A Quantum Computing Approach for the Unit Commitment Problem

TL;DR

This paper models the complex unit commitment problem in energy planning as a quadratic unconstrained optimization problem suitable for quantum computing, demonstrating potential advantages in solution quality and resource efficiency.

Contribution

It introduces a novel quantum computing formulation for the UCP, enabling more efficient solutions compared to traditional methods.

Findings

Reduced qubit usage and improved connectivity in quantum implementation

Enhanced solution quality for the unit commitment problem

Feasibility of quantum approach for complex energy planning tasks

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 \emph{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.