This Python project utilizes pvlib and a custom forecasting library to predict solar power generation based on various environmental factors at a specific location. The project aims to provide accurate solar generation forecasts to help optimize and plan solar energy usage.
- Solar Power Prediction: Estimate the amount of solar power generation based on historical and forecasted weather data.
- Custom Environmental Forecasting: Utilize a custom-built forecasting library to predict key environmental variables such as temperature, irradiance, and humidity.
- Location Specific: Tailor predictions to the specific geographic and climatic conditions of any location.
Before you begin, ensure you have met the following requirements:
- Python 3.7 or higher
Clone the repository to your local machine:
git clone https://github.com/grierdavid/pvlib-site-model.git
cd pvlib-site-mode
docker build -t site-model .
docker run -it --rm -p 8888:8888 -v $(pwd):/home/jovyan/work site-model
copy from startup: http://127.0.0.1:8888/lab?token=<session token>
into browser
navigate to work/experiments.ipynb