The chosen solver, glpk, does not suport warmstart, which may impact performance.
ERROR: Solver (glpk) returned non-zero return code (1)
ERROR: See the solver log above for diagnostic information.
Traceback (most recent call last):
File "write.py", line 183, in <module>
File "C:\Daten\Tools\PortableApps\PortableApps\anaconda3\envs\calliope\lib\site-packages\calliope\core\model.py", line 261, in run
results, self._backend_model, interface = run_backend(
File "C:\Daten\Tools\PortableApps\PortableApps\anaconda3\envs\calliope\lib\site-packages\calliope\backend\run.py", line 54, in run
results, backend = run_operate(
File "C:\Daten\Tools\PortableApps\PortableApps\anaconda3\envs\calliope\lib\site-packages\calliope\backend\run.py", line 487, in run_operate
_results = backend.solve_model(
File "C:\Daten\Tools\PortableApps\PortableApps\anaconda3\envs\calliope\lib\site-packages\calliope\backend\pyomo\model.py", line 209, in solve_model
results = opt.solve(backend_model, tee=True, **solve_kwargs)
File "C:\Daten\Tools\PortableApps\PortableApps\anaconda3\envs\calliope\lib\site-packages\pyomo\opt\base\solvers.py", line 599, in solve
pyutilib.common._exceptions.ApplicationError: Solver (glpk) did not exit normally
(calliope) C:\Users\Lars Bretschneider\lblabr@owncloud\Projekte\calliope_models\models\00 - HEMS 03 - PV-BAT>
available_areaar the location level (see here for an example)
are there some issues in operate mode with 15-min intervals ?
Starte Time: 2021-01-11 04:00
End Time: 2021-01-13 23:45
Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
Possible issues found during model processing:
mipgap) or removing MILP constraints.
Traceback (most recent call last):
File "write.py", line 190, in <module>
File "C:\Daten\Tools\PortableApps\PortableApps\anaconda3\envs\calliope\lib\site-packages\calliope\core\model.py", line 256, in run
calliope.exceptions.ModelError: Unable to run this model in operational mode, probably because there exist non-uniform timesteps (e.g. from time masking)
I recently have started to use calliope. As I understood energy_cap variable can show the installed capacity over the subset of the studied period. But, it just gives a single value and is not a time series variable. For example, I am planning for a 15-year time horizon, and I want to know which tech in the year 7'th is installed? and how is the installed capacity value?
Hi @vahidsabzpoosh, currently calliope does not allow a dynamic capacity expansion, i.e. one which accounts for what happens in each year. It only allows a 'static' optimisation in which you get the 'final' capacity expansion. There is however a planned development in the direction you have in mind, e.g. see calliope-project/calliope#125
How do i model a battery with an minimal power restriction in timesteps of use ?
units_equals: 1 energy_cap_per_unit: 14800 energy_cap_min_use: 0.2 energy_cap_max: 14800 # kW storage_cap_per_unit: 14800 energy_eff: 1 # 0.95 * 0.95 = 0.9025 round trip efficiency storage_loss: 0.001 # No loss over time assumed lifetime: 25 costs: monetary: interest_rate: 0.11
does not work
i still playing around with operate mode, does have energy_cap_max at transmission technology any impact an the results ? i does not look like that ...
energy_cap_max is not really suited for operate mode, as it limits the maximum capacity the optimization procedure can allocate to a given technology in a given location.
and the "operate" mode does not perform any optimization on the installed capacities, only the "plan" mode