This project is now incorporated into FoxESS-Cloud. To use this code in Jupyter Lab, you should load the module as follows:
!pip install foxesscloud --root-user-action=ignore --quiet
import foxesscloud.foxesscloud as f
print(f"foxesscloud version = {f.version}")
f.solcast_api_key = "<your api key>"
f.solcast_rids = ["<your rid 1>", "<your rid 2>"]
fcast = f.Solcast()
print(fcast)
fcast.plot_daily()
This project loads, aggregates and displays solar yield estimates and forcasts from http://solcast.com.au over a number of days (6 days past, 7 days ahead).
It uses Python for loading and analysis and Jupyter Lab for display. Jupyter Lab provides a flexible way for users to build simple scripts to analyse data that is specific to them.
The core code is contained in solcast.py and an example Jupyter notebook is provided in forecast.ipynb. Clicking forecast.ipynb will display the last uploaded notebook so you can see what this looks like.
To forecast your solar yield, you will need to:
- Register a hobbyist account at https://solcast.com.au
- Create an API access key for your account and make a note of this
- Create and configure a solar array for each string (by default, the hobbyist account is limited to 2 arrays)
- Make a note of the resource id (rid) for each array