A couple of scripts which have gradually developed over the time I have been on Octopus Energy's Agile Octopus electricity tariff.
config.py should be populated before using either of them.
This script is intended to be run daily (when each batch of prices is published). It sends an email containing tomorrow's prices, a few quantities derived therefrom, and a summary of the cost of recent usage.
It also includes a rough TensorFlow-based forecast of the prices for the
following seven days, based on the National Grid's demand and wind generation
forecasts. This must first be trained with the train_price_forecast script.
This script implements a simple simulation of the heating and cooling of a building (as defined in the config), and uses it to determine the cheapest combination of heating for the next few days. This is non-trivial, as it often works out cheaper to heat the property to a higher temperature on a day with low prices so no heating is needed on more expensive subsequent days.