Towards optimization under uncertainty for fundamental models in energy markets using quantum computers

• URL: http://arxiv.org/abs/2301.01108v1
• Date: Tue, 3 Jan 2023 14:07:15 GMT
• Title: Towards optimization under uncertainty for fundamental models in energy markets using quantum computers
• Authors: M.C. Braun, T. Decker, N. Hegemann, S.F. Kerstan, F. Lorenz
• Abstract summary: We suggest a first approach to consider uncertainties in the renewable energy supply, power demand and machine failures. We show how to find cost-saving solutions of the UCP under these uncertainties on quantum computers.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a method to formulate the unit commitment problem in energy production as quadratic unconstrained binary optimization (QUBO) problem, which can be solved by classical algorithms and quantum computers. We suggest a first approach to consider uncertainties in the renewable energy supply, power demand and machine failures. We show how to find cost-saving solutions of the UCP under these uncertainties on quantum computers. We also conduct a study with different problem sizes and we compare results of simulated annealing with results from quantum annealing machines.

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