Hybrid Quantum System Speeds Up Energy Grid Scheduling
The proof-of-concept uses partitioned subproblems to outperform classical models in decentralized energy management.
Updated on Oct. 31, 2026 in Quantum Computing
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E.ON and Qoro Quantum have demonstrated a hybrid quantum-classical proof-of-concept designed to optimize peer-to-peer energy grid scheduling. The researchers successfully outperformed classical baselines on the PEGASE-1354 bus benchmark using IBM quantum hardware.
Why it matters
Peer-to-peer energy scheduling involves combinatorial complexity that often exceeds the capabilities of classical systems and the current qubit counts of commercial quantum processors. This hybrid approach suggests a pathway to managing decentralized grid workloads by breaking them into manageable, quantum-ready subproblems.
The team utilized spectral graph partitioning to process the PEGASE-1354 bus model, which requires 1,710 qubits, by fragmenting it into 50-qubit partitions. This spatial circuit packing resulted in a 3x reduction in hardware execution time.
The players
E.ON
A European energy utility focused on power distribution and sustainable infrastructure.
Qoro Quantum
A quantum software developer specializing in optimization algorithms and the Divi open-source SDK.
IBM
A global hardware provider whose superconducting quantum processors served as the computation platform for the project.
The details
The system employs the Quantum Approximate Optimization Algorithm (QAOA), a procedure designed for solving combinatorial optimization problems by iteratively finding an approximate solution. To handle grid constraints that exceed current hardware capacity, the team implemented classical feasibility repair, a technique that enforces physical grid rules on the output generated by the quantum processor. The process utilizes the open-source Divi software development kit to orchestrate communication between the classical host and IBM quantum hardware.
Timeline
2025: The project was conducted as part of the SparQ 2025 program.
The Tech Race
This work follows the industry trend of using hybrid architectures to circumvent current quantum hardware limitations such as low qubit counts and high error rates. It advances the race to move quantum applications from theoretical simulations toward the optimization of large-scale infrastructure systems.
This research is currently in the proof-of-concept stage and does not immediately affect existing energy grid operations or consumer pricing. Qoro Quantum plans to release tools from this project into the open-source Divi ecosystem, potentially enabling other developers to refine grid scheduling algorithms.
The takeaway
The research establishes a framework for using hybrid quantum computing to address complex combinatorial grid scheduling problems. Future industry benchmarks will confirm whether this approach maintains its speed advantage as grid data complexity increases beyond the 1,710-qubit PEGASE model.
Further reading
Learn more about the latest research in Quantum Computing.
Source note: This article includes information reported by AZoQuantum.
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