PyPSA / pypsa-usa

PyPSA-USA: An Open-Source Energy System Optimization Model for the United States
https://pypsa-usa.readthedocs.io
MIT License
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Add cutouts for 2018 #284

Open trevorb1 opened 2 months ago

trevorb1 commented 2 months ago

Feature Request

For residential and commercial demand profiles, they are based on a 2018 weather year.

Suggested Solution

We should add cutouts to the zenodo deposit for 2018 weather year.

Additional Info

No response

trevorb1 commented 2 months ago

Data for this is based on Amy2018, note ERA5

trevorb1 commented 2 months ago

Once this is done, dont forget to remove this code block from build_demand.py

##################################################################
## REMOVE THIS ONCE 2018 CUTOUTS ARE CREATED
##################################################################
df = df.reset_index()
df["snapshot"] = df.snapshot.map(lambda x: x.replace(year=2019))
df = df.set_index(["snapshot", "sector", "subsector", "fuel"])
##################################################################
## REMOVE THIS ONCE 2018 CUTOUTS ARE CREATED
##################################################################