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.
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Notes
- 1.
Remark that in our example this parameter is set to 1 and does not need any binarization, increased parameter values worsen the generic model.
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Acknowledgements
This publication has been funded by the German Federal Ministry for Economic Affairs and Climate Action (grant no. 03EI1025A).
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Halffmann, P., Holzer, P., Plociennik, K., Trebing, M. (2023). A Quantum Computing Approach for the Unit Commitment Problem. In: Grothe, O., Nickel, S., Rebennack, S., Stein, O. (eds) Operations Research Proceedings 2022. OR 2022. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-24907-5_14
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