Closed trevorb1 closed 6 months ago
This is just an issue with how the Breakthrough/TAMU Transmission network is created. It's a synthetic network and they created it so that the capacities and dispatch loosely matches historical data. There was a project at BE to load the HIFLD dataset you posted into the model, but they didn't get that far since there are issues with ensuring network connectivity with that dataset.
this is a project I might be taking on in the next year... can share more when we chat.
Closing- as discussed this is part of the issue with synthetic networks. At some point in the future we will explore converting HIFLD or using OSM / Earth Data
Checklist
master
branchpypsa-usa
environment. Update viaconda env update -f envs/environment.yaml
The Issue
There seems to be an inconsistency of the Breakthrough Energy's transmission line voltages. Specifically, I think the data processing of BE into PyPSA is correct, but the interpretation of the data may be off.
I have included a notebook of this issue, and will describe the issue using
765kV
lines as an example.PyPSA-USA network If I run the workflow, and import the network before any simplification/clustering, this is the result. The bold red lines are
765kV
.Breakthrough Energy If I do the mapping of buses/subs to highlight the
765kV
buses, these are the locations. This match up with the PyPSA-USA representation -- this is why I think the data processing is correctGeospatial Management Office If I take the geospatial management offices gis data on USA transmission lines and plot it, this is the result for
765kV
lines. Notably, there are none in the western interconnect. Moreover, the existing765kV
lines in the north east do not appear on the breakthrough energy dataset. I have confirmed that the765kV
lines in this dataset are correct.Steps To Reproduce
Expected Behavior
I would expect the two separate datasets to at least be similar. The geospatial management offices
765kV
lines should be present in the BE dataset?Error Message
No response
Anything else?
@ktehranchi do you have any immediate thoughts on this issue? If not, maybe we can meet up to discuss the differences between the datasets to try and figure out where the differences are coming from?