Model.results() error in oemof 3.1

Hello,
I made a Modell in oemof which worked perfectly fine in oemof 2.4 and now I wanted to test it in oemof 3.1 and got this error:

Traceback (most recent call last):
File “/usr/lib/python3.7/code.py”, line 90, in runcode
exec(code, self.locals)
File “”, line 1, in
File “/snap/pycharm-community/132/helpers/pydev/_pydev_bundle/pydev_umd.py”, line 197, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File “/snap/pycharm-community/132/helpers/pydev/_pydev_imps/_pydev_execfile.py”, line 18, in execfile
exec(compile(contents+"\n", file, ‘exec’), glob, loc)
File “/home/philipp/Schreibtisch/oemof_new/oemof/solph/test_systems/1_system.py”, line 76, in
model.results()
File “/home/philipp/Schreibtisch/oemof_new/oemof/solph/models.py”, line 146, in results
result = processing.results(self)
File “/home/philipp/Schreibtisch/oemof_new/oemof/outputlib/processing.py”, line 111, in results
df = create_dataframe(om)
File “/home/philipp/Schreibtisch/oemof_new/oemof/outputlib/processing.py”, line 89, in create_dataframe
df[‘timestep’] = df[‘oemof_tuple’].map(get_timestep)
File “/home/philipp/.local/lib/python3.7/site-packages/pandas/core/series.py”, line 2998, in map
arg, na_action=na_action)
File “/home/philipp/.local/lib/python3.7/site-packages/pandas/core/base.py”, line 1004, in _map_values
new_values = map_f(values, mapper)
File “pandas/_libs/src/inference.pyx”, line 1472, in pandas._libs.lib.map_infer
File “/home/philipp/Schreibtisch/oemof_new/oemof/outputlib/processing.py”, line 45, in get_timestep
if all(issubclass(type(n), Node) for n in x):
TypeError: ‘NoneType’ object is not iterable

I am even able to solve the model, but when I use:
model.results()
I get an error… Has anyone an idea what the problem could be?

Best, Philipp

As I do not know anything about your model it is difficult to help.

A good way is to reduce the number of components of your system. For example you could remove all storage and check if the problem persists. You also should check if the problem ends with an optimal status.