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Quantum Optimization

A Quantum Computing Approach for the Unit Commitment Problem

arXiv
Authors: Pascal Halffmann, Patrick Holzer, Kai Plociennik, Michael Trebing

Year

2022

Paper ID

14137

Status

Preprint

Abstract Read

~2 min

Abstract Words

99

Citations

N/A

Abstract

Planning energy production is a challenging task due to its cost-sensitivity, fast-moving energy markets, uncertainties in demand, and technical constraints of power plants. Thus, more complex models of this so-called unit commitment problem (UCP) have to be solved more rapidly, a task that probably can be solved more efficiently via quantum computing. In this article, we model a UCP with minimum running and idle times as a quadratic unconstrained optimization problem to solve it on quantum computing hardware. First experiments confirm the advantages of our formulation in terms of qubit usage and connectivity and most importantly solution quality.

Why This Paper Matters

  • This paper contributes to the Quantum Optimization research area in the Quantum Articles archive.
  • It adds a 2022 reference point for readers tracking recent quantum research.
  • Planning energy production is a challenging task due to its cost-sensitivity, fast-moving energy markets, uncertainties in demand, and technical constraints of power plants.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2212.06480 [2] arXiv https://arxiv.org/abs/2212.06480 [3] Publisher https://arxiv.org/abs/2212.06480

Local Citation Graph (Related-Paper Links)

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