In this PR I have added a dissagregation strategy for industrial loads. It is based on the United States County-Level Industrial Energy Use dataset. All industrial load is treated equally here (ie. heat and electrical industry demand follow the same dissagregation logic). So for only state level dissagregation is supported (ie. EFS data works).
Note: I think something is still off with the actual dissagreagtion. If I plot county level energy use, counties just north of LA have the highest energy use. However, if I plot clustered industrial load (based on EFS), it shows the SF area as being the highest energy use.
Im gonna move on to implementing the reading of the Industrial load dataset to see if I can find the issue while working through that.
County level demand
Clustered region demand
Checklist
[x] I tested my contribution locally and it seems to work fine.
[x] Code and workflow changes are sufficiently documented.
[x] Changed dependencies are added to envs/environment.yaml.
[x] Changes in configuration options are added in all of config.default.yaml.
[x] Changes in configuration options are also documented in doc/configtables/*.csv.
Closes #296
Changes proposed in this Pull Request
In this PR I have added a dissagregation strategy for industrial loads. It is based on the United States County-Level Industrial Energy Use dataset. All industrial load is treated equally here (ie. heat and electrical industry demand follow the same dissagregation logic). So for only state level dissagregation is supported (ie. EFS data works).
Note: I think something is still off with the actual dissagreagtion. If I plot county level energy use, counties just north of LA have the highest energy use. However, if I plot clustered industrial load (based on EFS), it shows the SF area as being the highest energy use.
Im gonna move on to implementing the reading of the Industrial load dataset to see if I can find the issue while working through that.
County level demand![image](https://github.com/PyPSA/pypsa-usa/assets/67297083/15408fd3-5932-4025-8308-4591756dfef2)
Clustered region demand![image](https://github.com/PyPSA/pypsa-usa/assets/67297083/879f8200-223d-4f73-84dd-425ab5d7de05)
Checklist
envs/environment.yaml
.config.default.yaml
.doc/configtables/*.csv
.