SQC's quantum processor lifts energy forecasting accuracy by 20%
SQC won $3.6 million to develop quantum AI that improves renewable energy forecasting with Schneider Electric and UNSW.
SQC, a UNSW spinout founded by former Australian of the Year Professor Michelle Simmons, tested a quantum-enhanced AI processor called Watermelon with energy company Schneider Electric. Early results were striking: next-day energy demand forecasting improved by an average of 20% compared to traditional computing, with some tests reaching 41% better accuracy.
Quantum-enhanced AI can spot complex patterns in energy data that older systems miss and may cut the computing power needed for complex forecasts. As homes add solar panels, batteries and electric vehicles, predicting when power is used, stored and sent back becomes harder and more crucial for grid stability.
Adelaide's QuantX Labs received $2.2 million to build a quantum clock to keep electricity networks accurately synchronised.
- $3.6 million
- SQC funding
- 20% average, up to 41%
- Accuracy improvement
- $2.2 million
- QuantX funding
- 2017
- Founded
Why it mattersBetter energy forecasting could help keep power networks stable as Australia's household energy systems grow more complex with solar, storage and electric vehicles.
AustraliaThe funding backs Australian-developed quantum technology competing globally; SQC's tool could eventually reduce energy costs and grid strain for Australian homes.
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