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New default solar position algorithm

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評估

難度
5/5
預估耗時
一週以上
新手友好度
12/100
Issue 類型
功能
描述清晰度
基本清楚
活躍度
冷清
技術堆疊
python
領域
data

研究方向

The entry point is the get_solarposition wrapper, whose default algorithm is nrel_numpy; the issue asks whether a faster model (SG2, USNO or NOAA) should replace it. This is a design decision for maintainers, not a code change, and the thread has no decision after 12 comments. Before any code, a contributor would need to agree the default with maintainers and benchmark the candidates against accuracy, not only run-time.

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描述

Is your feature request related to a problem? Please describe.

[Solar Position Documentation](https://pvlib-python.readthedocs.io/en/stable/reference/solarposition.html
https://pvlib-python.readthedocs.io/en/stable/reference/generated/) recommends using the default solar position algorithm. Should we update to a faster algorithm given @AdamRJensen's poster at this year's PVPMC which shows that most algorithms have minimal impact on energy regardless of run-time?

With permission I can edit this comment and add a photo of the poster.

Describe the solution you'd like
A fast implementation of the SG2, USNO or NOAA solar position algorithms set as the default model for the get_solarposition wrapper.

Describe alternatives you've considered
We could leave the default as nrel_numpy

Additional context

  • Increased run-time speed of pvlib reduces carbon output of running models (no matter how small or large that might be)
  • I am happy to re-implement one of the above models in Rust with python bindings and open source the rust backend. I know that this comment will open up a can of worms. I think one way to go about this is to implement the model twice, once in python as a reference for the community and once in rust/julia/c++ etc. for use in practice. Users would be able to select which model to use at their prerogative.
主要語言
Python
星號
1.7k
分支
1.2k
平均合併
3 天 18 小時
30 天內合併 PR
13

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