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Description
Introduction
This issue summarises the ongoing and completed work for the GSoC 2024 programme with pvlib.
The project I am undertaking relates to an issue raised earlier this year. The official abstract for the project can be found here. This project is being carried out under the supervision of @AdamRJensen and @kandersolar
In summary, the aim of the project is to implement new spectral correction models in pvlib, as well as examples of their application and use. In addition to updating this issue as the project progresses, detailed updates on the project will also be shared in blog posts. Major milestone updates will be shared on my LinkedIn page as well.
Plan
The current overall project plan is described below.
- Three new models are planned for development and implementation:
- Pelland 2020 PVSPEC model
- Huld 2009 JRC model
- Daxini 2023 APE/e model (stretch goal, if time permits)
- A combined example to demonstrate the use of the new models and application in the overall modelling pipeline will be developed.
As the project develops I will link these tasks to individual issues and pull requests.
Issues
Open:
Closed:
#2065 (this one)
#2135 (create average photon energy function)
#2125 (suggestion to split mismatch.py
)
#1950 (general issue, add new spectral factor models)
#2087 (add JRC spectral factor model)
#2115 (update SAPM spectral factor docs)
#2107 (add spectral factor example),
#2086 (update spectral_factor_firstsolar
)
PRs
- (merged) Split
test_spectrum.py
Split test_spectrum.py #2151 - (merged) Function to calculate APE Create function to calculate average photon energy #2140
- (merged) Restructure
pvlib/spectrum
restructure pvlib/spectrum #2136 - (merged) Update First Solar model update spectral_factor_firstsolar #2100
- (merged) Spectral mismatch factor example Add spectral factor gallery example #2114
- (merged) Update SAPM docs Update spectral_factor_sapm docs #2116
- (merged) JRC model (air mass and clearsky index) Add JRC spectral factor correction #2088
- (merged) PVSPEC model (air mass and clearsky index): Add PVSPEC spectral correction factor model #2072
- (closed) Add ape_e spectral factor model Add ape_e spectral factor model #2126
Any feedback on the project is certainly more than welcome. Using github and contributing to open-source software is completely new to me so I am looking forward to learning about this so that I can contribute to pvlib not only through this project but also in future.
Dax
Activity
markcampanelli commentedon May 27, 2024
As part of the documentation of a growing number of methods, it might be helpful if a “overview” table of spectral-correction method vs. required+optional inputs were added. This way consumers would be able to get a quicker idea of what information/data is needed to apply each correction. The timescale over which the correction is applied could also be a factor (although maybe they are all the same at this point).
RDaxini commentedon May 27, 2024
@markcampanelli I think that is a good suggestion. I tried to achieve something similar with Table 10 in this study; is that the sort of thing you had in mind? Timescale is a good point too. I have had a paper examining this issue under review for a while so maybe/hopefully something will come out of that soon that I can implement into this work.
adriesse commentedon May 31, 2024
@didierthevenard
markcampanelli commentedon May 31, 2024
@RDaxini Yes. Depending on your time, you could at a bare minimum reference your paper with table 10. If time permits, then you could perhaps provide a “translation” of that table into something more specific to pvlib’s variable names and functions.
BTW: Your timescale-focused paper also sounds like an interesting read 🙂. Good luck working it through the process!
kandersolar commentedon Jun 20, 2024
@RDaxini #2088 got automatically linked to this issue based on its description, so merging that PR automatically closed this issue. Check out https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword
Try "see also #XXX" or some other phrasing to prevent the automatic linkage next time :)
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