23.5
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 73.0.0
pip : 24.0
Cython : None
pytest : 8.3.2
hypothesis : None
sphinx : 7.4.7
blosc : None
feather : None
xlsxwriter : 3.2.0
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.9
jinja2 : 3.1.4
IPython : 8.18.1
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : 1.3.7
dataframe-api-compat : None
fastparquet : 2024.5.0
fsspec : 2024.6.1
gcsfs : None
matplotlib : 3.8.4
numba : 0.60.0
numexpr : 2.8.7
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
pyarrow : 17.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.13.1
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : 2024.7.0
xlrd : 2.0.1
zstandard : None
tzdata : 2023.3
qtpy : 2.4.1
pyqt5 : None

Label

Relevant labels are selected

The text was updated successfully, but these errors were encountered:

yasirroni · 2024-09-24T09:47:22Z

Hi, I'm matpowercaseframes and matpower-pip developer. The easiest way to solve it is to run matpower-pip.

from matpower import start_instance

from matpowercaseframes import CaseFrames

m = start_instance()
CASE_NAME = "case16am.m"
cf_16am = CaseFrames(CASE_NAME)

Then, after the line 100, we should introduce something like

ppc = {key: mpc_frames.__getattribute__(key) if not isinstance(
        mpc_frames.__getattribute__(key), pd.DataFrame) else mpc_frames.__getattribute__(
        key).values for key in mpc_frames._attributes}
    _adjust_ppc_indices(ppc)

See: https://github.com/UGM-EPSLab/matpowercaseframes/blob/master/notebooks/load_case16am.ipynb

Let's wait pandapower developer on the best way to integrate this to pandapower.

Len02805 · 2024-09-24T10:21:36Z

Hi Yasirroni,

I know the m = start_instance() should work as you mentioned in #1556.

However, as you also mentioned in the above link "Sadly, it need a third parties octave.cli." and actually the oct2py package is unstable as well. BTW, I had a bug with function start_instance(). But I do not have enough time and interest to investigate the reason as it doesn't affect my work.

error: graphics_toolkit: = toolkit is not available error: called from graphics_toolkit at line 84 column 5

Sadly, we fall in a loop between two fairly unstable dependency packages while using pandapower :(

yasirroni · 2024-09-24T23:04:10Z

Handling per name file like if mpc_file[-8:]=="case69.m": is not wise and I think it should not be implemented.

In my case, oct2py is pretty stable and reliable. If you got a problem in installing matpower-pip or oct2py, you should report the issue in their respective repo. You can mention me there with complete debugging or info if possible.

Len02805 · 2024-09-24T23:37:02Z

Yes, as I mentioned, "this is a customized method for this spcific .m file. It would be helpful if you guys could rewrite a more general method". I post this spcific method for insight the debug solution. Appreantly you cannot implement this into the pandapower public package.

yasirroni · 2024-09-25T01:50:54Z

pandapower relies on matpowercaseframes to read .m file. Solution to read that file is already solved with matpowercaseframes and matpower-pip.

If you don't want to use matpowercaseframes and matpower-pip, run matlab/octave, iterate loop save as .mat, then pandapower will be able to use scipy.io.

I think that is the best possible way here.

Len02805 · 2024-09-25T02:19:49Z

If you run the reproducible example above, you will get an error.

yasirroni · 2024-09-25T02:23:51Z

If you run the reproducible example above, you will get an error.

Which code? Which error?

yasirroni · 2024-09-25T02:27:24Z

from matpower import start_instance

from matpowercaseframes import CaseFrames

m = start_instance()
CASE_NAME = "case16am.m"
cf_16am = CaseFrames(CASE_NAME, load_case_engine=m)

import numpy as np
import pandas as pd

def _adjust_ppc_indices(ppc):
    # adjust indices of ppc, since ppc must start at 0 rather than 1 (matlab)
    ppc["bus"][:, 0] -= 1
    ppc["branch"][:, 0] -= 1
    ppc["branch"][:, 1] -= 1
    # if in ppc is only one gen -> numpy initially uses one dim array -> change to two dim array
    if len(ppc["gen"].shape) == 1:
        ppc["gen"] = np.array(ppc["gen"], ndmin=2)
    ppc["gen"][:, 0] -= 1

mpc_frames = cf_16am
ppc = {key: mpc_frames.__getattribute__(key) if not isinstance(
        mpc_frames.__getattribute__(key), pd.DataFrame) else mpc_frames.__getattribute__(
        key).values for key in mpc_frames._attributes}
_adjust_ppc_indices(ppc)
print(ppc)

