About Battery Badger
Battery Badger is an AI-powered energy trading platform that optimises home battery charge and discharge schedules on dynamic electricity tariffs.
The project was founded by Damian Moore, a software, data and devops engineer with 15+ years of experience building production backend and ML systems. It began as a personal effort to maximise returns from a DIY home solar and battery system on Octopus Agile, and was developed further as part of an application to Bethnal Green Ventures’ “Tech for Good” accelerator in 2024.
We believe AI-driven battery optimisation is a critical lever for both household economics and grid decarbonisation. People use more power in the evenings when renewables are at their lowest, forcing gas peaker plants online. By shifting consumption to times when renewable energy is abundant and cheap, home batteries can reduce bills and carbon simultaneously.
What we build
- Rate forecasting models — machine learning models that predict half-hourly Octopus Agile rates up to 7 days ahead, using historical rates, weather forecasts, and grid demand data
- Battery trading engine — a reinforcement learning optimiser trained on hundreds of thousands of simulated days to decide optimal charge/discharge schedules
- APIs — we are building open APIs for rate forecasts, dispatch signals, and consumption modelling
Who we work with
We work with battery manufacturers who want to add intelligent tariff optimisation to their cloud platform, developers who want to build energy apps on our forecasting data, and homeowners who want to understand what a battery could save them.
Get in touch
For partnership enquiries, integration questions, or general feedback: