Modeling Energy Communities: A Case Study of Quantum Approximate Optimization on a Superconducting Processor

Modeling Energy Communities: A Case Study of Quantum Approximate Optimization on a Superconducting Processor

This work explores the use of variational quantum algorithms to optimize energy distribution among users in energy communities, using real data from a community lab. This requires integrating various energy sources, storage solutions, and the ability to respond to variations in demand within energy...

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Bibliographic Details
Main Authors: Mateo Alonso, Guillermo Rubinos Rodriguez, Pablo Diez-Valle, Ana Garbayo, Xela Garcia-Santiago, Gonzalo Blazquez Gil
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Energy communities
energy efficiency
optimization models
quantum algorithms
quantum computing
quantum optimization
Online Access:https://ieeexplore.ieee.org/document/11030452/
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