Internal OCF application to run PVNet models and (optionally) PVNet summation models for the UK in a live environment. This involves accessing weather data stored in AWS S3 buckets, processing and loading this data using either our ocf-data-sampler or ocf_datapipes libraries, pulling pre-trained models from HuggingFace and then producing solar PV power forecasts for the UK by feeding the processed weather data into the model.
The app supports multiple model versions being deployed to live environments and these can be ran with specific configurations which are set via environment variables.
To be able to run the tests locally it is recommended to use conda & pip and follow the steps from the Install requirements section onwards in the Dockerfile or the install steps in the conda-pytest.yaml file and run tests the usual way via python -m pytest. Note if using certain macs you may need to install python >= 3.11 to get this to work.
It is possbile to run the app locally by setting the required environment variables listed at the top of the app, these should point to the relevant data sources and DBs for the environment you want to run the app in. You will need to make sure you have opened a connection to the DB, as well as authenticating against any cloud providers where data may be stored (e.g if using AWS S3 then can do this via the AWS CLI command aws configure), a simple notebook has been created as an example.
Thanks goes to these wonderful people (emoji key):
 Dubraska Solórzano 💻 |
 James Fulton 💻 |
 Megawattz 💻 |
 Peter Dudfield 💻 |
 DivyamAgg24 💻 |
This project follows the all-contributors specification. Contributions of any kind welcome!
