Preprint
Leveraging Quantum Annealing for Large-Scale Household Energy Scheduling with Hydrogen Storage
ArXiv.org
Cornell University
08/03/2026
Abstract
Hydrogen integration into microgrids facilitates the absorption of intermittencies from renewable energy resources. However, significant challenges remain due to complex optimization problems, particularly in large-scale applications involving multiple fuel cells (FCs) and electrolyzers (ELs) with numerous binary decision variables. This paper presents a hierarchical quantum annealing (QA) model predictive control-based power allocation framework aimed at accelerating these optimization problems. First, in a day-ahead stage, the framework determines the startup and shutdown of the FCs and ELs. The short-term stage then refines the output power of the FCs and the hydrogen generation rate of the ELs. The feasibility is evaluated through a case study consisting of multiple households in Australia. Our findings demonstrate that while the traditional optimization approach performs satisfactorily in scenarios with a small number of households, the QA approach becomes more appropriate and effectively solves the problem within an acceptable range as the number of connected households increases.
Details
- Title
- Leveraging Quantum Annealing for Large-Scale Household Energy Scheduling with Hydrogen Storage
- Authors/Creators
- Arash KhalatbarisoltaniAmin MahmoudiJie HanMuhammad SaeedWenxue LiuJinwen LiSolmaz KahourzadeAmirmehdi YazdaniXiaosong Hu
- Publication Details
- ArXiv.org
- Publisher
- Cornell University
- Identifiers
- 991005870933507891
- Murdoch Affiliation
- School of Engineering and Energy
- Language
- English
- Resource Type
- Preprint
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