Inbuilt math¶
As of Calliope version 0.7, the math used to build optimisation problems is stored in YAML files. The inbuilt math is a re-implementation of the formerly hardcoded math formulation in this YAML format.
The base math is always applied to your model when you build
the optimisation problem.
In addition, there are other math formulation files built in which you can load into your model.
For instance, the inter-cluster storage math allows you to track storage levels in technologies more accurately when you are using timeseries clustering in your model.
To load one of the built-in math files, you can reference it by name (without the file extension) in your model configuration:
When solving the model in a run mode other than plan
, some built-in custom math will be applied automatically from a file of the same name (e.g., spores
mode custom math is stored in math/spores.yaml).
Note
Custom math is applied in the order it appears in the config.init.custom_math
list.
By default, any run mode custom math will be applied as the final step.
If you want to apply your own custom math after the run mode custom math, you should add the name of the run mode explicitly to the config.init.custom_math
list, e.g., config.init.custom_math: [operate, my_custom_math.yaml]
.
If you want to introduce new constraints, decision variables, or objectives, you can do so as part of the collection of YAML files describing your model. See the custom math section for an in-depth guide to applying custom math.
The inbuilt math documentation can be explored in this section by selecting one of the options in the left-hand side table of contents.
A guide to math documentation¶
If a math component's initial conditions are met (those to the left of the curly brace), it will be applied to a model. For each objective, constraint and global expression, a number of sub-conditions then apply (those to the right of the curly brace) to decide on the specific expression to apply at a given iteration of the component dimensions.
In the expressions, terms in bold font are decision variables and terms in italic font are parameters.
A list of the decision variables is given at the end of this page.
A detailed listing of parameters along with their units and default values is given in the model definition reference sheet.
Those parameters which are defined over time (timesteps
) in the expressions can be defined by a user as a single, time invariant value, or as a timeseries that is loaded from file or dataframe.