A simple and intuitive Flask application for forecasting photovoltaic production from 1 to 14 days ahead. It uses the pvlib library to model the photovoltaic system with few parameters and open-meteo API to obtain the forecasts.
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Clone the project from the repository:
git clone https://github.com/Giudice7/pv_forecast
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Open the terminal and move to the project folder.
cd pv_forecast -
Check the python version installed:
python --version
In this project, Python 3.11 was used, so it is recommended to use the same version to avoid compilation problems. If you have a different version, download the 3.11 from the following link.
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Create a virtual environment (venv) in the project folder:
python -m venv venv
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Activate the virtual environment:
venv/Scripts/activate
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Install dependencies:
pip install -r requirements.txt
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Run the application:
python app.py
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Open the browser and go to the following address:
http://127.0.0.1:5000
- Open the file
config.jsonand change the parameters of the photovoltaic system to match your system. The parameters are:latitude: Latitude of the location in decimal degrees.longitude: Longitude of the location in decimal degrees.forecasting_days: Number of days to forecast.pdc0_inverter: Nominal power of the inverter in W.array_list: The list of arrays that compose the whole PV system.
Each array has the following parameters:
surface_tilt: The tilt angle of the panels.surface_azimuth: The azimuth angle of the panels.module_type: The module materials sandwich: can be one of polymer_glass or glass_glass.pdc0_module: The nominal power of each module.gamma_pdc_module: The loss coefficient due to temperature increase of the module (from - 0.002 to -0.005 typically)module_per_string: The number of module per each string.strings: The number of strings in the array.
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Build the image:
docker build -t pv_forecast . -
Run the container:
docker run -p 5000:5000 pv_forecast
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Open the browser and go to the following address:
http://localhost:5000