Modelling the impact of low carbon technology adoption on consumer energy consumption is challenging without access to smart meter data. Centre for Net Zero’s unique access to Octopus Energy’s data allows us to train a generative model conditioned on information that is vital to prepare intelligent grid systems for the future, when there will be a high penetration of low carbon technologies (LCTs) in homes.

Faraday is a model based on Conditional Variational Auto-encoder (VAE) and Gaussian Mixture Model (GMM). Using over 1.8 billion smart meter readings, from a nationally representative dataset, it generates daily load “profiles” consisting of half-hourly kWh consumption for a given set of user-specified inputs (such as days of week, months of year, LCT ownership, EPC rating, property type, and tariff type), outputting synthetic data that can be safely be shared with third parties.

Researchers, policy makers and DNOs are exploring multiple downstream applications of the tool, simulating how households consume energy and modelling specific scenarios. Users include the Department for Energy Security & Net Zero, Ofgem, ARUP and the universities of Oxford, Cambridge, Manchester, Birmingham and more. Access to the tool is free; get in touch to find out more.

Our Faraday model is the foundation for OpenSynth, an open data community that we created in partnership with the Linux Foundation. OpenSynth is democratising access to synthetic energy demand data, enabling widespread, global access to smart meter datasets. We have released a dataset that contains 10M synthetic smart meter profiles to the data repository.