Min/max generation for Generators#1047
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* refactor: naming convention `network` -> `n` * refactor: naming `sub_network` and `sub-network` * refactor: naming `df` -> `static` * refactor: naming `dataframe` -> `df` * refactor: naming `pnl` -> `dynamic` * ignore linopy in type checking * docs: add release notes * fix: pre-commit * make dataclasses more robust * fix: missed pnl * fix docs * add some more deprecation decorators * fix type ignore
* add 4 kA high-temperature low-sag (HTLS) line type Based on data from JAO Static Grid Model. * Updated description in the user-guide: components.rst. --------- Co-authored-by: bobbyxng <[email protected]>
lkstrp
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Some small stuff and I check for another test with snapshots
Co-authored-by: Lukas Trippe <[email protected]>
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Is it possible to include this function to links? |
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At least not planned in a similar approach. What is your use case for this? |
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I think generalizing it would be helpful. Often total transmission of individual links or total energy consumed/produced by conversion technologies such as electrolyzers need to be fixed per optimization horizon. The only question is whether the constraint should run on p0 or p1, where I would strongly lean towards p0. A side note: I don't like the current naming of the constraint as it is very unspecific. When generalizing, i would prefer something like "define_total_production_constraint" |
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@lkstrp I see that @FabianHofmann addressed the need for the generalization of this constraint. I agree with the use cases. I also agree we should set the constraint at p0. |
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e_sum_max is a fixed value, how should I make it vary with the installed capacity? |
This feature is not implemented. |
Changes proposed in this Pull Request
This PR introduces two new optional fields for generators, namely
e_sum_minande_sum_max. These fields restrict the overall amount of energy generated by the unit during a single optimization horizon within the constraintdefine_generators_constraints. Here, e_sum_min serves as the lower bound for generation, and e_sum_max as the upper bound.The extension offers the following practical advantages:
e_sum_max.In comparison to the current modeling approaches using store and link components, it requires 1. fewer components, thereby increasing the sparsity of networks (1 generator vs. 1 store + 1 link), and 2. reduces the complexity of the linear program (LP) by eliminating the need for storage-consistency constraints.
Checklist
doc.doc/release_notes.rstof the upcoming release is included.