Hello everyone,
I have a question regarding repeated solution of an oemof model, e.g. in the context of model predictive control. For performance reasons it would be interesting to be able to re-use an already instantiated oemof model. The workflow would be as follows:
-
instantiate oemof model
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solve model
-
change parameters
-
solve model
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goto 3.
The parameters I want to change would be the time series for load, costs, … so the model topology would stay the same. I know that this is possible for a pyomo ConcreteModel() by declaring your parameters with pyo.Param() and adapting the values in between calls of solve(), see Manipulating Pyomo Models — Pyomo 6.8.1 documentation .
So far my impression is that oemof does not use pyo.Param’s, at least I couldn’t find any after instantiating the model. So, does anybody know how to accomplish this with oemof?
On a related side-note, it would be nice if the time step could vary in between repeated solves.
Thanks in advance.