Quantum tech boosts Schneider Electric energy forecasts

Silicon Quantum Computing and Schneider Electric have advanced to Stage 2 of Australia's Critical Technologies Challenge Program, with the project receiving AUD $3.6 million in government funding.

The companies are working with UNSW Sydney on energy forecasting for distributed household energy systems, using SQC's Watermelon system within Schneider Electric's modelling workflows.

Stage 2 follows an initial phase in which the partners tested whether quantum-generated features could improve electricity consumption forecasts. The work focused on next-day forecasting using data collected over 12 months.

Stage 1 results showed an average 20% improvement in forecasting accuracy over a classical benchmark, with gains reaching 41% in some cases.

The project targets a growing operational challenge for power networks as rooftop solar, home batteries, and electric vehicles add variability to household energy demand and supply. This makes forecasting harder for grid operators and energy technology providers trying to balance distributed energy resources.

Stage 2 scope

In Stage 2, the modelling will expand to hundreds of homes across Australia and be integrated directly into Schneider Electric's artificial intelligence workflows.

SQC's Watermelon system generates quantum features from classical data, which are then used alongside conventional features in forecasting models. The approach is intended to help models identify relationships in sparse and time-series datasets.

The work is part of a broader effort to find practical uses for quantum computing in existing commercial systems, rather than waiting for large-scale fault-tolerant machines. Here, the focus is a routine operational problem in the energy sector: predicting demand and optimising the use of distributed resources.

Pressure on electricity systems is rising as demand grows from data centres, electric vehicles, home heating and cooling, and industrial activity. These trends underscore the need for better forecasting tools.

Michelle Simmons, Founder and Chief Executive Officer, Silicon Quantum Computing, said: "We have always believed that quantum processors would work alongside CPUs and GPUs to deliver real-world performance gains. 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."

Even modest gains in forecast accuracy can affect how energy resources are scheduled and switched, including the use of solar power in household systems. Better forecasts can also influence costs across the wider system by improving balancing decisions.

Commercial test

For SQC, the project is a live commercial test of how a quantum-derived system can be used in production settings. For Schneider Electric, it offers a way to assess whether a quantum-enhanced approach can improve operational models already used in energy management.

According to SQC, Watermelon was launched in 2025 and has been deployed in sectors including telecommunications, banking, and high-frequency trading. The system is available through cloud access and hardware sales.

Schneider Electric said the changing mix of consumer energy assets is increasing complexity across the electricity system. This includes the growth of rooftop solar, batteries, and electric vehicle charging, all of which can shift demand patterns and export behaviour at the household level.

Colette Munro, Pacific Zone President, Schneider Electric, said: "The energy system is becoming more dynamic with variables like rooftop solar, EVs, and home batteries creating 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."

The funding decision places the partnership among a small group of projects backed by Australia's Critical Technologies Challenge Program, which is intended to support practical applications of emerging technologies in national priority areas.