{'version': '2',
 'baseMVA': 10.0,
 'bus': array([[ 0.  ,  3.  ,  0.  ,  0.  ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.  ,  1.  ],
        [ 1.  ,  1.  ,  0.  ,  0.  ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 2.  ,  1.  ,  2.  ,  1.6 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 3.  ,  1.  ,  3.  ,  0.4 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 4.  ,  1.  ,  2.  , -0.4 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 5.  ,  1.  ,  1.5 ,  1.2 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 6.  ,  1.  ,  4.  ,  2.7 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 7.  ,  1.  ,  5.  ,  1.8 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 8.  ,  1.  ,  1.  ,  0.9 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [ 9.  ,  1.  ,  0.6 , -0.5 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [10.  ,  1.  ,  4.5 , -1.7 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [11.  ,  1.  ,  1.  ,  0.9 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [12.  ,  1.  ,  1.  , -1.1 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [13.  ,  1.  ,  1.  ,  0.9 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ],
        [14.  ,  1.  ,  2.1 , -0.8 ,  0.  ,  0.  ,  1.  ,  1.  ,  0.  ,
         12.66,  1.  ,  1.1 ,  0.9 ]]),
 'gen': array([[  0.,   0.,   0.,  10., -10.,   1., 100.,   1.,  10.,   0.,   0.,
           0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.]]),
 'branch': array([[ 0.00000000e+00,  1.00000000e+00,  0.00000000e+00,
          6.23925289e-10,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 1.00000000e+00,  2.00000000e+00,  7.49958197e-03,
          1.00015224e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 2.00000000e+00,  3.00000000e+00,  7.99872220e-03,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 2.00000000e+00,  4.00000000e+00,  8.99700266e-03,
          1.80002446e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 4.00000000e+00,  5.00000000e+00,  3.99936110e-03,
          3.99936110e-03,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 1.00000000e+00,  6.00000000e+00,  1.09998028e-02,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 6.00000000e+00,  7.00000000e+00,  7.99872220e-03,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 6.00000000e+00,  8.00000000e+00,  1.09998028e-02,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 7.00000000e+00,  9.00000000e+00,  1.09998028e-02,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 7.00000000e+00,  1.00000000e+01,  7.99872220e-03,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 1.00000000e+00,  1.10000000e+01,  1.09998028e-02,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 1.10000000e+01,  1.20000000e+01,  8.99700266e-03,
          1.19980833e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 1.10000000e+01,  1.30000000e+01,  7.99872220e-03,
          1.09998028e-02,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02],
        [ 1.30000000e+01,  1.40000000e+01,  3.99936110e-03,
          3.99936110e-03,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
          0.00000000e+00,  1.00000000e+00, -3.60000000e+02,
          3.60000000e+02]]),
 'gencost': array([[ 2.,  0.,  0.,  3.,  0., 20.,  0.]])}

Len02805 · 2024-09-25T08:34:33Z

import pandapower as pp
net = pp.converter.from_mpc('/Your/path/to/Matpower/Cases/case69.m', f_hz=50, validate_conversion=False)
pp.runpp(net)

FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
  net[table] = pd.concat([net[table], dd[dd.columns[~dd.isnull().all()]]], sort=False)
/opt/anaconda3/envs/Envs/lib/python3.9/site-packages/pandapower/converter/pypower/from_ppc.py:277: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '[]' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.
  branch_lookup.loc[~is_line, "element"] = idx_trafo
---------------------------------------------------------------------------
LoadflowNotConverged                      Traceback (most recent call last)
Cell In[2], line 3
      1 network = pp.converter.from_mpc('case69.m', f_hz=50, validate_conversion=False)
      2 network.line["max_i_ka"]=0.1
----> 3 pp.runpp(network)

File /opt/anaconda3/envs/Envs/lib/python3.9/site-packages/pandapower/run.py:250, in runpp(net, algorithm, calculate_voltage_angles, init, max_iteration, tolerance_mva, trafo_model, trafo_loading, enforce_q_lims, check_connectivity, voltage_depend_loads, consider_line_temperature, run_control, distributed_slack, tdpf, tdpf_delay_s, **kwargs)
    248 _check_bus_index_and_print_warning_if_high(net)
    249 _check_gen_index_and_print_warning_if_high(net)
--> 250 _powerflow(net, **kwargs)

