Runs wind and PV forecasts for India and saves to database
The ML model is from PVnet and uses ocf_datapipes for the data processing For both Wind and Solar we use ECMWF data and predict 48 hours into the future.
The latest change is to use a patch size of 84x84, an increase from 64x64. This is to allow for more context in the image and to allow for the model to learn more about the wind patterns.
The validation error is ~ 7.15% (normalized using the maximum wind generation)
The weather variables are currently
We add some model smoothing
The validation error is ~ 2.28% (normalized using the maximum solar generation)
The weather variables are
poetry install
Lint with:
make lint
Format code with:
make format
make test
Replace {DB_URL}
with a postgres DB connection string (see below for setting up a ephemeral local DB)
If testing on a local DB, you may use the following script to seed the the DB with a dummy user, site and site_group.
DB_URL={DB_URL} poetry run seeder
⚠️ Note this is a destructive script and will drop all tables before recreating them to ensure a clean slate. DO NOT RUN IN PRODUCTION ENVIRONMENTS
This example runs the application and writes the results to stdout
DB_URL={DB_URL} NWP_ZARR_PATH={NWP_ZARR_PATH} poetry run app
docker run \
-it --rm \
-e POSTGRES_USER=postgres \
-e POSTGRES_PASSWORD=postgres \
-p 54545:5432 postgres:14-alpine \
postgres
The corresponding DB_URL
will be
postgresql://postgres:postgres@localhost:54545/postgres
Build the Docker image
make docker.build
Create a container from the image. This example runs the application and writes the results to stdout.\
Replace {DB_URL}
with a postgres DB connection string.\
N.B if the database host is localhost
on the host machine, replace localhost
with host.docker.internal
so that docker can access the database from within the container
docker run -it --rm -e DB_URL={DB_URL} -e NWP_ZARR_PATH={NWP_ZARR_PATH} ocf/india-forecast-app
This repo makes use of PyTorch (torch
and torchvision
packages) CPU-only version. In order to support installing PyTorch via poetry for various environments, we specify the exact wheels for each environment in the pyproject.toml file. Some background reading on why this is required can be found here: https://santiagovelez.substack.com/p/how-to-install-torch-cpu-in-poetry?utm_campaign=post&utm_medium=web&triedRedirect=true