Quantum Optimization for the Future Energy Grid: Summary and Quantum Utility Prospects
Abstract
In this project summary paper, we summarize the key results and use-cases explored in the German Federal Ministry of Education and Research (BMBF) funded project "Q-GRID" which aims to assess potential quantum utility optimization applications in the electrical grid. The project focuses on two layers of optimization problems relevant to decentralized energy generation and transmission as well as novel energy transportation/exchange methods such as Peer-2-Peer energy trading and microgrid formation. For select energy grid optimization problems, we demonstrate exponential classical optimizer runtime scaling even for small problem instances, and present initial findings that variational quantum algorithms such as QAOA and hybrid quantum annealing solvers may provide more favourable runtime scaling to obtain similar solution quality. These initial results suggest that quantum computing may be a key enabling technology in the future energy transition insofar that they may be able to solve business problems which are already challenging at small problem instance sizes.
Cite
@article{arxiv.2403.17495,
title = {Quantum Optimization for the Future Energy Grid: Summary and Quantum Utility Prospects},
author = {Jonas Blenninger and David Bucher and Giorgio Cortiana and Kumar Ghosh and Naeimeh Mohseni and Jonas Nüßlein and Corey O'Meara and Daniel Porawski and Benedikt Wimmer},
journal= {arXiv preprint arXiv:2403.17495},
year = {2024}
}
Comments
12 pages. arXiv admin note: text overlap with arXiv:2309.05502