NatLabRockies / NatLabRockies/reView
Area based weighting with Bespoke Hybrids
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 8
- Forks
- 12
- PR merge metrics
- No merged PRs in 30d
Description
Since bespoke, we are taking area weighted means instead of capacity weighted means. This will be a problem for hybrid datasets since there is no singular capacity field for the combination of wind and solar, just individual wind and solar area fields.
Figure something out in this case.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the area-weighted and capacity-weighted mean logic and the handling of bespoke hybrid datasets. Determine how combined wind and solar records should be weighted when only separate wind and solar area fields exist; done means the chosen behavior is implemented and verified for hybrid data.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100