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

Len02805 commented 1 month ago

Bug report checklis

[X] Searched the issues page for similar reports
[X] Read the relevant sections of the documentation
[X] Browse the tutorials and tests for usefull code snippets and examples of use
[X] Reproduced the issue after updating with pip install --upgrade pandapower (or git pull)
[X] 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 to /opt/anaconda3/envs/env_name/lib/python3.9/site-packages/pandapower/converter/matpower/from_mpc.py after the code line 100

    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

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yasirroni commented 1 month ago

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 commented 1 month ago

Hi Yasirroni,

I know the m = start_instance() should work as you mentioned in https://github.com/e2nIEE/pandapower/issues/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 commented 1 month ago

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 commented 1 month ago

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 commented 1 month ago

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 commented 1 month ago

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

yasirroni commented 1 month ago

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

Which code? Which error?

yasirroni commented 1 month ago

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 commented 1 month ago

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 commented 1 month ago

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 commented 1 month ago

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 commented 1 month ago

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 commented 1 month ago

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 commented 1 month ago

As mentioned in https://github.com/MATPOWER/matpower/issues/208, case16am.m is non convergent case. My bad changing your initial case69.m to case16am.m.

Len02805 commented 1 month ago

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

e2nIEE / pandapower