ntnuiotenergy / openempire Goto Github PK

8): 68422.0, ('France', 719, 'scenario5', 8): 67613.0, ('France',
720, 'scenario5', 8): 69987.0} failed: RuntimeError: Failed to set value for
param=sloadRaw, index=('Germany', 1, 'scenario1', 4), value=57195.1825.
source error message="Index '('Germany', 1, 'scenario1', 4)' is not
valid for indexed component 'sloadRaw'"
Traceback (most recent call last):

File ~\anaconda3\lib\site-packages\pyomo\core\base\param.py:808 in construct
self._setitem_when_not_present(self._validate_index(key), val)

File ~\anaconda3\lib\site-packages\pyomo\core\base\indexed_component.py:874 in _validate_index
raise KeyError(

KeyError: "Index '('Germany', 1, 'scenario1', 4)' is not valid for indexed component 'sloadRaw'"

During handling of the above exception, another exception occurred:

Traceback (most recent call last):

File ~\anaconda3\lib\site-packages\spyder_kernels\py3compat.py:356 in compat_exec
exec(code, globals, locals)

File c:\users\lothar\documents\github\openempire\run.py:122
run_empire(name = name,

File ~\Documents\GitHub\OpenEMPIRE\Empire.py:755 in run_empire
instance = model.create_instance(data) #, report_timing=True)

File ~\anaconda3\lib\site-packages\pyomo\core\base\PyomoModel.py:734 in create_instance
instance.load(data, namespaces=_namespaces, profile_memory=profile_memory)

File ~\anaconda3\lib\site-packages\pyomo\core\base\PyomoModel.py:771 in load
self._load_model_data(dp, namespaces, profile_memory=profile_memory)

File ~\anaconda3\lib\site-packages\pyomo\core\base\PyomoModel.py:823 in _load_model_data
self._initialize_component(

File ~\anaconda3\lib\site-packages\pyomo\core\base\PyomoModel.py:871 in _initialize_component
declaration.construct(data)

File ~\anaconda3\lib\site-packages\pyomo\core\base\param.py:811 in construct
raise RuntimeError(

RuntimeError: Failed to set value for param=sloadRaw, index=('Germany', 1, 'scenario1', 4), value=57195.1825.
source error message="Index '('Germany', 1, 'scenario1', 4)' is not valid for indexed component 'sloadRaw'"

To enhance software quality and rule out problems with commits to the master branch the project should be setup with a continuous integration system to test changes that are push to the central repository,

A prerequisite would be to setup an optimization instance that can be run smoothly without the use of a commercial solver as this would be difficult to use with the relevant CI services due to licensing. The instance "test" can be a good candidate for this.

Possible CI options are either Github Actions or Travis

The current documentation practice, writing the documentation in a MS word file and converting to a pdf, does not allow for proper source control and may prohibit (or at least complicate) community contributions.

The documentation should be moved to a system that better allows source control, such as sphinx or readthedocs.

In the current version of OpenEMPIRE the config_run.yaml file only includes a hand-full of the possible configurations one can imagine using for optimization runs. As of now the user has to interact with the model through the excel input files to run sensitivity analysis, however, some configurations (e.g. enabling/disabling technologies for investment and level of transmission expansion permitted) could easily be changed upon run-time if the configuration file allowed.

Also, more general settings could be added to config_run.yaml,, e.g. optimization solver settings and log level which are currently hardcoded in Empire.py.

We should review and restructure the files config_run.yaml, run.py and Empire.py to improve flexibility in model run.

Currently the full EMPIRE model setup and solution is handled in a single function run_empire in Empire.py. There are a number of ways to split it up into several more specialized functions which can be called from the main run_empire function. The advantage would firstly be improved code readability as it would be clearer which parts are sort of self-contained. Secondly, it would be possible to write unit tests for the individual functions which can be run in a continuous integration framework.