File /opt/anaconda3/envs/Envs/lib/python3.9/site-packages/pandapower/powerflow.py:86, in _powerflow(net, **kwargs)
     84 result = _run_pf_algorithm(ppci, net["_options"], **kwargs)
     85 # read the results (=ppci with results) to net
---> 86 _ppci_to_net(result, net)

File /opt/anaconda3/envs/Envs/lib/python3.9/site-packages/pandapower/powerflow.py:190, in _ppci_to_net(result, net)
    188     algorithm = net["_options"]["algorithm"]
    189     max_iteration = net["_options"]["max_iteration"]
--> 190     raise LoadflowNotConverged("Power Flow {0} did not converge after "
    191                                "{1} iterations!".format(algorithm, max_iteration))
    192 else:
    193     net["_ppc"] = result

LoadflowNotConverged: Power Flow nr did not converge after 10 iterations!

matpowercaseframes==1.0.8
matpower==8.0.0.2.1.8
pandapower==2.14.11

yasirroni · 2024-09-25T09:59:29Z

Hmm, something must be wrong here.

from matpower import start_instance

from matpowercaseframes import CaseFrames

m = start_instance()
CASE_NAME = "case16am.m"
cf = CaseFrames(CASE_NAME, load_case_engine=m)

import numpy as np
import pandas as pd

def _adjust_ppc_indices(ppc):
    # adjust indices of ppc, since ppc must start at 0 rather than 1 (matlab)
    ppc["bus"][:, 0] -= 1
    ppc["branch"][:, 0] -= 1
    ppc["branch"][:, 1] -= 1

    # if in ppc is only one gen -> numpy initially uses one dim array -> change to two dim array
    if len(ppc["gen"].shape) == 1:
        ppc["gen"] = np.array(ppc["gen"], ndmin=2)
    ppc["gen"][:, 0] -= 1

mpc_frames = cf
ppc = {key: mpc_frames.__getattribute__(key) if not isinstance(
        mpc_frames.__getattribute__(key), pd.DataFrame) else mpc_frames.__getattribute__(
        key).values for key in mpc_frames._attributes}
_adjust_ppc_indices(ppc)

import pandapower as pp
import pandapower.converter as pc


net = pc.from_ppc(ppc)
pp.runpp(net)

LoadflowNotConverged: Power Flow nr did not converge after 10 iterations!

Len02805 · 2024-09-25T10:21:17Z

Yes. This is supposed to be that the following codes in the ending of .m file is not corrected processed by "from_mpc" function:

For your "case16am.m" case, the para should be:

%% convert branch impedances from Ohms to p.u.
[PQ, PV, REF, NONE, BUS_I, BUS_TYPE, PD, QD, GS, BS, BUS_AREA, VM, ...
    VA, BASE_KV, ZONE, VMAX, VMIN, LAM_P, LAM_Q, MU_VMAX, MU_VMIN] = idx_bus;
[F_BUS, T_BUS, BR_R, BR_X, BR_B, RATE_A, RATE_B, RATE_C, ...
    TAP, SHIFT, BR_STATUS, PF, QF, PT, QT, MU_SF, MU_ST, ...
    ANGMIN, ANGMAX, MU_ANGMIN, MU_ANGMAX] = idx_brch;
Vbase = mpc.bus(1, BASE_KV) * 1e3;      %% in Volts
Sbase = mpc.baseMVA * 1e6;              %% in VA
mpc.branch(:, [BR_R BR_X]) = mpc.branch(:, [BR_R BR_X]) / (Vbase^2 / Sbase);

%% convert loads from kW to MW
mpc.bus(:, [PD, QD]) = mpc.bus(:, [PD, QD]) / 1e3;

Which code? Which error?

