Last month, our COO Gareth Jones and Data Lead Gus Chadney were invited to join EPRI's Artificial Intelligence & Digital Transformation in Electric Power Summit in California, to examine one of the key barriers and enablers that shape AI development in the energy sector: access to data.

We presented our work to develop and openly share synthetic smart meter data, speaking alongside François Mirallès (Hydro Québec), Abder Elandaloussi (Southern California Edison) and Alexandre Parisot (LF Energy).

There are material barriers to accessing energy demand data. While adoption of smart meters increases, privacy issues limit access to half-hourly consumption data. At Centre for Net Zero, we’ve trained our model, Faraday, on 1.8 billion smart meter readings to generate household-level synthetic load profiles — modifiable by time, property type, LCT ownership, EPC rating, and more.

We’re open sourcing our synthetic data, and are working with LF Energy to grow OpenSynth, an open-data community designed to democratise access to synthetic smart meter data and accelerate energy modelling innovations.

If you would like access to our Faraday model, or want to get involved with OpenSynth, please get in touch.