Photovoltaic-Model: calculates the current-voltage characteristic of a solar cell using the two-diode model, with a possibility to fit an experimental characteristic
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PhotovoltaicModel.py
PhotovoltaicModelCore.py
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# Photovoltaic Solar Cell Two-Diode Model

Code written by:
Dr. habil. Eng., Associate professor
Université de Lorraine, France

## Presentation and Requirements

Photovoltaic-Model calculates the current-voltage characteristic of a solar cell using the two-diode model, with a possibility to fit an experimental characteristic to get short-circuit current, diodes parameters (reverse saturation current and ideality factor), series and parallel resistances.

To install Photovoltaic-Model:
unzip and use.

The distribution mainly includes:

Two main Python files:

It is not necessary to know the Python language to use the program.

The basic requirements are found in any Linux distribution (and easily installed for Windows):

• Python version 2.7.x or later
• numpy version 1.5 or later
• scipy version 0.13.1 or later
• matplotlib version 1.3.x or later
• tkinter 8.5 or later

PS: for Windows, you can download a complete Python distribution from https://www.anaconda.com/distribution/

## HowTo

Start PhotovoltaicModel.py interface:

from the command line prompt:
under Linux:

cd /path/to/PhotovoltaicModel/
python -u PhotovoltaicModel.py


under Windows (in the command prompt):

cd C:\path\to\PhotovoltaicModel\
python.exe -u PhotovoltaicModel.py


You can also execute PhotovoltaicModel.py by double clicking on it (depending on the operating system settings), or from within your editor, if possible.

In the graphical interface, change the parameters you want and press 'Calculate'.

To fit experimental current-voltage characteristic, load the file and press 'Fit'.
The file format consists of two columns (voltage in V and current in A) separated by tabulation:
0.00 -20.035e-3
0.05 -20.035e-3
...
0.55 -1.5e-8
The first two lines and lines beginning with a hash are ignored.
Of course, the fitting algorithm converges faster if provided with good initial guess for the parameters.
You can restart fitting as many times as necessary to reach the desired accuracy.

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