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We present a method to formulate the unit commitment problem in energyproduction as quadratic unconstrained binary optimization (QUBO) problem, whichcan be solved by classical algorithms and quantum computers. We suggest a firstapproach to consider uncertainties in the renewable energy supply, power demandand machine failures. We show how to find cost-saving solutions of the UCPunder these uncertainties on quantum computers. We also conduct a study withdifferent problem sizes and we compare results of simulated annealing withresults from quantum annealing machines.

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