Now you find and reproduce the code and error :)

yasirroni · 2024-09-26T04:05:34Z

Now you find and reproduce the code and error :)

@Len02805 No, it seems you don't understand it yet. load_case_engine already execute the MATLAB code of:

%% convert branch impedances from Ohms to p.u.
[PQ, PV, REF, NONE, BUS_I, BUS_TYPE, PD, QD, GS, BS, BUS_AREA, VM, ...
    VA, BASE_KV, ZONE, VMAX, VMIN, LAM_P, LAM_Q, MU_VMAX, MU_VMIN] = idx_bus;
[F_BUS, T_BUS, BR_R, BR_X, BR_B, RATE_A, RATE_B, RATE_C, ...
    TAP, SHIFT, BR_STATUS, PF, QF, PT, QT, MU_SF, MU_ST, ...
    ANGMIN, ANGMAX, MU_ANGMIN, MU_ANGMAX] = idx_brch;
Vbase = mpc.bus(1, BASE_KV) * 1e3;      %% in Volts
Sbase = mpc.baseMVA * 1e6;              %% in VA
mpc.branch(:, [BR_R BR_X]) = mpc.branch(:, [BR_R BR_X]) / (Vbase^2 / Sbase);

%% convert loads from kW to MW
mpc.bus(:, [PD, QD]) = mpc.bus(:, [PD, QD]) / 1e3;

yasirroni · 2024-09-26T09:44:11Z

After checking, even MATPOWER itself did not converge. Using other file, that is case69.m, my example is working.

from matpower import start_instance

from matpowercaseframes import CaseFrames

m = start_instance()
CASE_NAME = 'case69.m`
cf = CaseFrames(CASE_NAME, load_case_engine=m)

mpc_frames = cf

if CASE_NAME == 'case16am.m':
    baseMVA69 = 10
    Sbase69 = baseMVA69 * 1e6
    Vbase69 = 12.66 * 1e3
    mpc_frames.branch[["BR_R", "BR_X"]] = mpc_frames.branch[["BR_R", "BR_X"]] / (Vbase69**2 / Sbase69)
    mpc_frames.bus[["PD", "QD"]] = mpc_frames.bus[["PD", "QD"]]/1000

import numpy as np
import pandas as pd

def _adjust_ppc_indices(ppc):
    # adjust indices of ppc, since ppc must start at 0 rather than 1 (matlab)
    ppc["bus"][:, 0] -= 1
    ppc["branch"][:, 0] -= 1
    ppc["branch"][:, 1] -= 1

    # if in ppc is only one gen -> numpy initially uses one dim array -> change to two dim array
    if len(ppc["gen"].shape) == 1:
        ppc["gen"] = np.array(ppc["gen"], ndmin=2)
    ppc["gen"][:, 0] -= 1

ppc = {key: mpc_frames.__getattribute__(key) if not isinstance(
        mpc_frames.__getattribute__(key), pd.DataFrame) else mpc_frames.__getattribute__(
        key).values for key in mpc_frames._attributes}
_adjust_ppc_indices(ppc)

import pandapower as pp
import pandapower.converter as pc


net = pc.from_ppc(ppc, f_hz=60, validate_conversion=False)
if "mpc_additional_data" in ppc:
    if "_options" not in net:
        net["_options"] = dict()
    net._options.update(ppc["mpc_additional_data"])

try:
    pp.runpp(net)
except Exception as e:
    print(e)

If cf = CaseFrames(CASE_NAME, load_case_engine=m) changed to cf = CaseFrames(CASE_NAME) (currently used by pandapower), the NR will not converge.

So, the correct use of matpowercaseframes in this case is to use load_case_engine.

yasirroni · 2024-09-26T09:48:40Z

As mentioned in MATPOWER/matpower#208, case16am.m is non convergent case. My bad changing your initial case69.m to case16am.m.

Len02805 · 2024-09-29T01:37:46Z

Yes, it seems you understand this bug in Pandapower on using matpowercaseframes (load_case_engine).

Len02805 added the bug label Sep 23, 2024

yasirroni mentioned this issue Sep 26, 2024

Example the importance of load_case_engine UGM-EPSLab/matpowercaseframes#12

Merged

vogt31337 added the converter label Nov 21, 2024

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[bug] The identified bug of function pandapower.converter.from_mpc for .m file #2403

[bug] The identified bug of function pandapower.converter.from_mpc for .m file #2403

Len02805 commented Sep 23, 2024 •

edited by KS-HTK

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[bug] The identified bug of function pandapower.converter.from_mpc for .m file #2403

[bug] The identified bug of function pandapower.converter.from_mpc for .m file #2403

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