Quantum AI chip boosts Australian energy grid forecasts

Silicon Quantum Computing and Schneider Electric secure AU$3.6m to roll out a hybrid AI chip that delivers a 20% jump in energy forecasting accuracy

Australian quantum computing company Silicon Quantum Computing (SQC) and Schneider Electric have partnered to advance energy forecasting with hybrid quantum-classical models.

The initiative, which is being undertaken under the government’s Critical Technologies Challenge Program, has now moved into Stage 2 with the award of AU$3.6 million (US$2.5 million/€2.2 million) in funding for the work to continue in partnership with UNSW Sydney University.

During Stage 1, the joint team explored whether SQC’s atomically engineered, quantum-enhanced AI chip, Watermelon, could improve the accuracy of Schneider Electric’s forecasting models.

Watermelon is designed to generate quantum features that, when used alongside classical features, deliver richer models with greater predictive abilities.

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“We have always believed that quantum processors would work alongside CPUs and GPUs to deliver real-world performance gains,” commented Michelle Simmons, founder and CEO of SQC.

“The results we have achieved with Schneider Electric demonstrate how quantum-enhanced AI can address practical challenges across the energy sector and time-series datasets more broadly. We’re grateful to the Australian government for continuing to back this important work.”

The grids are under increasing pressure and urgent solutions are required for grid resilience. As rooftop solar, batteries and electric vehicles become widespread, household energy systems have become more dynamic and difficult to predict.

Schneider Electric uses advanced forecasting and optimisation technologies to help balance distributed energy resources, including forecasting when to switch back and forth to solar energy deployment.

Clearly, more accurate forecasting can be beneficial in this context, including increasing renewable energy utilisation and contributing to lower energy costs for consumers.

Building on the Stage 1 results, the Stage 2 funding is intended to expand modelling to hundreds of homes across Australia, with direct integration into Schneider Electric’s AI workflows.

The work is also considered to provide a clear pathway for today’s quantum computing systems to be used in production environments.

Colette Munro, Pacific Zone president at Schneider Electric, said the energy system is becoming more dynamic with new levels of complexity.

“Together with SQC, we've demonstrated how advanced energy technology has the potential to better manage this complexity, lowering costs for consumers and using energy more efficiently across the system.”

Launched in 2025, Watermelon is a quantum feature generator for machine learning combining classical and quantum processors – AKA quantum enhanced AI – that is intended in particular for time series data and sparse data sets.

Available via both cloud and hardware networks, Watermelon has been deployed by customers across the telecommunications, banking and high-frequency trading sectors.

Critical technologies challenge

The Australian government’s critical technologies challenge is focused on addressing issues of national significance using quantum technologies.

In addition to the SQC-Schneider Electric initiative, others focussed on optimising the performance and security of the energy networks being led by the Flinders and La Trobe universities.

The Flinders-led project is investigating the potential of quantum computing supplemented with a digital twin model in managing remote-community energy systems, for example to improve the reliability of renewable supply.

The La Trobe-led project is addressing the potential of quantum-enhanced optimisation to improve the energy efficiency of data centres, with initial findings showing that as the size of the centre increases, the quantum approach scales more favourably than classical methods.

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