Quantum Restricted Boltzmann Machine for Fast Unit Commitment

Abstract

Unit commitment (UC) problems must be solved repeatedly to ensure power system reliability, yet face computational challenges from growing system scale and fast response requirements. This letter proposes a quantum restricted Boltzmann machine (qRBM) method that first predicts UC patterns via quantum-hardware-compatible energy scoring, then recovers optimal solutions through affine mapping. Compared to existing work, this method reduces the qubits needed for the same UC problem by 223 times and computation time by 99.96%.

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