E.ON and Qoro test hybrid quantum computing for scheduling local energy trades

[Ava_75]

Quantum computing is being tested on a very practical energy problem. The Quantum Insider reports that Qoro Quantum, E.ON and the UK's National Quantum Computing Centre have built a proof of concept pipeline for scheduling peer to peer energy trades

The trades involve so called prosumers, households and businesses that both use and produce electricity, for example through solar panels. Scheduling who trades with whom, and when, quickly becomes a very large optimisation problem as more people take part. The project was funded through the SparQ 2025 programme and overseen by the STFC Hartree Centre and the NQCC

The pipeline first splits a large grid into smaller subgrids. Qoro's open source Divi software then breaks the work into pieces needing up to 50 qubits, its Maestro engine handles large simulations, and a quantum algorithm called QAOA suggests candidate solutions that a classical step then repairs so they are valid

It ran on IBM quantum processors, using a technique that packs several circuits onto one chip, which cut hardware time by about three times. A realistic grid based on a standard benchmark would normally need around 1,710 qubits. The hybrid approach gave lower errors than standard classical baselines and reduced the number of scheduling rounds. Dr Corey O'Meara, E.ON's chief quantum scientist, said efficient scheduling is key to scalable peer to peer energy markets

This is a proof of concept rather than a system running on a real grid, and the announcement is fairly promotional. Breaking big problems into chunks that today's machines can handle is a sensible strategy, though. Energy is one of the more realistic early targets for quantum optimisation

Could quantum computing help run local energy markets one day? And is splitting problems into small pieces the right approach for current hardware?

E.ON and Qoro Test Hybrid Quantum Computing for Energy Schedulingthequantuminsider.com