Summary

As energy systems electrify and rely on weather-dependent generation from more varied sources, it is increasingly important to accurately profile, predict and actively manage demand. However, broad access to granular smart meter data is prevented by the need to protect consumer privacy and maintain cybersecurity, slowing down the transition to a smarter, more flexible energy system.

Synthetic smart meter data offers a breakthrough solution, drawing on pioneering approaches in healthcare, finance and technology sectors. By using open source, generative AI techniques whose outputs accurately mirror real-world energy consumption patterns, synthetic data allows users to forecast energy demand, optimise planning, and develop smarter energy policies - ultimately benefitting consumers without compromising on privacy.

This policy paper covers five key applications of open source, synthetic smart meter data in supporting smart energy systems in the UK, US & Europe: integration in consumer facing products; policy and regulatory design; electricity system and network modelling; development of financial products and services; and housing development planning.

Key Recommendations

To unlock the full potential of synthetic smart meter data, there are five principal actions that must be taken across the ecosystem:

① Integrate synthetic data in data accessibility strategies. Governments should take a proactive and strategic role in promoting synthetic data alongside improving access to real customer smart meter data through consumer consent mechanisms.

② Develop commonly agreed standards for synthetic data quality. Researchers, industry and regulators should collaborate to develop common frameworks for objectively evaluating and quality assuring synthetic data.

③ Remove ambiguity through explicit mention of synthetic data in legal frameworks and voluntary codes of conduct. Regulators should be explicit that ‘synthetic data’ is ‘deidentified data’ and therefore suitable for data-sharing purposes.

④ Fund innovation projects and support regulatory sandboxes to allow regulated industries to test and trial with new, synthetic data sources. Research councils, regulators and governments should prioritise funding for collaborative innovation projects, or establish regulatory sandboxes, to test and trial synthetic data in business operations.

⑤ Collaborate internationally, taking an open source approach, to improve access to data, resources, and skills. Through international, open source initiatives such as OpenSynth, researchers, industry stakeholders, and government bodies should share data, algorithms, and evaluation techniques for synthetic data.