Adding the Loss Factors Model and Mechanistic Performance Models to PVLIB

[steve-ransome]

I'll be adding the Loss Factors Models and Mechanistic Performance Models to PVLIB, .

See http://www.steveransome.com/PUBS/1906_PVSC46_Chicago_Ransome.pdf for more details on what they do

I hope it should be ready by the conference in Salt Lake in May

I've uploaded a couple of graphs and some sample code and Initially I'm looking for feedback and comments as I will need to enhance the present naming convention

With the LFM I have been using prefix and suffix letters to describe the type of measurement and any corrections. For example this Python 3 code shows the naming I have been using and does normalised LFM and temperature correction.
I have just shown nIsc and nVoc for clarity but will upload code for all variables soon plus graphs and MPM fits.

Once I have this in a correct form I can add more of features

MLFM_SRCL_200302.py.txt

Any feedback is welcome
Steve

[cwhanse]

@steve-ransome looking forward to hosting this function. Have you thought about the function's signature? What are the inputs, what is output?

I should look at your PVSC paper again, refresh my memory, but Sandia is blocking your website. Would you mind sending it to me directly?

[steve-ransome]

Thanks Cliff.

I've been writing Python code for myself and clients for a few years. I am not yet familiar with these collaborative efforts although I am learning. The python I added is just simple, sample code,to calculate some of the LFM coefficients and show my naming convention which allows variables to be identified as "reference, measured or normalised" and also "uncorrected or temperature corrected" (e.g. "nIsc_T") so need an idea if this is OK to use as the naming convention document just allows names like i_sc and v_oc.

Basically the LFM function will transform measured values from an IV curve to normalised values

Inputs
IV curve : (mIsc, mRsc, mmp, mVmp, mRoc, mVoc ...)
Reference module STC values : (rIsc, rImp, rVmp, rVoc , rIsc_Alpha etc. ...)
Weather data : (Irradiance Gi, module temperature Tm, Windspeed WS ...)

Normalised Outputs
LFM values : (nIsc_U, nRsc, nImp, nVmp, nRoc, nVoc_U and temperature corrected _T) if desired

The MPM function fits up to n=6 normalised coefficients to predict a normalised LFM output such as nIdc or nVoc

nLFM = fn ( Gi, Tmod, WS, C1 .. Cn)

I've been reading up on some of the coding examples such as the 1-diode model to get an idea of the sort of style used for comments, layout etc. and hope to follow that. Maybe if I follow https://www.python.org/dev/peps/pep-0362/ I can get you code that will be closer to what's needed,

Here are my Chicago files uploaded - please tell me if you can get them

1906_PVSC46_Chicago_Ransome_ppt_Presented.pdf

1906_PVSC46_Chicago_Ransome.pdf

Is anyone else blocked from www.steveransome,com ?

Does Sandia give a reason why my website is blocked? Perhaps you could ask them to unblock it, or give me a reason why not

I appreciate the amount of work you guys have done already over the years and will try to contribute as best as I can - even though I don't understand all the stuff mentioned in github.

[cwhanse]

allows variables to be identified as "reference, measured or normalised" and also "uncorrected
or temperature corrected" (e.g. "nIsc_T") so need an idea if this is OK to use as the naming
convention document just allows names like i_sc and v_oc.

We can work through naming conventions for these new quantities with the pull request. It really helps to see the variables in context.

I've been reading up on some of the coding examples such as the 1-diode model to get an idea of the sort of style used for comments, layout etc. and hope to follow that. Maybe if I follow https://www.python.org/dev/peps/pep-0362/ I can get you code that will be closer to what's needed,

I don't think we are using PEP-362. By "signature" I only meant a list of inputs and outputs.

I can get the files from here, thank you. www.steveransome.com is not blocked, but the links to the hosted files are blocked here. Hard to say why without a dozen phone calls.

[steve-ransome]

Thanks. Maybe I can send some code over in a few days where I've tried to follow everything and made clear when I can't achieve something (like naming) as it is.

