Energy
The fuel that keeps our world moving
Grid Management
The energy transition increases electricity demand while supply becomes less predictable, which strongly increases the complexity of grid management.
One way to deal with this complexity is to identify parts of the grid which in space or time have similar ‘operating modes’, and can serve as a basis for aggregating grid information or reduce the admissible set-in optimization processes.
Graph theory offers a powerful approach to model electricity grids[2] and similar ‘operating modes’ of the electricity grid can be identified through studying graph similarity.
Graph kernels can be an efficient tool to study graph isomorphism (similarity), but more expressive kernels can be beyond reach of classical computers.
PASQAL and French utility RTE are testing PASQAL’s proprietary quantum graph kernel method.
Such graph machine learning problems can be natively implemented through the analog mode of our neutral atoms quantum processor, which makes them a prime candidate for quantum advantage n the very near-term.

Quantum in Real Life

BASF
"PASQAL’s quantum solutions are ideal for simplifying BASF’s complex computational simulations. Leveraging PASQAL’s quantum processors for weather modeling validates quantum computing’s ability to go beyond what can be achieved with classical high performance computing. This transformational technology helps us prepare for climate change impacts and drive progress toward a more sustainable future."
John Manobianco
Senior Weather Modeler at BASF
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