This model forecasts Octopus Agile electricity prices up to 14 days in advance using a Machine Learning model trained on data from the Balancing Mechanism Reporting System (BRMS), National Grid Electricity Supply Operator (NG ESO) and weather data from open-meteo.com.

This project is made using Python and Django. Here is some instructions to get you started if you want to develop for the project.

As with all python projects, it is recommended to create a virtual environment. For example, in this project, create a virtual environment using python's built in virtual environment tool venv to create an virtual environment in a folder .venv:

cd agile_predict
python3 -m venv .venv

Then, each time you are developing, activate the virtual environment according to the OS you are using.

Windows:

./.venv/Scripts/activate

Requirements are listed in requirements.txt. You may install these however you like. The usual way is via python pip:

pip install -r requirements.txt

Run the project via the Django manage.py script. It's as simple as:

python manage.py runserver

Have fun!