As it's Python it should be clear what it is I am trying to do but I do add comments too. You can see the basics from the first py file I sent

[steve-ransome]

I presented a virtual talk at "August 5, 2020 PVPMC Webinar on PV Performance Modeling Methods"
https://pvpmc.sandia.gov/resources-and-events/events/2020-pvpmc-webinars/

"How to use the Loss Factors and Mechanistic Performance Models effectively with PVPMC/PVLIB"
https://pvpmc.sandia.gov/download/7879/

After receiving some positive feedback I'll soon be to be able to upload code as described in slides 15 and 16.

What's the best way to go about this? I've followed as many of the hints and tips as I can find for coding, documentation and naming but I'm sure there will be changes needed
.
There'll be an ipynb file, a py lib file, some default measurement data, reference measurements and it will generate the 5 graphs in slide 16. Instructions are provided for you to use your own measurement data.

I am not familiar with the procedures you've already been using and welcome suggestions and links.

[mikofski]

Hi Steve,

This is very exciting and welcome news! Thank you for offering your contributions to pvlib!

The best source of info would be the contributing section of the pvlib documentation. Here are the salient points:

1. pvlib python uses Git & GitHub to manage contributions. There are other methods but this will give you the most control to ease integration of your code. Therefore you will need to have:

   • Registered for a GitHub account
   • Forked the pvlib python repo to your personal GitHub account. Click the fork button on the pvlib python GitHub page
   • Installed Git on your computer. If you prefer a graphic user interface (*), after installing Git, get tortoiseGit which adds icon overlays and subcontext menus to Windows explorer

2. The easiest way to integrate your code into pvlib python is on your machine first! This is done by "cloning" the pvlib Git repository to your computer. If you installed tortoise then browse to the location where you want to work on your development version of pvlib, right click the folder and select "clone" then enter the URL to your fork of the GitHub pvlib python repo, eg: https://github.com/steve-ransome/pvlib-python, then enter your GitHub credentials when prompted (**)

3. pvlib python uses a strategy called feature branching to integrate enhancements like the loss factor model. If using tortoise, navigate to the Git repo you just cloned, right click anywhere and select "checkout new branch". Then enter a descriptive branch name like "loss-factor-model"

4. Now integrate your code into the branch in your computer. After you've made the changes, you need to "commit" them to the repository. Right click again and select "commit". You should see that there are "untracked" changes. Click the files you want to add, add a descriptive comment and click "commit".

5. Next you need to make your changes known to GitHub by pushing them to your fork. Using tortoise, right click and select "push". In the field select "origin" and the name of your branch: "loss-factor-model", then click okay. Enter your GitHub credentials again if prompted.

6. The last step is to let the maintainers know you want to integrate your changes on GitHub by creating a "pull request"online. Go to your online fork of pvlib python and you should see a message noting that GitHub observed your changes and offering to open a pull request from you to the main pvlib python repo. Do it.

Here are some more references to help you get started:

• https://bids.github.io/dats/posts/2018-09-10-github-oss.html
• https://bids.github.io/dats/posts/2017-10-04-github-oss-f17.html#using-github-for-open-source-projects
• http://poquitopicante.blogspot.com/2016/10/winning-workflow.html
• https://mikofski.github.io/BasicGitWorkFlow/

[mikofski]

Here are the additional notes where I left asterisks

• (*) There are other graphic user interface for Git, notably GitHub desktop & Atlassian sourcetree, but I personal recommend just using the command line. The Pro Git book is IMHO very good. GitHub & Bitbucket help can also be useful.
• (**) Another scheme for cloning your repo uses SSH keys instead of HTTPS. This requires you to create SSH private & public keys on your computer first, and then copying the public key online in your personal GitHub account settings

[steve-ransome]

Thanks @mikofski , I'll try that over the weekend, there's a lot to take in!

[steve-ransome]

Thanks @mikofski , I've been through all of your documentation but am still struggling to get this set up properly. I've used tortoisegit

I've tried to add my mlfm files in a directory pvlib_python\pvlib\mlfm. There are a notebook (mlfm_pvpmc1.ipynb), library (mlfm_lib_1.py) then reference (ref, test and matrix.csv) and measurement files (*.csv) and a graphs directory where it automatically saves generated .png files. The ipynb and .py files have a lot of documentation. I've just put in the first couple of graphs and once it's working can update and add more.

Please can anyone help let me know if this is OK or what else I should do.