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PVSC48 computing tutorial with focus on PV computing packages, Python, data wrangling with Pandas, and data viz

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PVSC48-Python-Tutorial

PVSC48 computing tutorial with focus on PV computing packages, Python, data wrangling with Pandas, and data viz

Tutorial Summary:

  • Tutorial 0: Introduction to the tutorial, the lesson plan, and resources
  • Tutorial 1: Access TMY weather data and visualize monthly irradiance data
  • Tutorial 2: Calculate solar position, plane-of-array irradiance, and visualize average daily insolation
  • Tutorial 3: Estimate module temperature from ambient
  • Tutorial 4: Use POA irradiance and module temperature to model output power from a single module
  • Tutorial 5: Combine modules to form strings, calculate inverter efficiency and total array output

Tutorial Setup

These tutorials are designed to run on Jupyter, a browser based interactive notebook that allows you to run the tutorial in the cloud without any additional setup. During the conference, June 20-25, you will be provided with a link and credentials to join the tutorial. After the conference the tutorials will remain available here on GitHub, and you can run the tutorial anytime in Binder by clicking the following link:

Binder

You can also run the tutorial locally with miniconda by following thes steps:

  1. Install miniconda.

  2. Clone the repository:

    git clone https://github.com/mikofski/PVSC48-Python-Tutorial.git
    
  3. Create the environment and install the requirements. The repository includes a requirements.txt file that contains a list the packages needed to run this tutorial. To install them using conda run:

    conda create -n pvsc jupyter -c pvlib --file requirements.txt
    conda activate pvsc
    
  4. Start a Jupyter session:

    jupyter lab
    
  5. Use the file explorer in Jupyter lab to browse to PVSC48-Python-Tutorial and start the first Tutorial.

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PVSC48 computing tutorial with focus on PV computing packages, Python, data wrangling with Pandas, and data viz

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