[Challenging] Add Orgill and Hollands decomposition model to pvlib

[AdamRJensen]

This project is for you who's been wanting to contribute to the pvlib code base but haven't found the time. Yet!

You have some experience with Python, feel comfortable writing your own functions, and are able to figure out how to install git or GitHub Desktop and fork the pvlib package (the pvlib maintainers will be available to help you during the session!).

The task is to add a new decomposition model to pvlib. The existing decomposition models in pvlib can be found here. Hint: decomposition models are also sometimes called DNI estimation or diffuse fraction estimation models.

The model that you will be implementing is the Orgill & Hollands model, which is a simple piecewise function that maps the clearness index to the diffuse fraction. The function is very similar to the Erbs model, which is already implemented in pvlib (steal as much useful code as possible).

Step 1 - Look through the documentation and code of the Erbs model

Step 2 - Use the code for the Erbs model as a starting point and adapt it to match the Orgill & Hollands piecewise function

Step 3 - Fork the pvlib python package either using git or GitHub Desktop

Step 4 - Create a pull request with the new function

Step 5 - Read the pvlib contributing guidelines and make sure to follow them

Step 6 - Request a review from the pvlib maintainers on GitHub

Step 7- After an initial review, it is time to add unit tests that ensure that the function works as it should. More information on this step will follow once you succeed in opening a pull request. Now go leave your mark on pvlib!