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Add selection for DCOPF, network flow, or copper plate transmission model #60
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For a network/transport model, we would still have power flow on each line, it just wouldn't be constrained by KVL. But with a copper-plate model, we no longer have meaningful values for |
Another transmission model we may be interested in: copper-plate, within interconnections only. I think we could enable this by removing all flow limits on AC lines, but not DC lines. This could let us investigate e.g. the difference between the best-case transmission upgrades within interconnections vs. the best case transmission upgrades including bridging the interconnections. |
This can be achieved by scaling the capacities of all AC branches to 0 via change table right, although, it is ugly in some sense. |
@BainanXia scaling the capacities of the AC branches down to zero will remove the min & max constraints on the AC lines, but REISE.jl will still add variables for the flow on each branch, enforce branch-angle constraints on their flows, and create power-balance constraints for each bus. It would work, but still creates a model with unnecessary complexity (although maybe Gurobi would realize this and presolve some/all of the unnecessary complexity away). I think what we want is:
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@danielolsen Agree. A true copper-plate mode should ignore the topology completely as long as the graph is a connected component. |
@rouille I would like to get your opinion on how to design for this. |
If a the PF file is not in data/output on the server the I think the necessary refactoring will happen in the |
extract_data.py will definitely need refactoring. Do you think the transmission model would be something we want to record in the ScenarioList as part of the create state (defaulting to |
Eventually we may even want to have ACOPF or security constrained OPF |
Plus unit commitment, SCUC. |
We may also want to add different formulations of DCOPF. This paper seems to show a pretty significant speed-up in computation time for the 'Kirchoff' formulation, around 2x-4x for large problems. The original formulation seems to come form https://ieeexplore.ieee.org/document/192975. This should be easy to swap in now that #117 is done. |
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