Grid Cost Allocation in Peer-to-Peer Electricity Markets: Benchmarking Classical and Quantum Optimization Approaches

David Bucher, Daniel Porawski, Benedikt Wimmer, Jonas Nüßlein, Corey O’Meara, Giorgio Cortiana, Claudia Linnhoff-Popien

2025

Abstract

This paper presents a novel optimization approach for allocating grid operation costs in Peer-to-Peer (P2P) electricity markets using Quantum Computing (QC). We develop a Quadratic Unconstrained Binary Optimization (QUBO) model that matches logical power flows between producer-consumer pairs with the physical power flow to distribute grid usage costs fairly. The model is evaluated on IEEE test cases with up to 57 nodes, comparing Quantum Annealing (QA), hybrid quantum-classical algorithms, and classical optimization approaches. Our results show that while the model effectively allocates grid operation costs, QA performs poorly in comparison despite extensive hyperparameter optimization. The classical branch-and-cut method outperforms all solvers, including classical heuristics, and shows the most advantageous scaling behavior. The findings may suggest that binary least-squares optimization problems may not be suitable candidates for near-term quantum utility.

Paper Citation

in Harvard Style

Bucher D., Porawski D., Wimmer B., Nüßlein J., O’Meara C., Cortiana G. and Linnhoff-Popien C. (2025). Grid Cost Allocation in Peer-to-Peer Electricity Markets: Benchmarking Classical and Quantum Optimization Approaches. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: QAIO; ISBN 978-989-758-737-5, SciTePress, pages 751-762. DOI: 10.5220/0013391400003890

in Bibtex Style

@conference{qaio25,
author={David Bucher and Daniel Porawski and Benedikt Wimmer and Jonas Nüßlein and Corey O’Meara and Giorgio Cortiana and Claudia Linnhoff-Popien},
title={Grid Cost Allocation in Peer-to-Peer Electricity Markets: Benchmarking Classical and Quantum Optimization Approaches},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: QAIO},
year={2025},
pages={751-762},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013391400003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: QAIO
TI - Grid Cost Allocation in Peer-to-Peer Electricity Markets: Benchmarking Classical and Quantum Optimization Approaches
SN - 978-989-758-737-5
AU - Bucher D.
AU - Porawski D.
AU - Wimmer B.
AU - Nüßlein J.
AU - O’Meara C.
AU - Cortiana G.
AU - Linnhoff-Popien C.
PY - 2025
SP - 751
EP - 762
DO - 10.5220/0013391400003890
PB - SciTePress